linux/mm/swap_state.c

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License cleanup: add SPDX GPL-2.0 license identifier to files with no license Many source files in the tree are missing licensing information, which makes it harder for compliance tools to determine the correct license. By default all files without license information are under the default license of the kernel, which is GPL version 2. Update the files which contain no license information with the 'GPL-2.0' SPDX license identifier. The SPDX identifier is a legally binding shorthand, which can be used instead of the full boiler plate text. This patch is based on work done by Thomas Gleixner and Kate Stewart and Philippe Ombredanne. How this work was done: Patches were generated and checked against linux-4.14-rc6 for a subset of the use cases: - file had no licensing information it it. - file was a */uapi/* one with no licensing information in it, - file was a */uapi/* one with existing licensing information, Further patches will be generated in subsequent months to fix up cases where non-standard license headers were used, and references to license had to be inferred by heuristics based on keywords. The analysis to determine which SPDX License Identifier to be applied to a file was done in a spreadsheet of side by side results from of the output of two independent scanners (ScanCode & Windriver) producing SPDX tag:value files created by Philippe Ombredanne. Philippe prepared the base worksheet, and did an initial spot review of a few 1000 files. The 4.13 kernel was the starting point of the analysis with 60,537 files assessed. Kate Stewart did a file by file comparison of the scanner results in the spreadsheet to determine which SPDX license identifier(s) to be applied to the file. She confirmed any determination that was not immediately clear with lawyers working with the Linux Foundation. Criteria used to select files for SPDX license identifier tagging was: - Files considered eligible had to be source code files. - Make and config files were included as candidates if they contained >5 lines of source - File already had some variant of a license header in it (even if <5 lines). All documentation files were explicitly excluded. The following heuristics were used to determine which SPDX license identifiers to apply. - when both scanners couldn't find any license traces, file was considered to have no license information in it, and the top level COPYING file license applied. For non */uapi/* files that summary was: SPDX license identifier # files ---------------------------------------------------|------- GPL-2.0 11139 and resulted in the first patch in this series. If that file was a */uapi/* path one, it was "GPL-2.0 WITH Linux-syscall-note" otherwise it was "GPL-2.0". Results of that was: SPDX license identifier # files ---------------------------------------------------|------- GPL-2.0 WITH Linux-syscall-note 930 and resulted in the second patch in this series. - if a file had some form of licensing information in it, and was one of the */uapi/* ones, it was denoted with the Linux-syscall-note if any GPL family license was found in the file or had no licensing in it (per prior point). Results summary: SPDX license identifier # files ---------------------------------------------------|------ GPL-2.0 WITH Linux-syscall-note 270 GPL-2.0+ WITH Linux-syscall-note 169 ((GPL-2.0 WITH Linux-syscall-note) OR BSD-2-Clause) 21 ((GPL-2.0 WITH Linux-syscall-note) OR BSD-3-Clause) 17 LGPL-2.1+ WITH Linux-syscall-note 15 GPL-1.0+ WITH Linux-syscall-note 14 ((GPL-2.0+ WITH Linux-syscall-note) OR BSD-3-Clause) 5 LGPL-2.0+ WITH Linux-syscall-note 4 LGPL-2.1 WITH Linux-syscall-note 3 ((GPL-2.0 WITH Linux-syscall-note) OR MIT) 3 ((GPL-2.0 WITH Linux-syscall-note) AND MIT) 1 and that resulted in the third patch in this series. - when the two scanners agreed on the detected license(s), that became the concluded license(s). - when there was disagreement between the two scanners (one detected a license but the other didn't, or they both detected different licenses) a manual inspection of the file occurred. - In most cases a manual inspection of the information in the file resulted in a clear resolution of the license that should apply (and which scanner probably needed to revisit its heuristics). - When it was not immediately clear, the license identifier was confirmed with lawyers working with the Linux Foundation. - If there was any question as to the appropriate license identifier, the file was flagged for further research and to be revisited later in time. In total, over 70 hours of logged manual review was done on the spreadsheet to determine the SPDX license identifiers to apply to the source files by Kate, Philippe, Thomas and, in some cases, confirmation by lawyers working with the Linux Foundation. Kate also obtained a third independent scan of the 4.13 code base from FOSSology, and compared selected files where the other two scanners disagreed against that SPDX file, to see if there was new insights. The Windriver scanner is based on an older version of FOSSology in part, so they are related. Thomas did random spot checks in about 500 files from the spreadsheets for the uapi headers and agreed with SPDX license identifier in the files he inspected. For the non-uapi files Thomas did random spot checks in about 15000 files. In initial set of patches against 4.14-rc6, 3 files were found to have copy/paste license identifier errors, and have been fixed to reflect the correct identifier. Additionally Philippe spent 10 hours this week doing a detailed manual inspection and review of the 12,461 patched files from the initial patch version early this week with: - a full scancode scan run, collecting the matched texts, detected license ids and scores - reviewing anything where there was a license detected (about 500+ files) to ensure that the applied SPDX license was correct - reviewing anything where there was no detection but the patch license was not GPL-2.0 WITH Linux-syscall-note to ensure that the applied SPDX license was correct This produced a worksheet with 20 files needing minor correction. This worksheet was then exported into 3 different .csv files for the different types of files to be modified. These .csv files were then reviewed by Greg. Thomas wrote a script to parse the csv files and add the proper SPDX tag to the file, in the format that the file expected. This script was further refined by Greg based on the output to detect more types of files automatically and to distinguish between header and source .c files (which need different comment types.) Finally Greg ran the script using the .csv files to generate the patches. Reviewed-by: Kate Stewart <kstewart@linuxfoundation.org> Reviewed-by: Philippe Ombredanne <pombredanne@nexb.com> Reviewed-by: Thomas Gleixner <tglx@linutronix.de> Signed-off-by: Greg Kroah-Hartman <gregkh@linuxfoundation.org>
2017-11-01 22:07:57 +08:00
// SPDX-License-Identifier: GPL-2.0
/*
* linux/mm/swap_state.c
*
* Copyright (C) 1991, 1992, 1993, 1994 Linus Torvalds
* Swap reorganised 29.12.95, Stephen Tweedie
*
* Rewritten to use page cache, (C) 1998 Stephen Tweedie
*/
#include <linux/mm.h>
include cleanup: Update gfp.h and slab.h includes to prepare for breaking implicit slab.h inclusion from percpu.h percpu.h is included by sched.h and module.h and thus ends up being included when building most .c files. percpu.h includes slab.h which in turn includes gfp.h making everything defined by the two files universally available and complicating inclusion dependencies. percpu.h -> slab.h dependency is about to be removed. Prepare for this change by updating users of gfp and slab facilities include those headers directly instead of assuming availability. As this conversion needs to touch large number of source files, the following script is used as the basis of conversion. http://userweb.kernel.org/~tj/misc/slabh-sweep.py The script does the followings. * Scan files for gfp and slab usages and update includes such that only the necessary includes are there. ie. if only gfp is used, gfp.h, if slab is used, slab.h. * When the script inserts a new include, it looks at the include blocks and try to put the new include such that its order conforms to its surrounding. It's put in the include block which contains core kernel includes, in the same order that the rest are ordered - alphabetical, Christmas tree, rev-Xmas-tree or at the end if there doesn't seem to be any matching order. * If the script can't find a place to put a new include (mostly because the file doesn't have fitting include block), it prints out an error message indicating which .h file needs to be added to the file. The conversion was done in the following steps. 1. The initial automatic conversion of all .c files updated slightly over 4000 files, deleting around 700 includes and adding ~480 gfp.h and ~3000 slab.h inclusions. The script emitted errors for ~400 files. 2. Each error was manually checked. Some didn't need the inclusion, some needed manual addition while adding it to implementation .h or embedding .c file was more appropriate for others. This step added inclusions to around 150 files. 3. The script was run again and the output was compared to the edits from #2 to make sure no file was left behind. 4. Several build tests were done and a couple of problems were fixed. e.g. lib/decompress_*.c used malloc/free() wrappers around slab APIs requiring slab.h to be added manually. 5. The script was run on all .h files but without automatically editing them as sprinkling gfp.h and slab.h inclusions around .h files could easily lead to inclusion dependency hell. Most gfp.h inclusion directives were ignored as stuff from gfp.h was usually wildly available and often used in preprocessor macros. Each slab.h inclusion directive was examined and added manually as necessary. 6. percpu.h was updated not to include slab.h. 7. Build test were done on the following configurations and failures were fixed. CONFIG_GCOV_KERNEL was turned off for all tests (as my distributed build env didn't work with gcov compiles) and a few more options had to be turned off depending on archs to make things build (like ipr on powerpc/64 which failed due to missing writeq). * x86 and x86_64 UP and SMP allmodconfig and a custom test config. * powerpc and powerpc64 SMP allmodconfig * sparc and sparc64 SMP allmodconfig * ia64 SMP allmodconfig * s390 SMP allmodconfig * alpha SMP allmodconfig * um on x86_64 SMP allmodconfig 8. percpu.h modifications were reverted so that it could be applied as a separate patch and serve as bisection point. Given the fact that I had only a couple of failures from tests on step 6, I'm fairly confident about the coverage of this conversion patch. If there is a breakage, it's likely to be something in one of the arch headers which should be easily discoverable easily on most builds of the specific arch. Signed-off-by: Tejun Heo <tj@kernel.org> Guess-its-ok-by: Christoph Lameter <cl@linux-foundation.org> Cc: Ingo Molnar <mingo@redhat.com> Cc: Lee Schermerhorn <Lee.Schermerhorn@hp.com>
2010-03-24 16:04:11 +08:00
#include <linux/gfp.h>
#include <linux/kernel_stat.h>
#include <linux/swap.h>
#include <linux/swapops.h>
#include <linux/init.h>
#include <linux/pagemap.h>
#include <linux/backing-dev.h>
swap: allow swap readahead to be merged Swap readahead works fine, but the I/O to disk is almost always done in page size requests, despite the fact that readahead submits 1<<page-cluster pages at a time. On older kernels the old per device plugging behavior might have captured this and merged the requests, but currently all comes down to much more I/Os than required. On a single device this might not be an issue, but as soon as a server runs on shared san resources savin I/Os not only improves swapin throughput but also provides a lower resource utilization. With a load running KVM in a lot of memory overcommitment (the hot memory is 1.5 times the host memory) swapping throughput improves significantly and the lead feels more responsive as well as achieves more throughput. In a test setup with 16 swap disks running blocktrace on one of those disks shows the improved merging: Prior: Reads Queued: 560,888, 2,243MiB Writes Queued: 226,242, 904,968KiB Read Dispatches: 544,701, 2,243MiB Write Dispatches: 159,318, 904,968KiB Reads Requeued: 0 Writes Requeued: 0 Reads Completed: 544,716, 2,243MiB Writes Completed: 159,321, 904,980KiB Read Merges: 16,187, 64,748KiB Write Merges: 61,744, 246,976KiB IO unplugs: 149,614 Timer unplugs: 2,940 With the patch: Reads Queued: 734,315, 2,937MiB Writes Queued: 300,188, 1,200MiB Read Dispatches: 214,972, 2,937MiB Write Dispatches: 215,176, 1,200MiB Reads Requeued: 0 Writes Requeued: 0 Reads Completed: 214,971, 2,937MiB Writes Completed: 215,177, 1,200MiB Read Merges: 519,343, 2,077MiB Write Merges: 73,325, 293,300KiB IO unplugs: 337,130 Timer unplugs: 11,184 I got ~10% to ~40% more throughput in my cases and at the same time much lower cpu consumption when broken down per transferred kilobyte (the majority of that due to saved interrupts and better cache handling). In a shared SAN others might get an additional benefit as well, because this now causes less protocol overhead. Signed-off-by: Christian Ehrhardt <ehrhardt@linux.vnet.ibm.com> Acked-by: Rik van Riel <riel@redhat.com> Acked-by: Jens Axboe <axboe@kernel.dk> Reviewed-by: Minchan Kim <minchan@kernel.org> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2012-08-01 07:41:44 +08:00
#include <linux/blkdev.h>
#include <linux/pagevec.h>
#include <linux/migrate.h>
mm/swap: split swap cache into 64MB trunks The patch is to improve the scalability of the swap out/in via using fine grained locks for the swap cache. In current kernel, one address space will be used for each swap device. And in the common configuration, the number of the swap device is very small (one is typical). This causes the heavy lock contention on the radix tree of the address space if multiple tasks swap out/in concurrently. But in fact, there is no dependency between pages in the swap cache. So that, we can split the one shared address space for each swap device into several address spaces to reduce the lock contention. In the patch, the shared address space is split into 64MB trunks. 64MB is chosen to balance the memory space usage and effect of lock contention reduction. The size of struct address_space on x86_64 architecture is 408B, so with the patch, 6528B more memory will be used for every 1GB swap space on x86_64 architecture. One address space is still shared for the swap entries in the same 64M trunks. To avoid lock contention for the first round of swap space allocation, the order of the swap clusters in the initial free clusters list is changed. The swap space distance between the consecutive swap clusters in the free cluster list is at least 64M. After the first round of allocation, the swap clusters are expected to be freed randomly, so the lock contention should be reduced effectively. Link: http://lkml.kernel.org/r/735bab895e64c930581ffb0a05b661e01da82bc5.1484082593.git.tim.c.chen@linux.intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Signed-off-by: Tim Chen <tim.c.chen@linux.intel.com> Cc: Aaron Lu <aaron.lu@intel.com> Cc: Andi Kleen <ak@linux.intel.com> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Christian Borntraeger <borntraeger@de.ibm.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Hillf Danton <hillf.zj@alibaba-inc.com> Cc: Huang Ying <ying.huang@intel.com> Cc: Hugh Dickins <hughd@google.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Corbet <corbet@lwn.net> escreveu: Cc: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Vladimir Davydov <vdavydov.dev@gmail.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-02-23 07:45:26 +08:00
#include <linux/vmalloc.h>
mm/swap: add cache for swap slots allocation We add per cpu caches for swap slots that can be allocated and freed quickly without the need to touch the swap info lock. Two separate caches are maintained for swap slots allocated and swap slots returned. This is to allow the swap slots to be returned to the global pool in a batch so they will have a chance to be coaelesced with other slots in a cluster. We do not reuse the slots that are returned right away, as it may increase fragmentation of the slots. The swap allocation cache is protected by a mutex as we may sleep when searching for empty slots in cache. The swap free cache is protected by a spin lock as we cannot sleep in the free path. We refill the swap slots cache when we run out of slots, and we disable the swap slots cache and drain the slots if the global number of slots fall below a low watermark threshold. We re-enable the cache agian when the slots available are above a high watermark. [ying.huang@intel.com: use raw_cpu_ptr over this_cpu_ptr for swap slots access] [tim.c.chen@linux.intel.com: add comments on locks in swap_slots.h] Link: http://lkml.kernel.org/r/20170118180327.GA24225@linux.intel.com Link: http://lkml.kernel.org/r/35de301a4eaa8daa2977de6e987f2c154385eb66.1484082593.git.tim.c.chen@linux.intel.com Signed-off-by: Tim Chen <tim.c.chen@linux.intel.com> Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Reviewed-by: Michal Hocko <mhocko@suse.com> Cc: Aaron Lu <aaron.lu@intel.com> Cc: Andi Kleen <ak@linux.intel.com> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Christian Borntraeger <borntraeger@de.ibm.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Hillf Danton <hillf.zj@alibaba-inc.com> Cc: Huang Ying <ying.huang@intel.com> Cc: Hugh Dickins <hughd@google.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Corbet <corbet@lwn.net> escreveu: Cc: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Vladimir Davydov <vdavydov.dev@gmail.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-02-23 07:45:39 +08:00
#include <linux/swap_slots.h>
mm, THP, swap: delay splitting THP during swap out Patch series "THP swap: Delay splitting THP during swapping out", v11. This patchset is to optimize the performance of Transparent Huge Page (THP) swap. Recently, the performance of the storage devices improved so fast that we cannot saturate the disk bandwidth with single logical CPU when do page swap out even on a high-end server machine. Because the performance of the storage device improved faster than that of single logical CPU. And it seems that the trend will not change in the near future. On the other hand, the THP becomes more and more popular because of increased memory size. So it becomes necessary to optimize THP swap performance. The advantages of the THP swap support include: - Batch the swap operations for the THP to reduce lock acquiring/releasing, including allocating/freeing the swap space, adding/deleting to/from the swap cache, and writing/reading the swap space, etc. This will help improve the performance of the THP swap. - The THP swap space read/write will be 2M sequential IO. It is particularly helpful for the swap read, which are usually 4k random IO. This will improve the performance of the THP swap too. - It will help the memory fragmentation, especially when the THP is heavily used by the applications. The 2M continuous pages will be free up after THP swapping out. - It will improve the THP utilization on the system with the swap turned on. Because the speed for khugepaged to collapse the normal pages into the THP is quite slow. After the THP is split during the swapping out, it will take quite long time for the normal pages to collapse back into the THP after being swapped in. The high THP utilization helps the efficiency of the page based memory management too. There are some concerns regarding THP swap in, mainly because possible enlarged read/write IO size (for swap in/out) may put more overhead on the storage device. To deal with that, the THP swap in should be turned on only when necessary. For example, it can be selected via "always/never/madvise" logic, to be turned on globally, turned off globally, or turned on only for VMA with MADV_HUGEPAGE, etc. This patchset is the first step for the THP swap support. The plan is to delay splitting THP step by step, finally avoid splitting THP during the THP swapping out and swap out/in the THP as a whole. As the first step, in this patchset, the splitting huge page is delayed from almost the first step of swapping out to after allocating the swap space for the THP and adding the THP into the swap cache. This will reduce lock acquiring/releasing for the locks used for the swap cache management. With the patchset, the swap out throughput improves 15.5% (from about 3.73GB/s to about 4.31GB/s) in the vm-scalability swap-w-seq test case with 8 processes. The test is done on a Xeon E5 v3 system. The swap device used is a RAM simulated PMEM (persistent memory) device. To test the sequential swapping out, the test case creates 8 processes, which sequentially allocate and write to the anonymous pages until the RAM and part of the swap device is used up. This patch (of 5): In this patch, splitting huge page is delayed from almost the first step of swapping out to after allocating the swap space for the THP (Transparent Huge Page) and adding the THP into the swap cache. This will batch the corresponding operation, thus improve THP swap out throughput. This is the first step for the THP swap optimization. The plan is to delay splitting the THP step by step and avoid splitting the THP finally. In this patch, one swap cluster is used to hold the contents of each THP swapped out. So, the size of the swap cluster is changed to that of the THP (Transparent Huge Page) on x86_64 architecture (512). For other architectures which want such THP swap optimization, ARCH_USES_THP_SWAP_CLUSTER needs to be selected in the Kconfig file for the architecture. In effect, this will enlarge swap cluster size by 2 times on x86_64. Which may make it harder to find a free cluster when the swap space becomes fragmented. So that, this may reduce the continuous swap space allocation and sequential write in theory. The performance test in 0day shows no regressions caused by this. In the future of THP swap optimization, some information of the swapped out THP (such as compound map count) will be recorded in the swap_cluster_info data structure. The mem cgroup swap accounting functions are enhanced to support charge or uncharge a swap cluster backing a THP as a whole. The swap cluster allocate/free functions are added to allocate/free a swap cluster for a THP. A fair simple algorithm is used for swap cluster allocation, that is, only the first swap device in priority list will be tried to allocate the swap cluster. The function will fail if the trying is not successful, and the caller will fallback to allocate a single swap slot instead. This works good enough for normal cases. If the difference of the number of the free swap clusters among multiple swap devices is significant, it is possible that some THPs are split earlier than necessary. For example, this could be caused by big size difference among multiple swap devices. The swap cache functions is enhanced to support add/delete THP to/from the swap cache as a set of (HPAGE_PMD_NR) sub-pages. This may be enhanced in the future with multi-order radix tree. But because we will split the THP soon during swapping out, that optimization doesn't make much sense for this first step. The THP splitting functions are enhanced to support to split THP in swap cache during swapping out. The page lock will be held during allocating the swap cluster, adding the THP into the swap cache and splitting the THP. So in the code path other than swapping out, if the THP need to be split, the PageSwapCache(THP) will be always false. The swap cluster is only available for SSD, so the THP swap optimization in this patchset has no effect for HDD. [ying.huang@intel.com: fix two issues in THP optimize patch] Link: http://lkml.kernel.org/r/87k25ed8zo.fsf@yhuang-dev.intel.com [hannes@cmpxchg.org: extensive cleanups and simplifications, reduce code size] Link: http://lkml.kernel.org/r/20170515112522.32457-2-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Signed-off-by: Johannes Weiner <hannes@cmpxchg.org> Suggested-by: Andrew Morton <akpm@linux-foundation.org> [for config option] Acked-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> [for changes in huge_memory.c and huge_mm.h] Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Ebru Akagunduz <ebru.akagunduz@gmail.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tejun Heo <tj@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Shaohua Li <shli@kernel.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-07 06:37:18 +08:00
#include <linux/huge_mm.h>
#include <asm/pgtable.h>
/*
* swapper_space is a fiction, retained to simplify the path through
* vmscan's shrink_page_list.
*/
static const struct address_space_operations swap_aops = {
.writepage = swap_writepage,
mm: add support for a filesystem to activate swap files and use direct_IO for writing swap pages Currently swapfiles are managed entirely by the core VM by using ->bmap to allocate space and write to the blocks directly. This effectively ensures that the underlying blocks are allocated and avoids the need for the swap subsystem to locate what physical blocks store offsets within a file. If the swap subsystem is to use the filesystem information to locate the blocks, it is critical that information such as block groups, block bitmaps and the block descriptor table that map the swap file were resident in memory. This patch adds address_space_operations that the VM can call when activating or deactivating swap backed by a file. int swap_activate(struct file *); int swap_deactivate(struct file *); The ->swap_activate() method is used to communicate to the file that the VM relies on it, and the address_space should take adequate measures such as reserving space in the underlying device, reserving memory for mempools and pinning information such as the block descriptor table in memory. The ->swap_deactivate() method is called on sys_swapoff() if ->swap_activate() returned success. After a successful swapfile ->swap_activate, the swapfile is marked SWP_FILE and swapper_space.a_ops will proxy to sis->swap_file->f_mappings->a_ops using ->direct_io to write swapcache pages and ->readpage to read. It is perfectly possible that direct_IO be used to read the swap pages but it is an unnecessary complication. Similarly, it is possible that ->writepage be used instead of direct_io to write the pages but filesystem developers have stated that calling writepage from the VM is undesirable for a variety of reasons and using direct_IO opens up the possibility of writing back batches of swap pages in the future. [a.p.zijlstra@chello.nl: Original patch] Signed-off-by: Mel Gorman <mgorman@suse.de> Acked-by: Rik van Riel <riel@redhat.com> Cc: Christoph Hellwig <hch@infradead.org> Cc: David S. Miller <davem@davemloft.net> Cc: Eric B Munson <emunson@mgebm.net> Cc: Eric Paris <eparis@redhat.com> Cc: James Morris <jmorris@namei.org> Cc: Mel Gorman <mgorman@suse.de> Cc: Mike Christie <michaelc@cs.wisc.edu> Cc: Neil Brown <neilb@suse.de> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Sebastian Andrzej Siewior <sebastian@breakpoint.cc> Cc: Trond Myklebust <Trond.Myklebust@netapp.com> Cc: Xiaotian Feng <dfeng@redhat.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2012-08-01 07:44:55 +08:00
.set_page_dirty = swap_set_page_dirty,
#ifdef CONFIG_MIGRATION
.migratepage = migrate_page,
#endif
};
struct address_space *swapper_spaces[MAX_SWAPFILES] __read_mostly;
static unsigned int nr_swapper_spaces[MAX_SWAPFILES] __read_mostly;
static bool enable_vma_readahead __read_mostly = true;
mm, swap: VMA based swap readahead The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patch, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:36 +08:00
#define SWAP_RA_WIN_SHIFT (PAGE_SHIFT / 2)
#define SWAP_RA_HITS_MASK ((1UL << SWAP_RA_WIN_SHIFT) - 1)
#define SWAP_RA_HITS_MAX SWAP_RA_HITS_MASK
#define SWAP_RA_WIN_MASK (~PAGE_MASK & ~SWAP_RA_HITS_MASK)
#define SWAP_RA_HITS(v) ((v) & SWAP_RA_HITS_MASK)
#define SWAP_RA_WIN(v) (((v) & SWAP_RA_WIN_MASK) >> SWAP_RA_WIN_SHIFT)
#define SWAP_RA_ADDR(v) ((v) & PAGE_MASK)
#define SWAP_RA_VAL(addr, win, hits) \
(((addr) & PAGE_MASK) | \
(((win) << SWAP_RA_WIN_SHIFT) & SWAP_RA_WIN_MASK) | \
((hits) & SWAP_RA_HITS_MASK))
/* Initial readahead hits is 4 to start up with a small window */
#define GET_SWAP_RA_VAL(vma) \
(atomic_long_read(&(vma)->swap_readahead_info) ? : 4)
#define INC_CACHE_INFO(x) do { swap_cache_info.x++; } while (0)
mm, THP, swap: delay splitting THP during swap out Patch series "THP swap: Delay splitting THP during swapping out", v11. This patchset is to optimize the performance of Transparent Huge Page (THP) swap. Recently, the performance of the storage devices improved so fast that we cannot saturate the disk bandwidth with single logical CPU when do page swap out even on a high-end server machine. Because the performance of the storage device improved faster than that of single logical CPU. And it seems that the trend will not change in the near future. On the other hand, the THP becomes more and more popular because of increased memory size. So it becomes necessary to optimize THP swap performance. The advantages of the THP swap support include: - Batch the swap operations for the THP to reduce lock acquiring/releasing, including allocating/freeing the swap space, adding/deleting to/from the swap cache, and writing/reading the swap space, etc. This will help improve the performance of the THP swap. - The THP swap space read/write will be 2M sequential IO. It is particularly helpful for the swap read, which are usually 4k random IO. This will improve the performance of the THP swap too. - It will help the memory fragmentation, especially when the THP is heavily used by the applications. The 2M continuous pages will be free up after THP swapping out. - It will improve the THP utilization on the system with the swap turned on. Because the speed for khugepaged to collapse the normal pages into the THP is quite slow. After the THP is split during the swapping out, it will take quite long time for the normal pages to collapse back into the THP after being swapped in. The high THP utilization helps the efficiency of the page based memory management too. There are some concerns regarding THP swap in, mainly because possible enlarged read/write IO size (for swap in/out) may put more overhead on the storage device. To deal with that, the THP swap in should be turned on only when necessary. For example, it can be selected via "always/never/madvise" logic, to be turned on globally, turned off globally, or turned on only for VMA with MADV_HUGEPAGE, etc. This patchset is the first step for the THP swap support. The plan is to delay splitting THP step by step, finally avoid splitting THP during the THP swapping out and swap out/in the THP as a whole. As the first step, in this patchset, the splitting huge page is delayed from almost the first step of swapping out to after allocating the swap space for the THP and adding the THP into the swap cache. This will reduce lock acquiring/releasing for the locks used for the swap cache management. With the patchset, the swap out throughput improves 15.5% (from about 3.73GB/s to about 4.31GB/s) in the vm-scalability swap-w-seq test case with 8 processes. The test is done on a Xeon E5 v3 system. The swap device used is a RAM simulated PMEM (persistent memory) device. To test the sequential swapping out, the test case creates 8 processes, which sequentially allocate and write to the anonymous pages until the RAM and part of the swap device is used up. This patch (of 5): In this patch, splitting huge page is delayed from almost the first step of swapping out to after allocating the swap space for the THP (Transparent Huge Page) and adding the THP into the swap cache. This will batch the corresponding operation, thus improve THP swap out throughput. This is the first step for the THP swap optimization. The plan is to delay splitting the THP step by step and avoid splitting the THP finally. In this patch, one swap cluster is used to hold the contents of each THP swapped out. So, the size of the swap cluster is changed to that of the THP (Transparent Huge Page) on x86_64 architecture (512). For other architectures which want such THP swap optimization, ARCH_USES_THP_SWAP_CLUSTER needs to be selected in the Kconfig file for the architecture. In effect, this will enlarge swap cluster size by 2 times on x86_64. Which may make it harder to find a free cluster when the swap space becomes fragmented. So that, this may reduce the continuous swap space allocation and sequential write in theory. The performance test in 0day shows no regressions caused by this. In the future of THP swap optimization, some information of the swapped out THP (such as compound map count) will be recorded in the swap_cluster_info data structure. The mem cgroup swap accounting functions are enhanced to support charge or uncharge a swap cluster backing a THP as a whole. The swap cluster allocate/free functions are added to allocate/free a swap cluster for a THP. A fair simple algorithm is used for swap cluster allocation, that is, only the first swap device in priority list will be tried to allocate the swap cluster. The function will fail if the trying is not successful, and the caller will fallback to allocate a single swap slot instead. This works good enough for normal cases. If the difference of the number of the free swap clusters among multiple swap devices is significant, it is possible that some THPs are split earlier than necessary. For example, this could be caused by big size difference among multiple swap devices. The swap cache functions is enhanced to support add/delete THP to/from the swap cache as a set of (HPAGE_PMD_NR) sub-pages. This may be enhanced in the future with multi-order radix tree. But because we will split the THP soon during swapping out, that optimization doesn't make much sense for this first step. The THP splitting functions are enhanced to support to split THP in swap cache during swapping out. The page lock will be held during allocating the swap cluster, adding the THP into the swap cache and splitting the THP. So in the code path other than swapping out, if the THP need to be split, the PageSwapCache(THP) will be always false. The swap cluster is only available for SSD, so the THP swap optimization in this patchset has no effect for HDD. [ying.huang@intel.com: fix two issues in THP optimize patch] Link: http://lkml.kernel.org/r/87k25ed8zo.fsf@yhuang-dev.intel.com [hannes@cmpxchg.org: extensive cleanups and simplifications, reduce code size] Link: http://lkml.kernel.org/r/20170515112522.32457-2-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Signed-off-by: Johannes Weiner <hannes@cmpxchg.org> Suggested-by: Andrew Morton <akpm@linux-foundation.org> [for config option] Acked-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> [for changes in huge_memory.c and huge_mm.h] Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Ebru Akagunduz <ebru.akagunduz@gmail.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tejun Heo <tj@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Shaohua Li <shli@kernel.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-07 06:37:18 +08:00
#define ADD_CACHE_INFO(x, nr) do { swap_cache_info.x += (nr); } while (0)
static struct {
unsigned long add_total;
unsigned long del_total;
unsigned long find_success;
unsigned long find_total;
} swap_cache_info;
unsigned long total_swapcache_pages(void)
{
mm/swap: split swap cache into 64MB trunks The patch is to improve the scalability of the swap out/in via using fine grained locks for the swap cache. In current kernel, one address space will be used for each swap device. And in the common configuration, the number of the swap device is very small (one is typical). This causes the heavy lock contention on the radix tree of the address space if multiple tasks swap out/in concurrently. But in fact, there is no dependency between pages in the swap cache. So that, we can split the one shared address space for each swap device into several address spaces to reduce the lock contention. In the patch, the shared address space is split into 64MB trunks. 64MB is chosen to balance the memory space usage and effect of lock contention reduction. The size of struct address_space on x86_64 architecture is 408B, so with the patch, 6528B more memory will be used for every 1GB swap space on x86_64 architecture. One address space is still shared for the swap entries in the same 64M trunks. To avoid lock contention for the first round of swap space allocation, the order of the swap clusters in the initial free clusters list is changed. The swap space distance between the consecutive swap clusters in the free cluster list is at least 64M. After the first round of allocation, the swap clusters are expected to be freed randomly, so the lock contention should be reduced effectively. Link: http://lkml.kernel.org/r/735bab895e64c930581ffb0a05b661e01da82bc5.1484082593.git.tim.c.chen@linux.intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Signed-off-by: Tim Chen <tim.c.chen@linux.intel.com> Cc: Aaron Lu <aaron.lu@intel.com> Cc: Andi Kleen <ak@linux.intel.com> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Christian Borntraeger <borntraeger@de.ibm.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Hillf Danton <hillf.zj@alibaba-inc.com> Cc: Huang Ying <ying.huang@intel.com> Cc: Hugh Dickins <hughd@google.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Corbet <corbet@lwn.net> escreveu: Cc: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Vladimir Davydov <vdavydov.dev@gmail.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-02-23 07:45:26 +08:00
unsigned int i, j, nr;
unsigned long ret = 0;
mm/swap: split swap cache into 64MB trunks The patch is to improve the scalability of the swap out/in via using fine grained locks for the swap cache. In current kernel, one address space will be used for each swap device. And in the common configuration, the number of the swap device is very small (one is typical). This causes the heavy lock contention on the radix tree of the address space if multiple tasks swap out/in concurrently. But in fact, there is no dependency between pages in the swap cache. So that, we can split the one shared address space for each swap device into several address spaces to reduce the lock contention. In the patch, the shared address space is split into 64MB trunks. 64MB is chosen to balance the memory space usage and effect of lock contention reduction. The size of struct address_space on x86_64 architecture is 408B, so with the patch, 6528B more memory will be used for every 1GB swap space on x86_64 architecture. One address space is still shared for the swap entries in the same 64M trunks. To avoid lock contention for the first round of swap space allocation, the order of the swap clusters in the initial free clusters list is changed. The swap space distance between the consecutive swap clusters in the free cluster list is at least 64M. After the first round of allocation, the swap clusters are expected to be freed randomly, so the lock contention should be reduced effectively. Link: http://lkml.kernel.org/r/735bab895e64c930581ffb0a05b661e01da82bc5.1484082593.git.tim.c.chen@linux.intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Signed-off-by: Tim Chen <tim.c.chen@linux.intel.com> Cc: Aaron Lu <aaron.lu@intel.com> Cc: Andi Kleen <ak@linux.intel.com> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Christian Borntraeger <borntraeger@de.ibm.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Hillf Danton <hillf.zj@alibaba-inc.com> Cc: Huang Ying <ying.huang@intel.com> Cc: Hugh Dickins <hughd@google.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Corbet <corbet@lwn.net> escreveu: Cc: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Vladimir Davydov <vdavydov.dev@gmail.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-02-23 07:45:26 +08:00
struct address_space *spaces;
mm/swap: split swap cache into 64MB trunks The patch is to improve the scalability of the swap out/in via using fine grained locks for the swap cache. In current kernel, one address space will be used for each swap device. And in the common configuration, the number of the swap device is very small (one is typical). This causes the heavy lock contention on the radix tree of the address space if multiple tasks swap out/in concurrently. But in fact, there is no dependency between pages in the swap cache. So that, we can split the one shared address space for each swap device into several address spaces to reduce the lock contention. In the patch, the shared address space is split into 64MB trunks. 64MB is chosen to balance the memory space usage and effect of lock contention reduction. The size of struct address_space on x86_64 architecture is 408B, so with the patch, 6528B more memory will be used for every 1GB swap space on x86_64 architecture. One address space is still shared for the swap entries in the same 64M trunks. To avoid lock contention for the first round of swap space allocation, the order of the swap clusters in the initial free clusters list is changed. The swap space distance between the consecutive swap clusters in the free cluster list is at least 64M. After the first round of allocation, the swap clusters are expected to be freed randomly, so the lock contention should be reduced effectively. Link: http://lkml.kernel.org/r/735bab895e64c930581ffb0a05b661e01da82bc5.1484082593.git.tim.c.chen@linux.intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Signed-off-by: Tim Chen <tim.c.chen@linux.intel.com> Cc: Aaron Lu <aaron.lu@intel.com> Cc: Andi Kleen <ak@linux.intel.com> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Christian Borntraeger <borntraeger@de.ibm.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Hillf Danton <hillf.zj@alibaba-inc.com> Cc: Huang Ying <ying.huang@intel.com> Cc: Hugh Dickins <hughd@google.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Corbet <corbet@lwn.net> escreveu: Cc: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Vladimir Davydov <vdavydov.dev@gmail.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-02-23 07:45:26 +08:00
rcu_read_lock();
for (i = 0; i < MAX_SWAPFILES; i++) {
/*
* The corresponding entries in nr_swapper_spaces and
* swapper_spaces will be reused only after at least
* one grace period. So it is impossible for them
* belongs to different usage.
*/
nr = nr_swapper_spaces[i];
spaces = rcu_dereference(swapper_spaces[i]);
if (!nr || !spaces)
continue;
for (j = 0; j < nr; j++)
ret += spaces[j].nrpages;
}
rcu_read_unlock();
return ret;
}
swap: add a simple detector for inappropriate swapin readahead This is a patch to improve swap readahead algorithm. It's from Hugh and I slightly changed it. Hugh's original changelog: swapin readahead does a blind readahead, whether or not the swapin is sequential. This may be ok on harddisk, because large reads have relatively small costs, and if the readahead pages are unneeded they can be reclaimed easily - though, what if their allocation forced reclaim of useful pages? But on SSD devices large reads are more expensive than small ones: if the readahead pages are unneeded, reading them in caused significant overhead. This patch adds very simplistic random read detection. Stealing the PageReadahead technique from Konstantin Khlebnikov's patch, avoiding the vma/anon_vma sophistications of Shaohua Li's patch, swapin_nr_pages() simply looks at readahead's current success rate, and narrows or widens its readahead window accordingly. There is little science to its heuristic: it's about as stupid as can be whilst remaining effective. The table below shows elapsed times (in centiseconds) when running a single repetitive swapping load across a 1000MB mapping in 900MB ram with 1GB swap (the harddisk tests had taken painfully too long when I used mem=500M, but SSD shows similar results for that). Vanilla is the 3.6-rc7 kernel on which I started; Shaohua denotes his Sep 3 patch in mmotm and linux-next; HughOld denotes my Oct 1 patch which Shaohua showed to be defective; HughNew this Nov 14 patch, with page_cluster as usual at default of 3 (8-page reads); HughPC4 this same patch with page_cluster 4 (16-page reads); HughPC0 with page_cluster 0 (1-page reads: no readahead). HDD for swapping to harddisk, SSD for swapping to VertexII SSD. Seq for sequential access to the mapping, cycling five times around; Rand for the same number of random touches. Anon for a MAP_PRIVATE anon mapping; Shmem for a MAP_SHARED anon mapping, equivalent to tmpfs. One weakness of Shaohua's vma/anon_vma approach was that it did not optimize Shmem: seen below. Konstantin's approach was perhaps mistuned, 50% slower on Seq: did not compete and is not shown below. HDD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0 Seq Anon 73921 76210 75611 76904 78191 121542 Seq Shmem 73601 73176 73855 72947 74543 118322 Rand Anon 895392 831243 871569 845197 846496 841680 Rand Shmem 1058375 1053486 827935 764955 764376 756489 SSD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0 Seq Anon 24634 24198 24673 25107 21614 70018 Seq Shmem 24959 24932 25052 25703 22030 69678 Rand Anon 43014 26146 28075 25989 26935 25901 Rand Shmem 45349 45215 28249 24268 24138 24332 These tests are, of course, two extremes of a very simple case: under heavier mixed loads I've not yet observed any consistent improvement or degradation, and wider testing would be welcome. Shaohua Li: Test shows Vanilla is slightly better in sequential workload than Hugh's patch. I observed with Hugh's patch sometimes the readahead size is shrinked too fast (from 8 to 1 immediately) in sequential workload if there is no hit. And in such case, continuing doing readahead is good actually. I don't prepare a sophisticated algorithm for the sequential workload because so far we can't guarantee sequential accessed pages are swap out sequentially. So I slightly change Hugh's heuristic - don't shrink readahead size too fast. Here is my test result (unit second, 3 runs average): Vanilla Hugh New Seq 356 370 360 Random 4525 2447 2444 Attached graph is the swapin/swapout throughput I collected with 'vmstat 2'. The first part is running a random workload (till around 1200 of the x-axis) and the second part is running a sequential workload. swapin and swapout throughput are almost identical in steady state in both workloads. These are expected behavior. while in Vanilla, swapin is much bigger than swapout especially in random workload (because wrong readahead). Original patches by: Shaohua Li and Konstantin Khlebnikov. [fengguang.wu@intel.com: swapin_nr_pages() can be static] Signed-off-by: Hugh Dickins <hughd@google.com> Signed-off-by: Shaohua Li <shli@fusionio.com> Signed-off-by: Fengguang Wu <fengguang.wu@intel.com> Cc: Rik van Riel <riel@redhat.com> Cc: Wu Fengguang <fengguang.wu@intel.com> Cc: Minchan Kim <minchan@kernel.org> Cc: Konstantin Khlebnikov <khlebnikov@openvz.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2014-02-07 04:04:21 +08:00
static atomic_t swapin_readahead_hits = ATOMIC_INIT(4);
void show_swap_cache_info(void)
{
printk("%lu pages in swap cache\n", total_swapcache_pages());
mm: print swapcache page count in show_swap_cache_info() Every arch implements its own show_mem() function. Most of them share quite some code, some of them are completely identical. This series implements a generic version of this function and migrates almost all architectures to it. This patch: Most show_mem() implementations calculate the amount of pages within the swapcache every time. Move the output to a more appropriate place and use the anyway available total_swapcache_pages variable. Signed-off-by: Johannes Weiner <hannes@saeurebad.de> Cc: Richard Henderson <rth@twiddle.net> Cc: Ivan Kokshaysky <ink@jurassic.park.msu.ru> Cc: Haavard Skinnemoen <hskinnemoen@atmel.com> Cc: Bryan Wu <cooloney@kernel.org> Cc: Chris Zankel <chris@zankel.net> Cc: Ingo Molnar <mingo@elte.hu> Cc: Jeff Dike <jdike@addtoit.com> Cc: David S. Miller <davem@davemloft.net> Cc: Paul Mundt <lethal@linux-sh.org> Cc: Heiko Carstens <heiko.carstens@de.ibm.com> Cc: Martin Schwidefsky <schwidefsky@de.ibm.com> Cc: David Howells <dhowells@redhat.com> Cc: Benjamin Herrenschmidt <benh@kernel.crashing.org> Cc: Paul Mackerras <paulus@samba.org> Cc: Yoshinori Sato <ysato@users.sourceforge.jp> Cc: Ralf Baechle <ralf@linux-mips.org> Cc: Greg Ungerer <gerg@uclinux.org> Cc: Geert Uytterhoeven <geert@linux-m68k.org> Cc: Roman Zippel <zippel@linux-m68k.org> Cc: Hirokazu Takata <takata@linux-m32r.org> Cc: Mikael Starvik <starvik@axis.com> Cc: Hugh Dickins <hugh@veritas.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2008-07-26 10:46:01 +08:00
printk("Swap cache stats: add %lu, delete %lu, find %lu/%lu\n",
swap_cache_info.add_total, swap_cache_info.del_total,
swap_cache_info.find_success, swap_cache_info.find_total);
swap: add per-partition lock for swapfile swap_lock is heavily contended when I test swap to 3 fast SSD (even slightly slower than swap to 2 such SSD). The main contention comes from swap_info_get(). This patch tries to fix the gap with adding a new per-partition lock. Global data like nr_swapfiles, total_swap_pages, least_priority and swap_list are still protected by swap_lock. nr_swap_pages is an atomic now, it can be changed without swap_lock. In theory, it's possible get_swap_page() finds no swap pages but actually there are free swap pages. But sounds not a big problem. Accessing partition specific data (like scan_swap_map and so on) is only protected by swap_info_struct.lock. Changing swap_info_struct.flags need hold swap_lock and swap_info_struct.lock, because scan_scan_map() will check it. read the flags is ok with either the locks hold. If both swap_lock and swap_info_struct.lock must be hold, we always hold the former first to avoid deadlock. swap_entry_free() can change swap_list. To delete that code, we add a new highest_priority_index. Whenever get_swap_page() is called, we check it. If it's valid, we use it. It's a pity get_swap_page() still holds swap_lock(). But in practice, swap_lock() isn't heavily contended in my test with this patch (or I can say there are other much more heavier bottlenecks like TLB flush). And BTW, looks get_swap_page() doesn't really need the lock. We never free swap_info[] and we check SWAP_WRITEOK flag. The only risk without the lock is we could swapout to some low priority swap, but we can quickly recover after several rounds of swap, so sounds not a big deal to me. But I'd prefer to fix this if it's a real problem. "swap: make each swap partition have one address_space" improved the swapout speed from 1.7G/s to 2G/s. This patch further improves the speed to 2.3G/s, so around 15% improvement. It's a multi-process test, so TLB flush isn't the biggest bottleneck before the patches. [arnd@arndb.de: fix it for nommu] [hughd@google.com: add missing unlock] [minchan@kernel.org: get rid of lockdep whinge on sys_swapon] Signed-off-by: Shaohua Li <shli@fusionio.com> Cc: Hugh Dickins <hughd@google.com> Cc: Rik van Riel <riel@redhat.com> Cc: Minchan Kim <minchan.kim@gmail.com> Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Cc: Seth Jennings <sjenning@linux.vnet.ibm.com> Cc: Konrad Rzeszutek Wilk <konrad.wilk@oracle.com> Cc: Xiao Guangrong <xiaoguangrong@linux.vnet.ibm.com> Cc: Dan Magenheimer <dan.magenheimer@oracle.com> Cc: Stephen Rothwell <sfr@canb.auug.org.au> Signed-off-by: Arnd Bergmann <arnd@arndb.de> Signed-off-by: Hugh Dickins <hughd@google.com> Signed-off-by: Minchan Kim <minchan@kernel.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2013-02-23 08:34:38 +08:00
printk("Free swap = %ldkB\n",
get_nr_swap_pages() << (PAGE_SHIFT - 10));
printk("Total swap = %lukB\n", total_swap_pages << (PAGE_SHIFT - 10));
}
/*
* add_to_swap_cache resembles add_to_page_cache_locked on swapper_space,
* but sets SwapCache flag and private instead of mapping and index.
*/
int add_to_swap_cache(struct page *page, swp_entry_t entry, gfp_t gfp)
{
struct address_space *address_space = swap_address_space(entry);
mm, THP, swap: delay splitting THP during swap out Patch series "THP swap: Delay splitting THP during swapping out", v11. This patchset is to optimize the performance of Transparent Huge Page (THP) swap. Recently, the performance of the storage devices improved so fast that we cannot saturate the disk bandwidth with single logical CPU when do page swap out even on a high-end server machine. Because the performance of the storage device improved faster than that of single logical CPU. And it seems that the trend will not change in the near future. On the other hand, the THP becomes more and more popular because of increased memory size. So it becomes necessary to optimize THP swap performance. The advantages of the THP swap support include: - Batch the swap operations for the THP to reduce lock acquiring/releasing, including allocating/freeing the swap space, adding/deleting to/from the swap cache, and writing/reading the swap space, etc. This will help improve the performance of the THP swap. - The THP swap space read/write will be 2M sequential IO. It is particularly helpful for the swap read, which are usually 4k random IO. This will improve the performance of the THP swap too. - It will help the memory fragmentation, especially when the THP is heavily used by the applications. The 2M continuous pages will be free up after THP swapping out. - It will improve the THP utilization on the system with the swap turned on. Because the speed for khugepaged to collapse the normal pages into the THP is quite slow. After the THP is split during the swapping out, it will take quite long time for the normal pages to collapse back into the THP after being swapped in. The high THP utilization helps the efficiency of the page based memory management too. There are some concerns regarding THP swap in, mainly because possible enlarged read/write IO size (for swap in/out) may put more overhead on the storage device. To deal with that, the THP swap in should be turned on only when necessary. For example, it can be selected via "always/never/madvise" logic, to be turned on globally, turned off globally, or turned on only for VMA with MADV_HUGEPAGE, etc. This patchset is the first step for the THP swap support. The plan is to delay splitting THP step by step, finally avoid splitting THP during the THP swapping out and swap out/in the THP as a whole. As the first step, in this patchset, the splitting huge page is delayed from almost the first step of swapping out to after allocating the swap space for the THP and adding the THP into the swap cache. This will reduce lock acquiring/releasing for the locks used for the swap cache management. With the patchset, the swap out throughput improves 15.5% (from about 3.73GB/s to about 4.31GB/s) in the vm-scalability swap-w-seq test case with 8 processes. The test is done on a Xeon E5 v3 system. The swap device used is a RAM simulated PMEM (persistent memory) device. To test the sequential swapping out, the test case creates 8 processes, which sequentially allocate and write to the anonymous pages until the RAM and part of the swap device is used up. This patch (of 5): In this patch, splitting huge page is delayed from almost the first step of swapping out to after allocating the swap space for the THP (Transparent Huge Page) and adding the THP into the swap cache. This will batch the corresponding operation, thus improve THP swap out throughput. This is the first step for the THP swap optimization. The plan is to delay splitting the THP step by step and avoid splitting the THP finally. In this patch, one swap cluster is used to hold the contents of each THP swapped out. So, the size of the swap cluster is changed to that of the THP (Transparent Huge Page) on x86_64 architecture (512). For other architectures which want such THP swap optimization, ARCH_USES_THP_SWAP_CLUSTER needs to be selected in the Kconfig file for the architecture. In effect, this will enlarge swap cluster size by 2 times on x86_64. Which may make it harder to find a free cluster when the swap space becomes fragmented. So that, this may reduce the continuous swap space allocation and sequential write in theory. The performance test in 0day shows no regressions caused by this. In the future of THP swap optimization, some information of the swapped out THP (such as compound map count) will be recorded in the swap_cluster_info data structure. The mem cgroup swap accounting functions are enhanced to support charge or uncharge a swap cluster backing a THP as a whole. The swap cluster allocate/free functions are added to allocate/free a swap cluster for a THP. A fair simple algorithm is used for swap cluster allocation, that is, only the first swap device in priority list will be tried to allocate the swap cluster. The function will fail if the trying is not successful, and the caller will fallback to allocate a single swap slot instead. This works good enough for normal cases. If the difference of the number of the free swap clusters among multiple swap devices is significant, it is possible that some THPs are split earlier than necessary. For example, this could be caused by big size difference among multiple swap devices. The swap cache functions is enhanced to support add/delete THP to/from the swap cache as a set of (HPAGE_PMD_NR) sub-pages. This may be enhanced in the future with multi-order radix tree. But because we will split the THP soon during swapping out, that optimization doesn't make much sense for this first step. The THP splitting functions are enhanced to support to split THP in swap cache during swapping out. The page lock will be held during allocating the swap cluster, adding the THP into the swap cache and splitting the THP. So in the code path other than swapping out, if the THP need to be split, the PageSwapCache(THP) will be always false. The swap cluster is only available for SSD, so the THP swap optimization in this patchset has no effect for HDD. [ying.huang@intel.com: fix two issues in THP optimize patch] Link: http://lkml.kernel.org/r/87k25ed8zo.fsf@yhuang-dev.intel.com [hannes@cmpxchg.org: extensive cleanups and simplifications, reduce code size] Link: http://lkml.kernel.org/r/20170515112522.32457-2-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Signed-off-by: Johannes Weiner <hannes@cmpxchg.org> Suggested-by: Andrew Morton <akpm@linux-foundation.org> [for config option] Acked-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> [for changes in huge_memory.c and huge_mm.h] Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Ebru Akagunduz <ebru.akagunduz@gmail.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tejun Heo <tj@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Shaohua Li <shli@kernel.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-07 06:37:18 +08:00
pgoff_t idx = swp_offset(entry);
XA_STATE_ORDER(xas, &address_space->i_pages, idx, compound_order(page));
unsigned long i, nr = 1UL << compound_order(page);
VM_BUG_ON_PAGE(!PageLocked(page), page);
VM_BUG_ON_PAGE(PageSwapCache(page), page);
VM_BUG_ON_PAGE(!PageSwapBacked(page), page);
mm, THP, swap: delay splitting THP during swap out Patch series "THP swap: Delay splitting THP during swapping out", v11. This patchset is to optimize the performance of Transparent Huge Page (THP) swap. Recently, the performance of the storage devices improved so fast that we cannot saturate the disk bandwidth with single logical CPU when do page swap out even on a high-end server machine. Because the performance of the storage device improved faster than that of single logical CPU. And it seems that the trend will not change in the near future. On the other hand, the THP becomes more and more popular because of increased memory size. So it becomes necessary to optimize THP swap performance. The advantages of the THP swap support include: - Batch the swap operations for the THP to reduce lock acquiring/releasing, including allocating/freeing the swap space, adding/deleting to/from the swap cache, and writing/reading the swap space, etc. This will help improve the performance of the THP swap. - The THP swap space read/write will be 2M sequential IO. It is particularly helpful for the swap read, which are usually 4k random IO. This will improve the performance of the THP swap too. - It will help the memory fragmentation, especially when the THP is heavily used by the applications. The 2M continuous pages will be free up after THP swapping out. - It will improve the THP utilization on the system with the swap turned on. Because the speed for khugepaged to collapse the normal pages into the THP is quite slow. After the THP is split during the swapping out, it will take quite long time for the normal pages to collapse back into the THP after being swapped in. The high THP utilization helps the efficiency of the page based memory management too. There are some concerns regarding THP swap in, mainly because possible enlarged read/write IO size (for swap in/out) may put more overhead on the storage device. To deal with that, the THP swap in should be turned on only when necessary. For example, it can be selected via "always/never/madvise" logic, to be turned on globally, turned off globally, or turned on only for VMA with MADV_HUGEPAGE, etc. This patchset is the first step for the THP swap support. The plan is to delay splitting THP step by step, finally avoid splitting THP during the THP swapping out and swap out/in the THP as a whole. As the first step, in this patchset, the splitting huge page is delayed from almost the first step of swapping out to after allocating the swap space for the THP and adding the THP into the swap cache. This will reduce lock acquiring/releasing for the locks used for the swap cache management. With the patchset, the swap out throughput improves 15.5% (from about 3.73GB/s to about 4.31GB/s) in the vm-scalability swap-w-seq test case with 8 processes. The test is done on a Xeon E5 v3 system. The swap device used is a RAM simulated PMEM (persistent memory) device. To test the sequential swapping out, the test case creates 8 processes, which sequentially allocate and write to the anonymous pages until the RAM and part of the swap device is used up. This patch (of 5): In this patch, splitting huge page is delayed from almost the first step of swapping out to after allocating the swap space for the THP (Transparent Huge Page) and adding the THP into the swap cache. This will batch the corresponding operation, thus improve THP swap out throughput. This is the first step for the THP swap optimization. The plan is to delay splitting the THP step by step and avoid splitting the THP finally. In this patch, one swap cluster is used to hold the contents of each THP swapped out. So, the size of the swap cluster is changed to that of the THP (Transparent Huge Page) on x86_64 architecture (512). For other architectures which want such THP swap optimization, ARCH_USES_THP_SWAP_CLUSTER needs to be selected in the Kconfig file for the architecture. In effect, this will enlarge swap cluster size by 2 times on x86_64. Which may make it harder to find a free cluster when the swap space becomes fragmented. So that, this may reduce the continuous swap space allocation and sequential write in theory. The performance test in 0day shows no regressions caused by this. In the future of THP swap optimization, some information of the swapped out THP (such as compound map count) will be recorded in the swap_cluster_info data structure. The mem cgroup swap accounting functions are enhanced to support charge or uncharge a swap cluster backing a THP as a whole. The swap cluster allocate/free functions are added to allocate/free a swap cluster for a THP. A fair simple algorithm is used for swap cluster allocation, that is, only the first swap device in priority list will be tried to allocate the swap cluster. The function will fail if the trying is not successful, and the caller will fallback to allocate a single swap slot instead. This works good enough for normal cases. If the difference of the number of the free swap clusters among multiple swap devices is significant, it is possible that some THPs are split earlier than necessary. For example, this could be caused by big size difference among multiple swap devices. The swap cache functions is enhanced to support add/delete THP to/from the swap cache as a set of (HPAGE_PMD_NR) sub-pages. This may be enhanced in the future with multi-order radix tree. But because we will split the THP soon during swapping out, that optimization doesn't make much sense for this first step. The THP splitting functions are enhanced to support to split THP in swap cache during swapping out. The page lock will be held during allocating the swap cluster, adding the THP into the swap cache and splitting the THP. So in the code path other than swapping out, if the THP need to be split, the PageSwapCache(THP) will be always false. The swap cluster is only available for SSD, so the THP swap optimization in this patchset has no effect for HDD. [ying.huang@intel.com: fix two issues in THP optimize patch] Link: http://lkml.kernel.org/r/87k25ed8zo.fsf@yhuang-dev.intel.com [hannes@cmpxchg.org: extensive cleanups and simplifications, reduce code size] Link: http://lkml.kernel.org/r/20170515112522.32457-2-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Signed-off-by: Johannes Weiner <hannes@cmpxchg.org> Suggested-by: Andrew Morton <akpm@linux-foundation.org> [for config option] Acked-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> [for changes in huge_memory.c and huge_mm.h] Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Ebru Akagunduz <ebru.akagunduz@gmail.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tejun Heo <tj@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Shaohua Li <shli@kernel.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-07 06:37:18 +08:00
page_ref_add(page, nr);
SetPageSwapCache(page);
do {
xas_lock_irq(&xas);
xas_create_range(&xas);
if (xas_error(&xas))
goto unlock;
for (i = 0; i < nr; i++) {
VM_BUG_ON_PAGE(xas.xa_index != idx + i, page);
set_page_private(page + i, entry.val + i);
xas_store(&xas, page + i);
xas_next(&xas);
}
mm, THP, swap: delay splitting THP during swap out Patch series "THP swap: Delay splitting THP during swapping out", v11. This patchset is to optimize the performance of Transparent Huge Page (THP) swap. Recently, the performance of the storage devices improved so fast that we cannot saturate the disk bandwidth with single logical CPU when do page swap out even on a high-end server machine. Because the performance of the storage device improved faster than that of single logical CPU. And it seems that the trend will not change in the near future. On the other hand, the THP becomes more and more popular because of increased memory size. So it becomes necessary to optimize THP swap performance. The advantages of the THP swap support include: - Batch the swap operations for the THP to reduce lock acquiring/releasing, including allocating/freeing the swap space, adding/deleting to/from the swap cache, and writing/reading the swap space, etc. This will help improve the performance of the THP swap. - The THP swap space read/write will be 2M sequential IO. It is particularly helpful for the swap read, which are usually 4k random IO. This will improve the performance of the THP swap too. - It will help the memory fragmentation, especially when the THP is heavily used by the applications. The 2M continuous pages will be free up after THP swapping out. - It will improve the THP utilization on the system with the swap turned on. Because the speed for khugepaged to collapse the normal pages into the THP is quite slow. After the THP is split during the swapping out, it will take quite long time for the normal pages to collapse back into the THP after being swapped in. The high THP utilization helps the efficiency of the page based memory management too. There are some concerns regarding THP swap in, mainly because possible enlarged read/write IO size (for swap in/out) may put more overhead on the storage device. To deal with that, the THP swap in should be turned on only when necessary. For example, it can be selected via "always/never/madvise" logic, to be turned on globally, turned off globally, or turned on only for VMA with MADV_HUGEPAGE, etc. This patchset is the first step for the THP swap support. The plan is to delay splitting THP step by step, finally avoid splitting THP during the THP swapping out and swap out/in the THP as a whole. As the first step, in this patchset, the splitting huge page is delayed from almost the first step of swapping out to after allocating the swap space for the THP and adding the THP into the swap cache. This will reduce lock acquiring/releasing for the locks used for the swap cache management. With the patchset, the swap out throughput improves 15.5% (from about 3.73GB/s to about 4.31GB/s) in the vm-scalability swap-w-seq test case with 8 processes. The test is done on a Xeon E5 v3 system. The swap device used is a RAM simulated PMEM (persistent memory) device. To test the sequential swapping out, the test case creates 8 processes, which sequentially allocate and write to the anonymous pages until the RAM and part of the swap device is used up. This patch (of 5): In this patch, splitting huge page is delayed from almost the first step of swapping out to after allocating the swap space for the THP (Transparent Huge Page) and adding the THP into the swap cache. This will batch the corresponding operation, thus improve THP swap out throughput. This is the first step for the THP swap optimization. The plan is to delay splitting the THP step by step and avoid splitting the THP finally. In this patch, one swap cluster is used to hold the contents of each THP swapped out. So, the size of the swap cluster is changed to that of the THP (Transparent Huge Page) on x86_64 architecture (512). For other architectures which want such THP swap optimization, ARCH_USES_THP_SWAP_CLUSTER needs to be selected in the Kconfig file for the architecture. In effect, this will enlarge swap cluster size by 2 times on x86_64. Which may make it harder to find a free cluster when the swap space becomes fragmented. So that, this may reduce the continuous swap space allocation and sequential write in theory. The performance test in 0day shows no regressions caused by this. In the future of THP swap optimization, some information of the swapped out THP (such as compound map count) will be recorded in the swap_cluster_info data structure. The mem cgroup swap accounting functions are enhanced to support charge or uncharge a swap cluster backing a THP as a whole. The swap cluster allocate/free functions are added to allocate/free a swap cluster for a THP. A fair simple algorithm is used for swap cluster allocation, that is, only the first swap device in priority list will be tried to allocate the swap cluster. The function will fail if the trying is not successful, and the caller will fallback to allocate a single swap slot instead. This works good enough for normal cases. If the difference of the number of the free swap clusters among multiple swap devices is significant, it is possible that some THPs are split earlier than necessary. For example, this could be caused by big size difference among multiple swap devices. The swap cache functions is enhanced to support add/delete THP to/from the swap cache as a set of (HPAGE_PMD_NR) sub-pages. This may be enhanced in the future with multi-order radix tree. But because we will split the THP soon during swapping out, that optimization doesn't make much sense for this first step. The THP splitting functions are enhanced to support to split THP in swap cache during swapping out. The page lock will be held during allocating the swap cluster, adding the THP into the swap cache and splitting the THP. So in the code path other than swapping out, if the THP need to be split, the PageSwapCache(THP) will be always false. The swap cluster is only available for SSD, so the THP swap optimization in this patchset has no effect for HDD. [ying.huang@intel.com: fix two issues in THP optimize patch] Link: http://lkml.kernel.org/r/87k25ed8zo.fsf@yhuang-dev.intel.com [hannes@cmpxchg.org: extensive cleanups and simplifications, reduce code size] Link: http://lkml.kernel.org/r/20170515112522.32457-2-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Signed-off-by: Johannes Weiner <hannes@cmpxchg.org> Suggested-by: Andrew Morton <akpm@linux-foundation.org> [for config option] Acked-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> [for changes in huge_memory.c and huge_mm.h] Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Ebru Akagunduz <ebru.akagunduz@gmail.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tejun Heo <tj@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Shaohua Li <shli@kernel.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-07 06:37:18 +08:00
address_space->nrpages += nr;
__mod_node_page_state(page_pgdat(page), NR_FILE_PAGES, nr);
ADD_CACHE_INFO(add_total, nr);
unlock:
xas_unlock_irq(&xas);
} while (xas_nomem(&xas, gfp));
if (!xas_error(&xas))
return 0;
ClearPageSwapCache(page);
page_ref_sub(page, nr);
return xas_error(&xas);
}
/*
* This must be called only on pages that have
* been verified to be in the swap cache.
*/
void __delete_from_swap_cache(struct page *page, swp_entry_t entry)
{
struct address_space *address_space = swap_address_space(entry);
mm, THP, swap: delay splitting THP during swap out Patch series "THP swap: Delay splitting THP during swapping out", v11. This patchset is to optimize the performance of Transparent Huge Page (THP) swap. Recently, the performance of the storage devices improved so fast that we cannot saturate the disk bandwidth with single logical CPU when do page swap out even on a high-end server machine. Because the performance of the storage device improved faster than that of single logical CPU. And it seems that the trend will not change in the near future. On the other hand, the THP becomes more and more popular because of increased memory size. So it becomes necessary to optimize THP swap performance. The advantages of the THP swap support include: - Batch the swap operations for the THP to reduce lock acquiring/releasing, including allocating/freeing the swap space, adding/deleting to/from the swap cache, and writing/reading the swap space, etc. This will help improve the performance of the THP swap. - The THP swap space read/write will be 2M sequential IO. It is particularly helpful for the swap read, which are usually 4k random IO. This will improve the performance of the THP swap too. - It will help the memory fragmentation, especially when the THP is heavily used by the applications. The 2M continuous pages will be free up after THP swapping out. - It will improve the THP utilization on the system with the swap turned on. Because the speed for khugepaged to collapse the normal pages into the THP is quite slow. After the THP is split during the swapping out, it will take quite long time for the normal pages to collapse back into the THP after being swapped in. The high THP utilization helps the efficiency of the page based memory management too. There are some concerns regarding THP swap in, mainly because possible enlarged read/write IO size (for swap in/out) may put more overhead on the storage device. To deal with that, the THP swap in should be turned on only when necessary. For example, it can be selected via "always/never/madvise" logic, to be turned on globally, turned off globally, or turned on only for VMA with MADV_HUGEPAGE, etc. This patchset is the first step for the THP swap support. The plan is to delay splitting THP step by step, finally avoid splitting THP during the THP swapping out and swap out/in the THP as a whole. As the first step, in this patchset, the splitting huge page is delayed from almost the first step of swapping out to after allocating the swap space for the THP and adding the THP into the swap cache. This will reduce lock acquiring/releasing for the locks used for the swap cache management. With the patchset, the swap out throughput improves 15.5% (from about 3.73GB/s to about 4.31GB/s) in the vm-scalability swap-w-seq test case with 8 processes. The test is done on a Xeon E5 v3 system. The swap device used is a RAM simulated PMEM (persistent memory) device. To test the sequential swapping out, the test case creates 8 processes, which sequentially allocate and write to the anonymous pages until the RAM and part of the swap device is used up. This patch (of 5): In this patch, splitting huge page is delayed from almost the first step of swapping out to after allocating the swap space for the THP (Transparent Huge Page) and adding the THP into the swap cache. This will batch the corresponding operation, thus improve THP swap out throughput. This is the first step for the THP swap optimization. The plan is to delay splitting the THP step by step and avoid splitting the THP finally. In this patch, one swap cluster is used to hold the contents of each THP swapped out. So, the size of the swap cluster is changed to that of the THP (Transparent Huge Page) on x86_64 architecture (512). For other architectures which want such THP swap optimization, ARCH_USES_THP_SWAP_CLUSTER needs to be selected in the Kconfig file for the architecture. In effect, this will enlarge swap cluster size by 2 times on x86_64. Which may make it harder to find a free cluster when the swap space becomes fragmented. So that, this may reduce the continuous swap space allocation and sequential write in theory. The performance test in 0day shows no regressions caused by this. In the future of THP swap optimization, some information of the swapped out THP (such as compound map count) will be recorded in the swap_cluster_info data structure. The mem cgroup swap accounting functions are enhanced to support charge or uncharge a swap cluster backing a THP as a whole. The swap cluster allocate/free functions are added to allocate/free a swap cluster for a THP. A fair simple algorithm is used for swap cluster allocation, that is, only the first swap device in priority list will be tried to allocate the swap cluster. The function will fail if the trying is not successful, and the caller will fallback to allocate a single swap slot instead. This works good enough for normal cases. If the difference of the number of the free swap clusters among multiple swap devices is significant, it is possible that some THPs are split earlier than necessary. For example, this could be caused by big size difference among multiple swap devices. The swap cache functions is enhanced to support add/delete THP to/from the swap cache as a set of (HPAGE_PMD_NR) sub-pages. This may be enhanced in the future with multi-order radix tree. But because we will split the THP soon during swapping out, that optimization doesn't make much sense for this first step. The THP splitting functions are enhanced to support to split THP in swap cache during swapping out. The page lock will be held during allocating the swap cluster, adding the THP into the swap cache and splitting the THP. So in the code path other than swapping out, if the THP need to be split, the PageSwapCache(THP) will be always false. The swap cluster is only available for SSD, so the THP swap optimization in this patchset has no effect for HDD. [ying.huang@intel.com: fix two issues in THP optimize patch] Link: http://lkml.kernel.org/r/87k25ed8zo.fsf@yhuang-dev.intel.com [hannes@cmpxchg.org: extensive cleanups and simplifications, reduce code size] Link: http://lkml.kernel.org/r/20170515112522.32457-2-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Signed-off-by: Johannes Weiner <hannes@cmpxchg.org> Suggested-by: Andrew Morton <akpm@linux-foundation.org> [for config option] Acked-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> [for changes in huge_memory.c and huge_mm.h] Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Ebru Akagunduz <ebru.akagunduz@gmail.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tejun Heo <tj@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Shaohua Li <shli@kernel.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-07 06:37:18 +08:00
int i, nr = hpage_nr_pages(page);
pgoff_t idx = swp_offset(entry);
XA_STATE(xas, &address_space->i_pages, idx);
VM_BUG_ON_PAGE(!PageLocked(page), page);
VM_BUG_ON_PAGE(!PageSwapCache(page), page);
VM_BUG_ON_PAGE(PageWriteback(page), page);
mm, THP, swap: delay splitting THP during swap out Patch series "THP swap: Delay splitting THP during swapping out", v11. This patchset is to optimize the performance of Transparent Huge Page (THP) swap. Recently, the performance of the storage devices improved so fast that we cannot saturate the disk bandwidth with single logical CPU when do page swap out even on a high-end server machine. Because the performance of the storage device improved faster than that of single logical CPU. And it seems that the trend will not change in the near future. On the other hand, the THP becomes more and more popular because of increased memory size. So it becomes necessary to optimize THP swap performance. The advantages of the THP swap support include: - Batch the swap operations for the THP to reduce lock acquiring/releasing, including allocating/freeing the swap space, adding/deleting to/from the swap cache, and writing/reading the swap space, etc. This will help improve the performance of the THP swap. - The THP swap space read/write will be 2M sequential IO. It is particularly helpful for the swap read, which are usually 4k random IO. This will improve the performance of the THP swap too. - It will help the memory fragmentation, especially when the THP is heavily used by the applications. The 2M continuous pages will be free up after THP swapping out. - It will improve the THP utilization on the system with the swap turned on. Because the speed for khugepaged to collapse the normal pages into the THP is quite slow. After the THP is split during the swapping out, it will take quite long time for the normal pages to collapse back into the THP after being swapped in. The high THP utilization helps the efficiency of the page based memory management too. There are some concerns regarding THP swap in, mainly because possible enlarged read/write IO size (for swap in/out) may put more overhead on the storage device. To deal with that, the THP swap in should be turned on only when necessary. For example, it can be selected via "always/never/madvise" logic, to be turned on globally, turned off globally, or turned on only for VMA with MADV_HUGEPAGE, etc. This patchset is the first step for the THP swap support. The plan is to delay splitting THP step by step, finally avoid splitting THP during the THP swapping out and swap out/in the THP as a whole. As the first step, in this patchset, the splitting huge page is delayed from almost the first step of swapping out to after allocating the swap space for the THP and adding the THP into the swap cache. This will reduce lock acquiring/releasing for the locks used for the swap cache management. With the patchset, the swap out throughput improves 15.5% (from about 3.73GB/s to about 4.31GB/s) in the vm-scalability swap-w-seq test case with 8 processes. The test is done on a Xeon E5 v3 system. The swap device used is a RAM simulated PMEM (persistent memory) device. To test the sequential swapping out, the test case creates 8 processes, which sequentially allocate and write to the anonymous pages until the RAM and part of the swap device is used up. This patch (of 5): In this patch, splitting huge page is delayed from almost the first step of swapping out to after allocating the swap space for the THP (Transparent Huge Page) and adding the THP into the swap cache. This will batch the corresponding operation, thus improve THP swap out throughput. This is the first step for the THP swap optimization. The plan is to delay splitting the THP step by step and avoid splitting the THP finally. In this patch, one swap cluster is used to hold the contents of each THP swapped out. So, the size of the swap cluster is changed to that of the THP (Transparent Huge Page) on x86_64 architecture (512). For other architectures which want such THP swap optimization, ARCH_USES_THP_SWAP_CLUSTER needs to be selected in the Kconfig file for the architecture. In effect, this will enlarge swap cluster size by 2 times on x86_64. Which may make it harder to find a free cluster when the swap space becomes fragmented. So that, this may reduce the continuous swap space allocation and sequential write in theory. The performance test in 0day shows no regressions caused by this. In the future of THP swap optimization, some information of the swapped out THP (such as compound map count) will be recorded in the swap_cluster_info data structure. The mem cgroup swap accounting functions are enhanced to support charge or uncharge a swap cluster backing a THP as a whole. The swap cluster allocate/free functions are added to allocate/free a swap cluster for a THP. A fair simple algorithm is used for swap cluster allocation, that is, only the first swap device in priority list will be tried to allocate the swap cluster. The function will fail if the trying is not successful, and the caller will fallback to allocate a single swap slot instead. This works good enough for normal cases. If the difference of the number of the free swap clusters among multiple swap devices is significant, it is possible that some THPs are split earlier than necessary. For example, this could be caused by big size difference among multiple swap devices. The swap cache functions is enhanced to support add/delete THP to/from the swap cache as a set of (HPAGE_PMD_NR) sub-pages. This may be enhanced in the future with multi-order radix tree. But because we will split the THP soon during swapping out, that optimization doesn't make much sense for this first step. The THP splitting functions are enhanced to support to split THP in swap cache during swapping out. The page lock will be held during allocating the swap cluster, adding the THP into the swap cache and splitting the THP. So in the code path other than swapping out, if the THP need to be split, the PageSwapCache(THP) will be always false. The swap cluster is only available for SSD, so the THP swap optimization in this patchset has no effect for HDD. [ying.huang@intel.com: fix two issues in THP optimize patch] Link: http://lkml.kernel.org/r/87k25ed8zo.fsf@yhuang-dev.intel.com [hannes@cmpxchg.org: extensive cleanups and simplifications, reduce code size] Link: http://lkml.kernel.org/r/20170515112522.32457-2-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Signed-off-by: Johannes Weiner <hannes@cmpxchg.org> Suggested-by: Andrew Morton <akpm@linux-foundation.org> [for config option] Acked-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> [for changes in huge_memory.c and huge_mm.h] Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Ebru Akagunduz <ebru.akagunduz@gmail.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tejun Heo <tj@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Shaohua Li <shli@kernel.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-07 06:37:18 +08:00
for (i = 0; i < nr; i++) {
void *entry = xas_store(&xas, NULL);
VM_BUG_ON_PAGE(entry != page + i, entry);
mm, THP, swap: delay splitting THP during swap out Patch series "THP swap: Delay splitting THP during swapping out", v11. This patchset is to optimize the performance of Transparent Huge Page (THP) swap. Recently, the performance of the storage devices improved so fast that we cannot saturate the disk bandwidth with single logical CPU when do page swap out even on a high-end server machine. Because the performance of the storage device improved faster than that of single logical CPU. And it seems that the trend will not change in the near future. On the other hand, the THP becomes more and more popular because of increased memory size. So it becomes necessary to optimize THP swap performance. The advantages of the THP swap support include: - Batch the swap operations for the THP to reduce lock acquiring/releasing, including allocating/freeing the swap space, adding/deleting to/from the swap cache, and writing/reading the swap space, etc. This will help improve the performance of the THP swap. - The THP swap space read/write will be 2M sequential IO. It is particularly helpful for the swap read, which are usually 4k random IO. This will improve the performance of the THP swap too. - It will help the memory fragmentation, especially when the THP is heavily used by the applications. The 2M continuous pages will be free up after THP swapping out. - It will improve the THP utilization on the system with the swap turned on. Because the speed for khugepaged to collapse the normal pages into the THP is quite slow. After the THP is split during the swapping out, it will take quite long time for the normal pages to collapse back into the THP after being swapped in. The high THP utilization helps the efficiency of the page based memory management too. There are some concerns regarding THP swap in, mainly because possible enlarged read/write IO size (for swap in/out) may put more overhead on the storage device. To deal with that, the THP swap in should be turned on only when necessary. For example, it can be selected via "always/never/madvise" logic, to be turned on globally, turned off globally, or turned on only for VMA with MADV_HUGEPAGE, etc. This patchset is the first step for the THP swap support. The plan is to delay splitting THP step by step, finally avoid splitting THP during the THP swapping out and swap out/in the THP as a whole. As the first step, in this patchset, the splitting huge page is delayed from almost the first step of swapping out to after allocating the swap space for the THP and adding the THP into the swap cache. This will reduce lock acquiring/releasing for the locks used for the swap cache management. With the patchset, the swap out throughput improves 15.5% (from about 3.73GB/s to about 4.31GB/s) in the vm-scalability swap-w-seq test case with 8 processes. The test is done on a Xeon E5 v3 system. The swap device used is a RAM simulated PMEM (persistent memory) device. To test the sequential swapping out, the test case creates 8 processes, which sequentially allocate and write to the anonymous pages until the RAM and part of the swap device is used up. This patch (of 5): In this patch, splitting huge page is delayed from almost the first step of swapping out to after allocating the swap space for the THP (Transparent Huge Page) and adding the THP into the swap cache. This will batch the corresponding operation, thus improve THP swap out throughput. This is the first step for the THP swap optimization. The plan is to delay splitting the THP step by step and avoid splitting the THP finally. In this patch, one swap cluster is used to hold the contents of each THP swapped out. So, the size of the swap cluster is changed to that of the THP (Transparent Huge Page) on x86_64 architecture (512). For other architectures which want such THP swap optimization, ARCH_USES_THP_SWAP_CLUSTER needs to be selected in the Kconfig file for the architecture. In effect, this will enlarge swap cluster size by 2 times on x86_64. Which may make it harder to find a free cluster when the swap space becomes fragmented. So that, this may reduce the continuous swap space allocation and sequential write in theory. The performance test in 0day shows no regressions caused by this. In the future of THP swap optimization, some information of the swapped out THP (such as compound map count) will be recorded in the swap_cluster_info data structure. The mem cgroup swap accounting functions are enhanced to support charge or uncharge a swap cluster backing a THP as a whole. The swap cluster allocate/free functions are added to allocate/free a swap cluster for a THP. A fair simple algorithm is used for swap cluster allocation, that is, only the first swap device in priority list will be tried to allocate the swap cluster. The function will fail if the trying is not successful, and the caller will fallback to allocate a single swap slot instead. This works good enough for normal cases. If the difference of the number of the free swap clusters among multiple swap devices is significant, it is possible that some THPs are split earlier than necessary. For example, this could be caused by big size difference among multiple swap devices. The swap cache functions is enhanced to support add/delete THP to/from the swap cache as a set of (HPAGE_PMD_NR) sub-pages. This may be enhanced in the future with multi-order radix tree. But because we will split the THP soon during swapping out, that optimization doesn't make much sense for this first step. The THP splitting functions are enhanced to support to split THP in swap cache during swapping out. The page lock will be held during allocating the swap cluster, adding the THP into the swap cache and splitting the THP. So in the code path other than swapping out, if the THP need to be split, the PageSwapCache(THP) will be always false. The swap cluster is only available for SSD, so the THP swap optimization in this patchset has no effect for HDD. [ying.huang@intel.com: fix two issues in THP optimize patch] Link: http://lkml.kernel.org/r/87k25ed8zo.fsf@yhuang-dev.intel.com [hannes@cmpxchg.org: extensive cleanups and simplifications, reduce code size] Link: http://lkml.kernel.org/r/20170515112522.32457-2-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Signed-off-by: Johannes Weiner <hannes@cmpxchg.org> Suggested-by: Andrew Morton <akpm@linux-foundation.org> [for config option] Acked-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> [for changes in huge_memory.c and huge_mm.h] Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Ebru Akagunduz <ebru.akagunduz@gmail.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tejun Heo <tj@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Shaohua Li <shli@kernel.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-07 06:37:18 +08:00
set_page_private(page + i, 0);
xas_next(&xas);
mm, THP, swap: delay splitting THP during swap out Patch series "THP swap: Delay splitting THP during swapping out", v11. This patchset is to optimize the performance of Transparent Huge Page (THP) swap. Recently, the performance of the storage devices improved so fast that we cannot saturate the disk bandwidth with single logical CPU when do page swap out even on a high-end server machine. Because the performance of the storage device improved faster than that of single logical CPU. And it seems that the trend will not change in the near future. On the other hand, the THP becomes more and more popular because of increased memory size. So it becomes necessary to optimize THP swap performance. The advantages of the THP swap support include: - Batch the swap operations for the THP to reduce lock acquiring/releasing, including allocating/freeing the swap space, adding/deleting to/from the swap cache, and writing/reading the swap space, etc. This will help improve the performance of the THP swap. - The THP swap space read/write will be 2M sequential IO. It is particularly helpful for the swap read, which are usually 4k random IO. This will improve the performance of the THP swap too. - It will help the memory fragmentation, especially when the THP is heavily used by the applications. The 2M continuous pages will be free up after THP swapping out. - It will improve the THP utilization on the system with the swap turned on. Because the speed for khugepaged to collapse the normal pages into the THP is quite slow. After the THP is split during the swapping out, it will take quite long time for the normal pages to collapse back into the THP after being swapped in. The high THP utilization helps the efficiency of the page based memory management too. There are some concerns regarding THP swap in, mainly because possible enlarged read/write IO size (for swap in/out) may put more overhead on the storage device. To deal with that, the THP swap in should be turned on only when necessary. For example, it can be selected via "always/never/madvise" logic, to be turned on globally, turned off globally, or turned on only for VMA with MADV_HUGEPAGE, etc. This patchset is the first step for the THP swap support. The plan is to delay splitting THP step by step, finally avoid splitting THP during the THP swapping out and swap out/in the THP as a whole. As the first step, in this patchset, the splitting huge page is delayed from almost the first step of swapping out to after allocating the swap space for the THP and adding the THP into the swap cache. This will reduce lock acquiring/releasing for the locks used for the swap cache management. With the patchset, the swap out throughput improves 15.5% (from about 3.73GB/s to about 4.31GB/s) in the vm-scalability swap-w-seq test case with 8 processes. The test is done on a Xeon E5 v3 system. The swap device used is a RAM simulated PMEM (persistent memory) device. To test the sequential swapping out, the test case creates 8 processes, which sequentially allocate and write to the anonymous pages until the RAM and part of the swap device is used up. This patch (of 5): In this patch, splitting huge page is delayed from almost the first step of swapping out to after allocating the swap space for the THP (Transparent Huge Page) and adding the THP into the swap cache. This will batch the corresponding operation, thus improve THP swap out throughput. This is the first step for the THP swap optimization. The plan is to delay splitting the THP step by step and avoid splitting the THP finally. In this patch, one swap cluster is used to hold the contents of each THP swapped out. So, the size of the swap cluster is changed to that of the THP (Transparent Huge Page) on x86_64 architecture (512). For other architectures which want such THP swap optimization, ARCH_USES_THP_SWAP_CLUSTER needs to be selected in the Kconfig file for the architecture. In effect, this will enlarge swap cluster size by 2 times on x86_64. Which may make it harder to find a free cluster when the swap space becomes fragmented. So that, this may reduce the continuous swap space allocation and sequential write in theory. The performance test in 0day shows no regressions caused by this. In the future of THP swap optimization, some information of the swapped out THP (such as compound map count) will be recorded in the swap_cluster_info data structure. The mem cgroup swap accounting functions are enhanced to support charge or uncharge a swap cluster backing a THP as a whole. The swap cluster allocate/free functions are added to allocate/free a swap cluster for a THP. A fair simple algorithm is used for swap cluster allocation, that is, only the first swap device in priority list will be tried to allocate the swap cluster. The function will fail if the trying is not successful, and the caller will fallback to allocate a single swap slot instead. This works good enough for normal cases. If the difference of the number of the free swap clusters among multiple swap devices is significant, it is possible that some THPs are split earlier than necessary. For example, this could be caused by big size difference among multiple swap devices. The swap cache functions is enhanced to support add/delete THP to/from the swap cache as a set of (HPAGE_PMD_NR) sub-pages. This may be enhanced in the future with multi-order radix tree. But because we will split the THP soon during swapping out, that optimization doesn't make much sense for this first step. The THP splitting functions are enhanced to support to split THP in swap cache during swapping out. The page lock will be held during allocating the swap cluster, adding the THP into the swap cache and splitting the THP. So in the code path other than swapping out, if the THP need to be split, the PageSwapCache(THP) will be always false. The swap cluster is only available for SSD, so the THP swap optimization in this patchset has no effect for HDD. [ying.huang@intel.com: fix two issues in THP optimize patch] Link: http://lkml.kernel.org/r/87k25ed8zo.fsf@yhuang-dev.intel.com [hannes@cmpxchg.org: extensive cleanups and simplifications, reduce code size] Link: http://lkml.kernel.org/r/20170515112522.32457-2-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Signed-off-by: Johannes Weiner <hannes@cmpxchg.org> Suggested-by: Andrew Morton <akpm@linux-foundation.org> [for config option] Acked-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> [for changes in huge_memory.c and huge_mm.h] Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Ebru Akagunduz <ebru.akagunduz@gmail.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tejun Heo <tj@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Shaohua Li <shli@kernel.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-07 06:37:18 +08:00
}
ClearPageSwapCache(page);
mm, THP, swap: delay splitting THP during swap out Patch series "THP swap: Delay splitting THP during swapping out", v11. This patchset is to optimize the performance of Transparent Huge Page (THP) swap. Recently, the performance of the storage devices improved so fast that we cannot saturate the disk bandwidth with single logical CPU when do page swap out even on a high-end server machine. Because the performance of the storage device improved faster than that of single logical CPU. And it seems that the trend will not change in the near future. On the other hand, the THP becomes more and more popular because of increased memory size. So it becomes necessary to optimize THP swap performance. The advantages of the THP swap support include: - Batch the swap operations for the THP to reduce lock acquiring/releasing, including allocating/freeing the swap space, adding/deleting to/from the swap cache, and writing/reading the swap space, etc. This will help improve the performance of the THP swap. - The THP swap space read/write will be 2M sequential IO. It is particularly helpful for the swap read, which are usually 4k random IO. This will improve the performance of the THP swap too. - It will help the memory fragmentation, especially when the THP is heavily used by the applications. The 2M continuous pages will be free up after THP swapping out. - It will improve the THP utilization on the system with the swap turned on. Because the speed for khugepaged to collapse the normal pages into the THP is quite slow. After the THP is split during the swapping out, it will take quite long time for the normal pages to collapse back into the THP after being swapped in. The high THP utilization helps the efficiency of the page based memory management too. There are some concerns regarding THP swap in, mainly because possible enlarged read/write IO size (for swap in/out) may put more overhead on the storage device. To deal with that, the THP swap in should be turned on only when necessary. For example, it can be selected via "always/never/madvise" logic, to be turned on globally, turned off globally, or turned on only for VMA with MADV_HUGEPAGE, etc. This patchset is the first step for the THP swap support. The plan is to delay splitting THP step by step, finally avoid splitting THP during the THP swapping out and swap out/in the THP as a whole. As the first step, in this patchset, the splitting huge page is delayed from almost the first step of swapping out to after allocating the swap space for the THP and adding the THP into the swap cache. This will reduce lock acquiring/releasing for the locks used for the swap cache management. With the patchset, the swap out throughput improves 15.5% (from about 3.73GB/s to about 4.31GB/s) in the vm-scalability swap-w-seq test case with 8 processes. The test is done on a Xeon E5 v3 system. The swap device used is a RAM simulated PMEM (persistent memory) device. To test the sequential swapping out, the test case creates 8 processes, which sequentially allocate and write to the anonymous pages until the RAM and part of the swap device is used up. This patch (of 5): In this patch, splitting huge page is delayed from almost the first step of swapping out to after allocating the swap space for the THP (Transparent Huge Page) and adding the THP into the swap cache. This will batch the corresponding operation, thus improve THP swap out throughput. This is the first step for the THP swap optimization. The plan is to delay splitting the THP step by step and avoid splitting the THP finally. In this patch, one swap cluster is used to hold the contents of each THP swapped out. So, the size of the swap cluster is changed to that of the THP (Transparent Huge Page) on x86_64 architecture (512). For other architectures which want such THP swap optimization, ARCH_USES_THP_SWAP_CLUSTER needs to be selected in the Kconfig file for the architecture. In effect, this will enlarge swap cluster size by 2 times on x86_64. Which may make it harder to find a free cluster when the swap space becomes fragmented. So that, this may reduce the continuous swap space allocation and sequential write in theory. The performance test in 0day shows no regressions caused by this. In the future of THP swap optimization, some information of the swapped out THP (such as compound map count) will be recorded in the swap_cluster_info data structure. The mem cgroup swap accounting functions are enhanced to support charge or uncharge a swap cluster backing a THP as a whole. The swap cluster allocate/free functions are added to allocate/free a swap cluster for a THP. A fair simple algorithm is used for swap cluster allocation, that is, only the first swap device in priority list will be tried to allocate the swap cluster. The function will fail if the trying is not successful, and the caller will fallback to allocate a single swap slot instead. This works good enough for normal cases. If the difference of the number of the free swap clusters among multiple swap devices is significant, it is possible that some THPs are split earlier than necessary. For example, this could be caused by big size difference among multiple swap devices. The swap cache functions is enhanced to support add/delete THP to/from the swap cache as a set of (HPAGE_PMD_NR) sub-pages. This may be enhanced in the future with multi-order radix tree. But because we will split the THP soon during swapping out, that optimization doesn't make much sense for this first step. The THP splitting functions are enhanced to support to split THP in swap cache during swapping out. The page lock will be held during allocating the swap cluster, adding the THP into the swap cache and splitting the THP. So in the code path other than swapping out, if the THP need to be split, the PageSwapCache(THP) will be always false. The swap cluster is only available for SSD, so the THP swap optimization in this patchset has no effect for HDD. [ying.huang@intel.com: fix two issues in THP optimize patch] Link: http://lkml.kernel.org/r/87k25ed8zo.fsf@yhuang-dev.intel.com [hannes@cmpxchg.org: extensive cleanups and simplifications, reduce code size] Link: http://lkml.kernel.org/r/20170515112522.32457-2-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Signed-off-by: Johannes Weiner <hannes@cmpxchg.org> Suggested-by: Andrew Morton <akpm@linux-foundation.org> [for config option] Acked-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> [for changes in huge_memory.c and huge_mm.h] Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Ebru Akagunduz <ebru.akagunduz@gmail.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tejun Heo <tj@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Shaohua Li <shli@kernel.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-07 06:37:18 +08:00
address_space->nrpages -= nr;
__mod_node_page_state(page_pgdat(page), NR_FILE_PAGES, -nr);
ADD_CACHE_INFO(del_total, nr);
}
/**
* add_to_swap - allocate swap space for a page
* @page: page we want to move to swap
*
* Allocate swap space for the page and add the page to the
* swap cache. Caller needs to hold the page lock.
*/
int add_to_swap(struct page *page)
{
swp_entry_t entry;
int err;
VM_BUG_ON_PAGE(!PageLocked(page), page);
VM_BUG_ON_PAGE(!PageUptodate(page), page);
mm, THP, swap: delay splitting THP during swap out Patch series "THP swap: Delay splitting THP during swapping out", v11. This patchset is to optimize the performance of Transparent Huge Page (THP) swap. Recently, the performance of the storage devices improved so fast that we cannot saturate the disk bandwidth with single logical CPU when do page swap out even on a high-end server machine. Because the performance of the storage device improved faster than that of single logical CPU. And it seems that the trend will not change in the near future. On the other hand, the THP becomes more and more popular because of increased memory size. So it becomes necessary to optimize THP swap performance. The advantages of the THP swap support include: - Batch the swap operations for the THP to reduce lock acquiring/releasing, including allocating/freeing the swap space, adding/deleting to/from the swap cache, and writing/reading the swap space, etc. This will help improve the performance of the THP swap. - The THP swap space read/write will be 2M sequential IO. It is particularly helpful for the swap read, which are usually 4k random IO. This will improve the performance of the THP swap too. - It will help the memory fragmentation, especially when the THP is heavily used by the applications. The 2M continuous pages will be free up after THP swapping out. - It will improve the THP utilization on the system with the swap turned on. Because the speed for khugepaged to collapse the normal pages into the THP is quite slow. After the THP is split during the swapping out, it will take quite long time for the normal pages to collapse back into the THP after being swapped in. The high THP utilization helps the efficiency of the page based memory management too. There are some concerns regarding THP swap in, mainly because possible enlarged read/write IO size (for swap in/out) may put more overhead on the storage device. To deal with that, the THP swap in should be turned on only when necessary. For example, it can be selected via "always/never/madvise" logic, to be turned on globally, turned off globally, or turned on only for VMA with MADV_HUGEPAGE, etc. This patchset is the first step for the THP swap support. The plan is to delay splitting THP step by step, finally avoid splitting THP during the THP swapping out and swap out/in the THP as a whole. As the first step, in this patchset, the splitting huge page is delayed from almost the first step of swapping out to after allocating the swap space for the THP and adding the THP into the swap cache. This will reduce lock acquiring/releasing for the locks used for the swap cache management. With the patchset, the swap out throughput improves 15.5% (from about 3.73GB/s to about 4.31GB/s) in the vm-scalability swap-w-seq test case with 8 processes. The test is done on a Xeon E5 v3 system. The swap device used is a RAM simulated PMEM (persistent memory) device. To test the sequential swapping out, the test case creates 8 processes, which sequentially allocate and write to the anonymous pages until the RAM and part of the swap device is used up. This patch (of 5): In this patch, splitting huge page is delayed from almost the first step of swapping out to after allocating the swap space for the THP (Transparent Huge Page) and adding the THP into the swap cache. This will batch the corresponding operation, thus improve THP swap out throughput. This is the first step for the THP swap optimization. The plan is to delay splitting the THP step by step and avoid splitting the THP finally. In this patch, one swap cluster is used to hold the contents of each THP swapped out. So, the size of the swap cluster is changed to that of the THP (Transparent Huge Page) on x86_64 architecture (512). For other architectures which want such THP swap optimization, ARCH_USES_THP_SWAP_CLUSTER needs to be selected in the Kconfig file for the architecture. In effect, this will enlarge swap cluster size by 2 times on x86_64. Which may make it harder to find a free cluster when the swap space becomes fragmented. So that, this may reduce the continuous swap space allocation and sequential write in theory. The performance test in 0day shows no regressions caused by this. In the future of THP swap optimization, some information of the swapped out THP (such as compound map count) will be recorded in the swap_cluster_info data structure. The mem cgroup swap accounting functions are enhanced to support charge or uncharge a swap cluster backing a THP as a whole. The swap cluster allocate/free functions are added to allocate/free a swap cluster for a THP. A fair simple algorithm is used for swap cluster allocation, that is, only the first swap device in priority list will be tried to allocate the swap cluster. The function will fail if the trying is not successful, and the caller will fallback to allocate a single swap slot instead. This works good enough for normal cases. If the difference of the number of the free swap clusters among multiple swap devices is significant, it is possible that some THPs are split earlier than necessary. For example, this could be caused by big size difference among multiple swap devices. The swap cache functions is enhanced to support add/delete THP to/from the swap cache as a set of (HPAGE_PMD_NR) sub-pages. This may be enhanced in the future with multi-order radix tree. But because we will split the THP soon during swapping out, that optimization doesn't make much sense for this first step. The THP splitting functions are enhanced to support to split THP in swap cache during swapping out. The page lock will be held during allocating the swap cluster, adding the THP into the swap cache and splitting the THP. So in the code path other than swapping out, if the THP need to be split, the PageSwapCache(THP) will be always false. The swap cluster is only available for SSD, so the THP swap optimization in this patchset has no effect for HDD. [ying.huang@intel.com: fix two issues in THP optimize patch] Link: http://lkml.kernel.org/r/87k25ed8zo.fsf@yhuang-dev.intel.com [hannes@cmpxchg.org: extensive cleanups and simplifications, reduce code size] Link: http://lkml.kernel.org/r/20170515112522.32457-2-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Signed-off-by: Johannes Weiner <hannes@cmpxchg.org> Suggested-by: Andrew Morton <akpm@linux-foundation.org> [for config option] Acked-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> [for changes in huge_memory.c and huge_mm.h] Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Ebru Akagunduz <ebru.akagunduz@gmail.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tejun Heo <tj@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Shaohua Li <shli@kernel.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-07 06:37:18 +08:00
entry = get_swap_page(page);
if (!entry.val)
return 0;
/*
* XArray node allocations from PF_MEMALLOC contexts could
* completely exhaust the page allocator. __GFP_NOMEMALLOC
* stops emergency reserves from being allocated.
*
* TODO: this could cause a theoretical memory reclaim
* deadlock in the swap out path.
*/
/*
mm: support madvise(MADV_FREE) Linux doesn't have an ability to free pages lazy while other OS already have been supported that named by madvise(MADV_FREE). The gain is clear that kernel can discard freed pages rather than swapping out or OOM if memory pressure happens. Without memory pressure, freed pages would be reused by userspace without another additional overhead(ex, page fault + allocation + zeroing). Jason Evans said: : Facebook has been using MAP_UNINITIALIZED : (https://lkml.org/lkml/2012/1/18/308) in some of its applications for : several years, but there are operational costs to maintaining this : out-of-tree in our kernel and in jemalloc, and we are anxious to retire it : in favor of MADV_FREE. When we first enabled MAP_UNINITIALIZED it : increased throughput for much of our workload by ~5%, and although the : benefit has decreased using newer hardware and kernels, there is still : enough benefit that we cannot reasonably retire it without a replacement. : : Aside from Facebook operations, there are numerous broadly used : applications that would benefit from MADV_FREE. The ones that immediately : come to mind are redis, varnish, and MariaDB. I don't have much insight : into Android internals and development process, but I would hope to see : MADV_FREE support eventually end up there as well to benefit applications : linked with the integrated jemalloc. : : jemalloc will use MADV_FREE once it becomes available in the Linux kernel. : In fact, jemalloc already uses MADV_FREE or equivalent everywhere it's : available: *BSD, OS X, Windows, and Solaris -- every platform except Linux : (and AIX, but I'm not sure it even compiles on AIX). The lack of : MADV_FREE on Linux forced me down a long series of increasingly : sophisticated heuristics for madvise() volume reduction, and even so this : remains a common performance issue for people using jemalloc on Linux. : Please integrate MADV_FREE; many people will benefit substantially. How it works: When madvise syscall is called, VM clears dirty bit of ptes of the range. If memory pressure happens, VM checks dirty bit of page table and if it found still "clean", it means it's a "lazyfree pages" so VM could discard the page instead of swapping out. Once there was store operation for the page before VM peek a page to reclaim, dirty bit is set so VM can swap out the page instead of discarding. One thing we should notice is that basically, MADV_FREE relies on dirty bit in page table entry to decide whether VM allows to discard the page or not. IOW, if page table entry includes marked dirty bit, VM shouldn't discard the page. However, as a example, if swap-in by read fault happens, page table entry doesn't have dirty bit so MADV_FREE could discard the page wrongly. For avoiding the problem, MADV_FREE did more checks with PageDirty and PageSwapCache. It worked out because swapped-in page lives on swap cache and since it is evicted from the swap cache, the page has PG_dirty flag. So both page flags check effectively prevent wrong discarding by MADV_FREE. However, a problem in above logic is that swapped-in page has PG_dirty still after they are removed from swap cache so VM cannot consider the page as freeable any more even if madvise_free is called in future. Look at below example for detail. ptr = malloc(); memset(ptr); .. .. .. heavy memory pressure so all of pages are swapped out .. .. var = *ptr; -> a page swapped-in and could be removed from swapcache. Then, page table doesn't mark dirty bit and page descriptor includes PG_dirty .. .. madvise_free(ptr); -> It doesn't clear PG_dirty of the page. .. .. .. .. heavy memory pressure again. .. In this time, VM cannot discard the page because the page .. has *PG_dirty* To solve the problem, this patch clears PG_dirty if only the page is owned exclusively by current process when madvise is called because PG_dirty represents ptes's dirtiness in several processes so we could clear it only if we own it exclusively. Firstly, heavy users would be general allocators(ex, jemalloc, tcmalloc and hope glibc supports it) and jemalloc/tcmalloc already have supported the feature for other OS(ex, FreeBSD) barrios@blaptop:~/benchmark/ebizzy$ lscpu Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Byte Order: Little Endian CPU(s): 12 On-line CPU(s) list: 0-11 Thread(s) per core: 1 Core(s) per socket: 1 Socket(s): 12 NUMA node(s): 1 Vendor ID: GenuineIntel CPU family: 6 Model: 2 Stepping: 3 CPU MHz: 3200.185 BogoMIPS: 6400.53 Virtualization: VT-x Hypervisor vendor: KVM Virtualization type: full L1d cache: 32K L1i cache: 32K L2 cache: 4096K NUMA node0 CPU(s): 0-11 ebizzy benchmark(./ebizzy -S 10 -n 512) Higher avg is better. vanilla-jemalloc MADV_free-jemalloc 1 thread records: 10 records: 10 avg: 2961.90 avg: 12069.70 std: 71.96(2.43%) std: 186.68(1.55%) max: 3070.00 max: 12385.00 min: 2796.00 min: 11746.00 2 thread records: 10 records: 10 avg: 5020.00 avg: 17827.00 std: 264.87(5.28%) std: 358.52(2.01%) max: 5244.00 max: 18760.00 min: 4251.00 min: 17382.00 4 thread records: 10 records: 10 avg: 8988.80 avg: 27930.80 std: 1175.33(13.08%) std: 3317.33(11.88%) max: 9508.00 max: 30879.00 min: 5477.00 min: 21024.00 8 thread records: 10 records: 10 avg: 13036.50 avg: 33739.40 std: 170.67(1.31%) std: 5146.22(15.25%) max: 13371.00 max: 40572.00 min: 12785.00 min: 24088.00 16 thread records: 10 records: 10 avg: 11092.40 avg: 31424.20 std: 710.60(6.41%) std: 3763.89(11.98%) max: 12446.00 max: 36635.00 min: 9949.00 min: 25669.00 32 thread records: 10 records: 10 avg: 11067.00 avg: 34495.80 std: 971.06(8.77%) std: 2721.36(7.89%) max: 12010.00 max: 38598.00 min: 9002.00 min: 30636.00 In summary, MADV_FREE is about much faster than MADV_DONTNEED. This patch (of 12): Add core MADV_FREE implementation. [akpm@linux-foundation.org: small cleanups] Signed-off-by: Minchan Kim <minchan@kernel.org> Acked-by: Michal Hocko <mhocko@suse.com> Acked-by: Hugh Dickins <hughd@google.com> Cc: Mika Penttil <mika.penttila@nextfour.com> Cc: Michael Kerrisk <mtk.manpages@gmail.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: KOSAKI Motohiro <kosaki.motohiro@jp.fujitsu.com> Cc: Jason Evans <je@fb.com> Cc: Daniel Micay <danielmicay@gmail.com> Cc: "Kirill A. Shutemov" <kirill@shutemov.name> Cc: Shaohua Li <shli@kernel.org> Cc: <yalin.wang2010@gmail.com> Cc: Andy Lutomirski <luto@amacapital.net> Cc: "James E.J. Bottomley" <jejb@parisc-linux.org> Cc: "Kirill A. Shutemov" <kirill@shutemov.name> Cc: "Shaohua Li" <shli@kernel.org> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Arnd Bergmann <arnd@arndb.de> Cc: Benjamin Herrenschmidt <benh@kernel.crashing.org> Cc: Catalin Marinas <catalin.marinas@arm.com> Cc: Chen Gang <gang.chen.5i5j@gmail.com> Cc: Chris Zankel <chris@zankel.net> Cc: Darrick J. Wong <darrick.wong@oracle.com> Cc: David S. Miller <davem@davemloft.net> Cc: Helge Deller <deller@gmx.de> Cc: Ivan Kokshaysky <ink@jurassic.park.msu.ru> Cc: Matt Turner <mattst88@gmail.com> Cc: Max Filippov <jcmvbkbc@gmail.com> Cc: Ralf Baechle <ralf@linux-mips.org> Cc: Richard Henderson <rth@twiddle.net> Cc: Roland Dreier <roland@kernel.org> Cc: Russell King <rmk@arm.linux.org.uk> Cc: Shaohua Li <shli@kernel.org> Cc: Will Deacon <will.deacon@arm.com> Cc: Wu Fengguang <fengguang.wu@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2016-01-16 08:54:53 +08:00
* Add it to the swap cache.
*/
err = add_to_swap_cache(page, entry,
__GFP_HIGH|__GFP_NOMEMALLOC|__GFP_NOWARN);
mm, THP, swap: delay splitting THP during swap out Patch series "THP swap: Delay splitting THP during swapping out", v11. This patchset is to optimize the performance of Transparent Huge Page (THP) swap. Recently, the performance of the storage devices improved so fast that we cannot saturate the disk bandwidth with single logical CPU when do page swap out even on a high-end server machine. Because the performance of the storage device improved faster than that of single logical CPU. And it seems that the trend will not change in the near future. On the other hand, the THP becomes more and more popular because of increased memory size. So it becomes necessary to optimize THP swap performance. The advantages of the THP swap support include: - Batch the swap operations for the THP to reduce lock acquiring/releasing, including allocating/freeing the swap space, adding/deleting to/from the swap cache, and writing/reading the swap space, etc. This will help improve the performance of the THP swap. - The THP swap space read/write will be 2M sequential IO. It is particularly helpful for the swap read, which are usually 4k random IO. This will improve the performance of the THP swap too. - It will help the memory fragmentation, especially when the THP is heavily used by the applications. The 2M continuous pages will be free up after THP swapping out. - It will improve the THP utilization on the system with the swap turned on. Because the speed for khugepaged to collapse the normal pages into the THP is quite slow. After the THP is split during the swapping out, it will take quite long time for the normal pages to collapse back into the THP after being swapped in. The high THP utilization helps the efficiency of the page based memory management too. There are some concerns regarding THP swap in, mainly because possible enlarged read/write IO size (for swap in/out) may put more overhead on the storage device. To deal with that, the THP swap in should be turned on only when necessary. For example, it can be selected via "always/never/madvise" logic, to be turned on globally, turned off globally, or turned on only for VMA with MADV_HUGEPAGE, etc. This patchset is the first step for the THP swap support. The plan is to delay splitting THP step by step, finally avoid splitting THP during the THP swapping out and swap out/in the THP as a whole. As the first step, in this patchset, the splitting huge page is delayed from almost the first step of swapping out to after allocating the swap space for the THP and adding the THP into the swap cache. This will reduce lock acquiring/releasing for the locks used for the swap cache management. With the patchset, the swap out throughput improves 15.5% (from about 3.73GB/s to about 4.31GB/s) in the vm-scalability swap-w-seq test case with 8 processes. The test is done on a Xeon E5 v3 system. The swap device used is a RAM simulated PMEM (persistent memory) device. To test the sequential swapping out, the test case creates 8 processes, which sequentially allocate and write to the anonymous pages until the RAM and part of the swap device is used up. This patch (of 5): In this patch, splitting huge page is delayed from almost the first step of swapping out to after allocating the swap space for the THP (Transparent Huge Page) and adding the THP into the swap cache. This will batch the corresponding operation, thus improve THP swap out throughput. This is the first step for the THP swap optimization. The plan is to delay splitting the THP step by step and avoid splitting the THP finally. In this patch, one swap cluster is used to hold the contents of each THP swapped out. So, the size of the swap cluster is changed to that of the THP (Transparent Huge Page) on x86_64 architecture (512). For other architectures which want such THP swap optimization, ARCH_USES_THP_SWAP_CLUSTER needs to be selected in the Kconfig file for the architecture. In effect, this will enlarge swap cluster size by 2 times on x86_64. Which may make it harder to find a free cluster when the swap space becomes fragmented. So that, this may reduce the continuous swap space allocation and sequential write in theory. The performance test in 0day shows no regressions caused by this. In the future of THP swap optimization, some information of the swapped out THP (such as compound map count) will be recorded in the swap_cluster_info data structure. The mem cgroup swap accounting functions are enhanced to support charge or uncharge a swap cluster backing a THP as a whole. The swap cluster allocate/free functions are added to allocate/free a swap cluster for a THP. A fair simple algorithm is used for swap cluster allocation, that is, only the first swap device in priority list will be tried to allocate the swap cluster. The function will fail if the trying is not successful, and the caller will fallback to allocate a single swap slot instead. This works good enough for normal cases. If the difference of the number of the free swap clusters among multiple swap devices is significant, it is possible that some THPs are split earlier than necessary. For example, this could be caused by big size difference among multiple swap devices. The swap cache functions is enhanced to support add/delete THP to/from the swap cache as a set of (HPAGE_PMD_NR) sub-pages. This may be enhanced in the future with multi-order radix tree. But because we will split the THP soon during swapping out, that optimization doesn't make much sense for this first step. The THP splitting functions are enhanced to support to split THP in swap cache during swapping out. The page lock will be held during allocating the swap cluster, adding the THP into the swap cache and splitting the THP. So in the code path other than swapping out, if the THP need to be split, the PageSwapCache(THP) will be always false. The swap cluster is only available for SSD, so the THP swap optimization in this patchset has no effect for HDD. [ying.huang@intel.com: fix two issues in THP optimize patch] Link: http://lkml.kernel.org/r/87k25ed8zo.fsf@yhuang-dev.intel.com [hannes@cmpxchg.org: extensive cleanups and simplifications, reduce code size] Link: http://lkml.kernel.org/r/20170515112522.32457-2-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Signed-off-by: Johannes Weiner <hannes@cmpxchg.org> Suggested-by: Andrew Morton <akpm@linux-foundation.org> [for config option] Acked-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> [for changes in huge_memory.c and huge_mm.h] Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Ebru Akagunduz <ebru.akagunduz@gmail.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tejun Heo <tj@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Shaohua Li <shli@kernel.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-07 06:37:18 +08:00
if (err)
/*
* add_to_swap_cache() doesn't return -EEXIST, so we can safely
* clear SWAP_HAS_CACHE flag.
*/
goto fail;
mm: fix data corruption caused by lazyfree page MADV_FREE clears pte dirty bit and then marks the page lazyfree (clear SwapBacked). There is no lock to prevent the page is added to swap cache between these two steps by page reclaim. If page reclaim finds such page, it will simply add the page to swap cache without pageout the page to swap because the page is marked as clean. Next time, page fault will read data from the swap slot which doesn't have the original data, so we have a data corruption. To fix issue, we mark the page dirty and pageout the page. However, we shouldn't dirty all pages which is clean and in swap cache. swapin page is swap cache and clean too. So we only dirty page which is added into swap cache in page reclaim, which shouldn't be swapin page. As Minchan suggested, simply dirty the page in add_to_swap can do the job. Fixes: 802a3a92ad7a ("mm: reclaim MADV_FREE pages") Link: http://lkml.kernel.org/r/08c84256b007bf3f63c91d94383bd9eb6fee2daa.1506446061.git.shli@fb.com Signed-off-by: Shaohua Li <shli@fb.com> Reported-by: Artem Savkov <asavkov@redhat.com> Acked-by: Michal Hocko <mhocko@suse.com> Acked-by: Minchan Kim <minchan@kernel.org> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Hillf Danton <hdanton@sina.com> Cc: Hugh Dickins <hughd@google.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@techsingularity.net> Cc: <stable@vger.kernel.org> [4.12+] Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-10-04 07:15:32 +08:00
/*
* Normally the page will be dirtied in unmap because its pte should be
* dirty. A special case is MADV_FREE page. The page'e pte could have
* dirty bit cleared but the page's SwapBacked bit is still set because
* clearing the dirty bit and SwapBacked bit has no lock protected. For
* such page, unmap will not set dirty bit for it, so page reclaim will
* not write the page out. This can cause data corruption when the page
* is swap in later. Always setting the dirty bit for the page solves
* the problem.
*/
set_page_dirty(page);
mm, THP, swap: delay splitting THP during swap out Patch series "THP swap: Delay splitting THP during swapping out", v11. This patchset is to optimize the performance of Transparent Huge Page (THP) swap. Recently, the performance of the storage devices improved so fast that we cannot saturate the disk bandwidth with single logical CPU when do page swap out even on a high-end server machine. Because the performance of the storage device improved faster than that of single logical CPU. And it seems that the trend will not change in the near future. On the other hand, the THP becomes more and more popular because of increased memory size. So it becomes necessary to optimize THP swap performance. The advantages of the THP swap support include: - Batch the swap operations for the THP to reduce lock acquiring/releasing, including allocating/freeing the swap space, adding/deleting to/from the swap cache, and writing/reading the swap space, etc. This will help improve the performance of the THP swap. - The THP swap space read/write will be 2M sequential IO. It is particularly helpful for the swap read, which are usually 4k random IO. This will improve the performance of the THP swap too. - It will help the memory fragmentation, especially when the THP is heavily used by the applications. The 2M continuous pages will be free up after THP swapping out. - It will improve the THP utilization on the system with the swap turned on. Because the speed for khugepaged to collapse the normal pages into the THP is quite slow. After the THP is split during the swapping out, it will take quite long time for the normal pages to collapse back into the THP after being swapped in. The high THP utilization helps the efficiency of the page based memory management too. There are some concerns regarding THP swap in, mainly because possible enlarged read/write IO size (for swap in/out) may put more overhead on the storage device. To deal with that, the THP swap in should be turned on only when necessary. For example, it can be selected via "always/never/madvise" logic, to be turned on globally, turned off globally, or turned on only for VMA with MADV_HUGEPAGE, etc. This patchset is the first step for the THP swap support. The plan is to delay splitting THP step by step, finally avoid splitting THP during the THP swapping out and swap out/in the THP as a whole. As the first step, in this patchset, the splitting huge page is delayed from almost the first step of swapping out to after allocating the swap space for the THP and adding the THP into the swap cache. This will reduce lock acquiring/releasing for the locks used for the swap cache management. With the patchset, the swap out throughput improves 15.5% (from about 3.73GB/s to about 4.31GB/s) in the vm-scalability swap-w-seq test case with 8 processes. The test is done on a Xeon E5 v3 system. The swap device used is a RAM simulated PMEM (persistent memory) device. To test the sequential swapping out, the test case creates 8 processes, which sequentially allocate and write to the anonymous pages until the RAM and part of the swap device is used up. This patch (of 5): In this patch, splitting huge page is delayed from almost the first step of swapping out to after allocating the swap space for the THP (Transparent Huge Page) and adding the THP into the swap cache. This will batch the corresponding operation, thus improve THP swap out throughput. This is the first step for the THP swap optimization. The plan is to delay splitting the THP step by step and avoid splitting the THP finally. In this patch, one swap cluster is used to hold the contents of each THP swapped out. So, the size of the swap cluster is changed to that of the THP (Transparent Huge Page) on x86_64 architecture (512). For other architectures which want such THP swap optimization, ARCH_USES_THP_SWAP_CLUSTER needs to be selected in the Kconfig file for the architecture. In effect, this will enlarge swap cluster size by 2 times on x86_64. Which may make it harder to find a free cluster when the swap space becomes fragmented. So that, this may reduce the continuous swap space allocation and sequential write in theory. The performance test in 0day shows no regressions caused by this. In the future of THP swap optimization, some information of the swapped out THP (such as compound map count) will be recorded in the swap_cluster_info data structure. The mem cgroup swap accounting functions are enhanced to support charge or uncharge a swap cluster backing a THP as a whole. The swap cluster allocate/free functions are added to allocate/free a swap cluster for a THP. A fair simple algorithm is used for swap cluster allocation, that is, only the first swap device in priority list will be tried to allocate the swap cluster. The function will fail if the trying is not successful, and the caller will fallback to allocate a single swap slot instead. This works good enough for normal cases. If the difference of the number of the free swap clusters among multiple swap devices is significant, it is possible that some THPs are split earlier than necessary. For example, this could be caused by big size difference among multiple swap devices. The swap cache functions is enhanced to support add/delete THP to/from the swap cache as a set of (HPAGE_PMD_NR) sub-pages. This may be enhanced in the future with multi-order radix tree. But because we will split the THP soon during swapping out, that optimization doesn't make much sense for this first step. The THP splitting functions are enhanced to support to split THP in swap cache during swapping out. The page lock will be held during allocating the swap cluster, adding the THP into the swap cache and splitting the THP. So in the code path other than swapping out, if the THP need to be split, the PageSwapCache(THP) will be always false. The swap cluster is only available for SSD, so the THP swap optimization in this patchset has no effect for HDD. [ying.huang@intel.com: fix two issues in THP optimize patch] Link: http://lkml.kernel.org/r/87k25ed8zo.fsf@yhuang-dev.intel.com [hannes@cmpxchg.org: extensive cleanups and simplifications, reduce code size] Link: http://lkml.kernel.org/r/20170515112522.32457-2-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Signed-off-by: Johannes Weiner <hannes@cmpxchg.org> Suggested-by: Andrew Morton <akpm@linux-foundation.org> [for config option] Acked-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> [for changes in huge_memory.c and huge_mm.h] Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Ebru Akagunduz <ebru.akagunduz@gmail.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tejun Heo <tj@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Shaohua Li <shli@kernel.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-07 06:37:18 +08:00
return 1;
fail:
put_swap_page(page, entry);
mm, THP, swap: delay splitting THP during swap out Patch series "THP swap: Delay splitting THP during swapping out", v11. This patchset is to optimize the performance of Transparent Huge Page (THP) swap. Recently, the performance of the storage devices improved so fast that we cannot saturate the disk bandwidth with single logical CPU when do page swap out even on a high-end server machine. Because the performance of the storage device improved faster than that of single logical CPU. And it seems that the trend will not change in the near future. On the other hand, the THP becomes more and more popular because of increased memory size. So it becomes necessary to optimize THP swap performance. The advantages of the THP swap support include: - Batch the swap operations for the THP to reduce lock acquiring/releasing, including allocating/freeing the swap space, adding/deleting to/from the swap cache, and writing/reading the swap space, etc. This will help improve the performance of the THP swap. - The THP swap space read/write will be 2M sequential IO. It is particularly helpful for the swap read, which are usually 4k random IO. This will improve the performance of the THP swap too. - It will help the memory fragmentation, especially when the THP is heavily used by the applications. The 2M continuous pages will be free up after THP swapping out. - It will improve the THP utilization on the system with the swap turned on. Because the speed for khugepaged to collapse the normal pages into the THP is quite slow. After the THP is split during the swapping out, it will take quite long time for the normal pages to collapse back into the THP after being swapped in. The high THP utilization helps the efficiency of the page based memory management too. There are some concerns regarding THP swap in, mainly because possible enlarged read/write IO size (for swap in/out) may put more overhead on the storage device. To deal with that, the THP swap in should be turned on only when necessary. For example, it can be selected via "always/never/madvise" logic, to be turned on globally, turned off globally, or turned on only for VMA with MADV_HUGEPAGE, etc. This patchset is the first step for the THP swap support. The plan is to delay splitting THP step by step, finally avoid splitting THP during the THP swapping out and swap out/in the THP as a whole. As the first step, in this patchset, the splitting huge page is delayed from almost the first step of swapping out to after allocating the swap space for the THP and adding the THP into the swap cache. This will reduce lock acquiring/releasing for the locks used for the swap cache management. With the patchset, the swap out throughput improves 15.5% (from about 3.73GB/s to about 4.31GB/s) in the vm-scalability swap-w-seq test case with 8 processes. The test is done on a Xeon E5 v3 system. The swap device used is a RAM simulated PMEM (persistent memory) device. To test the sequential swapping out, the test case creates 8 processes, which sequentially allocate and write to the anonymous pages until the RAM and part of the swap device is used up. This patch (of 5): In this patch, splitting huge page is delayed from almost the first step of swapping out to after allocating the swap space for the THP (Transparent Huge Page) and adding the THP into the swap cache. This will batch the corresponding operation, thus improve THP swap out throughput. This is the first step for the THP swap optimization. The plan is to delay splitting the THP step by step and avoid splitting the THP finally. In this patch, one swap cluster is used to hold the contents of each THP swapped out. So, the size of the swap cluster is changed to that of the THP (Transparent Huge Page) on x86_64 architecture (512). For other architectures which want such THP swap optimization, ARCH_USES_THP_SWAP_CLUSTER needs to be selected in the Kconfig file for the architecture. In effect, this will enlarge swap cluster size by 2 times on x86_64. Which may make it harder to find a free cluster when the swap space becomes fragmented. So that, this may reduce the continuous swap space allocation and sequential write in theory. The performance test in 0day shows no regressions caused by this. In the future of THP swap optimization, some information of the swapped out THP (such as compound map count) will be recorded in the swap_cluster_info data structure. The mem cgroup swap accounting functions are enhanced to support charge or uncharge a swap cluster backing a THP as a whole. The swap cluster allocate/free functions are added to allocate/free a swap cluster for a THP. A fair simple algorithm is used for swap cluster allocation, that is, only the first swap device in priority list will be tried to allocate the swap cluster. The function will fail if the trying is not successful, and the caller will fallback to allocate a single swap slot instead. This works good enough for normal cases. If the difference of the number of the free swap clusters among multiple swap devices is significant, it is possible that some THPs are split earlier than necessary. For example, this could be caused by big size difference among multiple swap devices. The swap cache functions is enhanced to support add/delete THP to/from the swap cache as a set of (HPAGE_PMD_NR) sub-pages. This may be enhanced in the future with multi-order radix tree. But because we will split the THP soon during swapping out, that optimization doesn't make much sense for this first step. The THP splitting functions are enhanced to support to split THP in swap cache during swapping out. The page lock will be held during allocating the swap cluster, adding the THP into the swap cache and splitting the THP. So in the code path other than swapping out, if the THP need to be split, the PageSwapCache(THP) will be always false. The swap cluster is only available for SSD, so the THP swap optimization in this patchset has no effect for HDD. [ying.huang@intel.com: fix two issues in THP optimize patch] Link: http://lkml.kernel.org/r/87k25ed8zo.fsf@yhuang-dev.intel.com [hannes@cmpxchg.org: extensive cleanups and simplifications, reduce code size] Link: http://lkml.kernel.org/r/20170515112522.32457-2-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Signed-off-by: Johannes Weiner <hannes@cmpxchg.org> Suggested-by: Andrew Morton <akpm@linux-foundation.org> [for config option] Acked-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> [for changes in huge_memory.c and huge_mm.h] Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Ebru Akagunduz <ebru.akagunduz@gmail.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tejun Heo <tj@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Shaohua Li <shli@kernel.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-07 06:37:18 +08:00
return 0;
}
/*
* This must be called only on pages that have
* been verified to be in the swap cache and locked.
* It will never put the page into the free list,
* the caller has a reference on the page.
*/
void delete_from_swap_cache(struct page *page)
{
swp_entry_t entry = { .val = page_private(page) };
struct address_space *address_space = swap_address_space(entry);
xa_lock_irq(&address_space->i_pages);
__delete_from_swap_cache(page, entry);
xa_unlock_irq(&address_space->i_pages);
put_swap_page(page, entry);
mm, THP, swap: delay splitting THP during swap out Patch series "THP swap: Delay splitting THP during swapping out", v11. This patchset is to optimize the performance of Transparent Huge Page (THP) swap. Recently, the performance of the storage devices improved so fast that we cannot saturate the disk bandwidth with single logical CPU when do page swap out even on a high-end server machine. Because the performance of the storage device improved faster than that of single logical CPU. And it seems that the trend will not change in the near future. On the other hand, the THP becomes more and more popular because of increased memory size. So it becomes necessary to optimize THP swap performance. The advantages of the THP swap support include: - Batch the swap operations for the THP to reduce lock acquiring/releasing, including allocating/freeing the swap space, adding/deleting to/from the swap cache, and writing/reading the swap space, etc. This will help improve the performance of the THP swap. - The THP swap space read/write will be 2M sequential IO. It is particularly helpful for the swap read, which are usually 4k random IO. This will improve the performance of the THP swap too. - It will help the memory fragmentation, especially when the THP is heavily used by the applications. The 2M continuous pages will be free up after THP swapping out. - It will improve the THP utilization on the system with the swap turned on. Because the speed for khugepaged to collapse the normal pages into the THP is quite slow. After the THP is split during the swapping out, it will take quite long time for the normal pages to collapse back into the THP after being swapped in. The high THP utilization helps the efficiency of the page based memory management too. There are some concerns regarding THP swap in, mainly because possible enlarged read/write IO size (for swap in/out) may put more overhead on the storage device. To deal with that, the THP swap in should be turned on only when necessary. For example, it can be selected via "always/never/madvise" logic, to be turned on globally, turned off globally, or turned on only for VMA with MADV_HUGEPAGE, etc. This patchset is the first step for the THP swap support. The plan is to delay splitting THP step by step, finally avoid splitting THP during the THP swapping out and swap out/in the THP as a whole. As the first step, in this patchset, the splitting huge page is delayed from almost the first step of swapping out to after allocating the swap space for the THP and adding the THP into the swap cache. This will reduce lock acquiring/releasing for the locks used for the swap cache management. With the patchset, the swap out throughput improves 15.5% (from about 3.73GB/s to about 4.31GB/s) in the vm-scalability swap-w-seq test case with 8 processes. The test is done on a Xeon E5 v3 system. The swap device used is a RAM simulated PMEM (persistent memory) device. To test the sequential swapping out, the test case creates 8 processes, which sequentially allocate and write to the anonymous pages until the RAM and part of the swap device is used up. This patch (of 5): In this patch, splitting huge page is delayed from almost the first step of swapping out to after allocating the swap space for the THP (Transparent Huge Page) and adding the THP into the swap cache. This will batch the corresponding operation, thus improve THP swap out throughput. This is the first step for the THP swap optimization. The plan is to delay splitting the THP step by step and avoid splitting the THP finally. In this patch, one swap cluster is used to hold the contents of each THP swapped out. So, the size of the swap cluster is changed to that of the THP (Transparent Huge Page) on x86_64 architecture (512). For other architectures which want such THP swap optimization, ARCH_USES_THP_SWAP_CLUSTER needs to be selected in the Kconfig file for the architecture. In effect, this will enlarge swap cluster size by 2 times on x86_64. Which may make it harder to find a free cluster when the swap space becomes fragmented. So that, this may reduce the continuous swap space allocation and sequential write in theory. The performance test in 0day shows no regressions caused by this. In the future of THP swap optimization, some information of the swapped out THP (such as compound map count) will be recorded in the swap_cluster_info data structure. The mem cgroup swap accounting functions are enhanced to support charge or uncharge a swap cluster backing a THP as a whole. The swap cluster allocate/free functions are added to allocate/free a swap cluster for a THP. A fair simple algorithm is used for swap cluster allocation, that is, only the first swap device in priority list will be tried to allocate the swap cluster. The function will fail if the trying is not successful, and the caller will fallback to allocate a single swap slot instead. This works good enough for normal cases. If the difference of the number of the free swap clusters among multiple swap devices is significant, it is possible that some THPs are split earlier than necessary. For example, this could be caused by big size difference among multiple swap devices. The swap cache functions is enhanced to support add/delete THP to/from the swap cache as a set of (HPAGE_PMD_NR) sub-pages. This may be enhanced in the future with multi-order radix tree. But because we will split the THP soon during swapping out, that optimization doesn't make much sense for this first step. The THP splitting functions are enhanced to support to split THP in swap cache during swapping out. The page lock will be held during allocating the swap cluster, adding the THP into the swap cache and splitting the THP. So in the code path other than swapping out, if the THP need to be split, the PageSwapCache(THP) will be always false. The swap cluster is only available for SSD, so the THP swap optimization in this patchset has no effect for HDD. [ying.huang@intel.com: fix two issues in THP optimize patch] Link: http://lkml.kernel.org/r/87k25ed8zo.fsf@yhuang-dev.intel.com [hannes@cmpxchg.org: extensive cleanups and simplifications, reduce code size] Link: http://lkml.kernel.org/r/20170515112522.32457-2-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Signed-off-by: Johannes Weiner <hannes@cmpxchg.org> Suggested-by: Andrew Morton <akpm@linux-foundation.org> [for config option] Acked-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> [for changes in huge_memory.c and huge_mm.h] Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Ebru Akagunduz <ebru.akagunduz@gmail.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Michal Hocko <mhocko@kernel.org> Cc: Tejun Heo <tj@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Shaohua Li <shli@kernel.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-07 06:37:18 +08:00
page_ref_sub(page, hpage_nr_pages(page));
}
/*
* If we are the only user, then try to free up the swap cache.
*
* Its ok to check for PageSwapCache without the page lock
mm: try_to_free_swap replaces remove_exclusive_swap_page remove_exclusive_swap_page(): its problem is in living up to its name. It doesn't matter if someone else has a reference to the page (raised page_count); it doesn't matter if the page is mapped into userspace (raised page_mapcount - though that hints it may be worth keeping the swap): all that matters is that there be no more references to the swap (and no writeback in progress). swapoff (try_to_unuse) has been removing pages from swapcache for years, with no concern for page count or page mapcount, and we used to have a comment in lookup_swap_cache() recognizing that: if you go for a page of swapcache, you'll get the right page, but it could have been removed from swapcache by the time you get page lock. So, give up asking for exclusivity: get rid of remove_exclusive_swap_page(), and remove_exclusive_swap_page_ref() and remove_exclusive_swap_page_count() which were spawned for the recent LRU work: replace them by the simpler try_to_free_swap() which just checks page_swapcount(). Similarly, remove the page_count limitation from free_swap_and_count(), but assume that it's worth holding on to the swap if page is mapped and swap nowhere near full. Add a vm_swap_full() test in free_swap_cache()? It would be consistent, but I think we probably have enough for now. Signed-off-by: Hugh Dickins <hugh@veritas.com> Cc: Lee Schermerhorn <lee.schermerhorn@hp.com> Cc: Rik van Riel <riel@redhat.com> Cc: Nick Piggin <nickpiggin@yahoo.com.au> Cc: KAMEZAWA Hiroyuki <kamezawa.hiroyu@jp.fujitsu.com> Cc: Robin Holt <holt@sgi.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2009-01-07 06:39:36 +08:00
* here because we are going to recheck again inside
* try_to_free_swap() _with_ the lock.
* - Marcelo
*/
static inline void free_swap_cache(struct page *page)
{
mm: try_to_free_swap replaces remove_exclusive_swap_page remove_exclusive_swap_page(): its problem is in living up to its name. It doesn't matter if someone else has a reference to the page (raised page_count); it doesn't matter if the page is mapped into userspace (raised page_mapcount - though that hints it may be worth keeping the swap): all that matters is that there be no more references to the swap (and no writeback in progress). swapoff (try_to_unuse) has been removing pages from swapcache for years, with no concern for page count or page mapcount, and we used to have a comment in lookup_swap_cache() recognizing that: if you go for a page of swapcache, you'll get the right page, but it could have been removed from swapcache by the time you get page lock. So, give up asking for exclusivity: get rid of remove_exclusive_swap_page(), and remove_exclusive_swap_page_ref() and remove_exclusive_swap_page_count() which were spawned for the recent LRU work: replace them by the simpler try_to_free_swap() which just checks page_swapcount(). Similarly, remove the page_count limitation from free_swap_and_count(), but assume that it's worth holding on to the swap if page is mapped and swap nowhere near full. Add a vm_swap_full() test in free_swap_cache()? It would be consistent, but I think we probably have enough for now. Signed-off-by: Hugh Dickins <hugh@veritas.com> Cc: Lee Schermerhorn <lee.schermerhorn@hp.com> Cc: Rik van Riel <riel@redhat.com> Cc: Nick Piggin <nickpiggin@yahoo.com.au> Cc: KAMEZAWA Hiroyuki <kamezawa.hiroyu@jp.fujitsu.com> Cc: Robin Holt <holt@sgi.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2009-01-07 06:39:36 +08:00
if (PageSwapCache(page) && !page_mapped(page) && trylock_page(page)) {
try_to_free_swap(page);
unlock_page(page);
}
}
/*
* Perform a free_page(), also freeing any swap cache associated with
* this page if it is the last user of the page.
*/
void free_page_and_swap_cache(struct page *page)
{
free_swap_cache(page);
thp: reduce usage of huge zero page's atomic counter The global zero page is used to satisfy an anonymous read fault. If THP(Transparent HugePage) is enabled then the global huge zero page is used. The global huge zero page uses an atomic counter for reference counting and is allocated/freed dynamically according to its counter value. CPU time spent on that counter will greatly increase if there are a lot of processes doing anonymous read faults. This patch proposes a way to reduce the access to the global counter so that the CPU load can be reduced accordingly. To do this, a new flag of the mm_struct is introduced: MMF_USED_HUGE_ZERO_PAGE. With this flag, the process only need to touch the global counter in two cases: 1 The first time it uses the global huge zero page; 2 The time when mm_user of its mm_struct reaches zero. Note that right now, the huge zero page is eligible to be freed as soon as its last use goes away. With this patch, the page will not be eligible to be freed until the exit of the last process from which it was ever used. And with the use of mm_user, the kthread is not eligible to use huge zero page either. Since no kthread is using huge zero page today, there is no difference after applying this patch. But if that is not desired, I can change it to when mm_count reaches zero. Case used for test on Haswell EP: usemem -n 72 --readonly -j 0x200000 100G Which spawns 72 processes and each will mmap 100G anonymous space and then do read only access to that space sequentially with a step of 2MB. CPU cycles from perf report for base commit: 54.03% usemem [kernel.kallsyms] [k] get_huge_zero_page CPU cycles from perf report for this commit: 0.11% usemem [kernel.kallsyms] [k] mm_get_huge_zero_page Performance(throughput) of the workload for base commit: 1784430792 Performance(throughput) of the workload for this commit: 4726928591 164% increase. Runtime of the workload for base commit: 707592 us Runtime of the workload for this commit: 303970 us 50% drop. Link: http://lkml.kernel.org/r/fe51a88f-446a-4622-1363-ad1282d71385@intel.com Signed-off-by: Aaron Lu <aaron.lu@intel.com> Cc: Sergey Senozhatsky <sergey.senozhatsky@gmail.com> Cc: "Kirill A. Shutemov" <kirill.shutemov@linux.intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Tim Chen <tim.c.chen@linux.intel.com> Cc: Huang Ying <ying.huang@intel.com> Cc: Vlastimil Babka <vbabka@suse.cz> Cc: Jerome Marchand <jmarchan@redhat.com> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Mel Gorman <mgorman@techsingularity.net> Cc: Ebru Akagunduz <ebru.akagunduz@gmail.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2016-10-08 08:00:08 +08:00
if (!is_huge_zero_page(page))
mm: thp: broken page count after commit aa88b68c3b1d Christian Borntraeger reported a kernel panic after corrupt page counts, and it turned out to be a regression introduced with commit aa88b68c3b1d ("thp: keep huge zero page pinned until tlb flush"), at least on s390. put_huge_zero_page() was moved over from zap_huge_pmd() to release_pages(), and it was replaced by tlb_remove_page(). However, release_pages() might not always be triggered by (the arch-specific) tlb_remove_page(). On s390 we call free_page_and_swap_cache() from tlb_remove_page(), and not tlb_flush_mmu() -> free_pages_and_swap_cache() like the generic version, because we don't use the MMU-gather logic. Although both functions have very similar names, they are doing very unsimilar things, in particular free_page_xxx is just doing a put_page(), while free_pages_xxx calls release_pages(). This of course results in very harmful put_page()s on the huge zero page, on architectures where tlb_remove_page() is implemented in this way. It seems to affect only s390 and sh, but sh doesn't have THP support, so the problem (currently) probably only exists on s390. The following quick hack fixed the issue: Link: http://lkml.kernel.org/r/20160602172141.75c006a9@thinkpad Signed-off-by: Gerald Schaefer <gerald.schaefer@de.ibm.com> Reported-by: Christian Borntraeger <borntraeger@de.ibm.com> Tested-by: Christian Borntraeger <borntraeger@de.ibm.com> Cc: "Kirill A. Shutemov" <kirill@shutemov.name> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: "Aneesh Kumar K.V" <aneesh.kumar@linux.vnet.ibm.com> Cc: Mel Gorman <mgorman@techsingularity.net> Cc: Hugh Dickins <hughd@google.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Vlastimil Babka <vbabka@suse.cz> Cc: Martin Schwidefsky <schwidefsky@de.ibm.com> Cc: Heiko Carstens <heiko.carstens@de.ibm.com> Cc: <stable@vger.kernel.org> [4.6.x] Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2016-06-09 06:33:50 +08:00
put_page(page);
}
/*
* Passed an array of pages, drop them all from swapcache and then release
* them. They are removed from the LRU and freed if this is their last use.
*/
void free_pages_and_swap_cache(struct page **pages, int nr)
{
struct page **pagep = pages;
mm: memcontrol: do not kill uncharge batching in free_pages_and_swap_cache free_pages_and_swap_cache limits release_pages to PAGEVEC_SIZE chunks. This is not a big deal for the normal release path but it completely kills memcg uncharge batching which reduces res_counter spin_lock contention. Dave has noticed this with his page fault scalability test case on a large machine when the lock was basically dominating on all CPUs: 80.18% 80.18% [kernel] [k] _raw_spin_lock | --- _raw_spin_lock | |--66.59%-- res_counter_uncharge_until | res_counter_uncharge | uncharge_batch | uncharge_list | mem_cgroup_uncharge_list | release_pages | free_pages_and_swap_cache | tlb_flush_mmu_free | | | |--90.12%-- unmap_single_vma | | unmap_vmas | | unmap_region | | do_munmap | | vm_munmap | | sys_munmap | | system_call_fastpath | | __GI___munmap | | | --9.88%-- tlb_flush_mmu | tlb_finish_mmu | unmap_region | do_munmap | vm_munmap | sys_munmap | system_call_fastpath | __GI___munmap In his case the load was running in the root memcg and that part has been handled by reverting 05b843012335 ("mm: memcontrol: use root_mem_cgroup res_counter") because this is a clear regression, but the problem remains inside dedicated memcgs. There is no reason to limit release_pages to PAGEVEC_SIZE batches other than lru_lock held times. This logic, however, can be moved inside the function. mem_cgroup_uncharge_list and free_hot_cold_page_list do not hold any lock for the whole pages_to_free list so it is safe to call them in a single run. The release_pages() code was previously breaking the lru_lock each PAGEVEC_SIZE pages (ie, 14 pages). However this code has no usage of pagevecs so switch to breaking the lock at least every SWAP_CLUSTER_MAX (32) pages. This means that the lock acquisition frequency is approximately halved and the max hold times are approximately doubled. The now unneeded batching is removed from free_pages_and_swap_cache(). Also update the grossly out-of-date release_pages documentation. Signed-off-by: Michal Hocko <mhocko@suse.cz> Signed-off-by: Johannes Weiner <hannes@cmpxchg.org> Reported-by: Dave Hansen <dave@sr71.net> Cc: Vladimir Davydov <vdavydov@parallels.com> Cc: Greg Thelen <gthelen@google.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2014-10-10 06:28:52 +08:00
int i;
lru_add_drain();
mm: memcontrol: do not kill uncharge batching in free_pages_and_swap_cache free_pages_and_swap_cache limits release_pages to PAGEVEC_SIZE chunks. This is not a big deal for the normal release path but it completely kills memcg uncharge batching which reduces res_counter spin_lock contention. Dave has noticed this with his page fault scalability test case on a large machine when the lock was basically dominating on all CPUs: 80.18% 80.18% [kernel] [k] _raw_spin_lock | --- _raw_spin_lock | |--66.59%-- res_counter_uncharge_until | res_counter_uncharge | uncharge_batch | uncharge_list | mem_cgroup_uncharge_list | release_pages | free_pages_and_swap_cache | tlb_flush_mmu_free | | | |--90.12%-- unmap_single_vma | | unmap_vmas | | unmap_region | | do_munmap | | vm_munmap | | sys_munmap | | system_call_fastpath | | __GI___munmap | | | --9.88%-- tlb_flush_mmu | tlb_finish_mmu | unmap_region | do_munmap | vm_munmap | sys_munmap | system_call_fastpath | __GI___munmap In his case the load was running in the root memcg and that part has been handled by reverting 05b843012335 ("mm: memcontrol: use root_mem_cgroup res_counter") because this is a clear regression, but the problem remains inside dedicated memcgs. There is no reason to limit release_pages to PAGEVEC_SIZE batches other than lru_lock held times. This logic, however, can be moved inside the function. mem_cgroup_uncharge_list and free_hot_cold_page_list do not hold any lock for the whole pages_to_free list so it is safe to call them in a single run. The release_pages() code was previously breaking the lru_lock each PAGEVEC_SIZE pages (ie, 14 pages). However this code has no usage of pagevecs so switch to breaking the lock at least every SWAP_CLUSTER_MAX (32) pages. This means that the lock acquisition frequency is approximately halved and the max hold times are approximately doubled. The now unneeded batching is removed from free_pages_and_swap_cache(). Also update the grossly out-of-date release_pages documentation. Signed-off-by: Michal Hocko <mhocko@suse.cz> Signed-off-by: Johannes Weiner <hannes@cmpxchg.org> Reported-by: Dave Hansen <dave@sr71.net> Cc: Vladimir Davydov <vdavydov@parallels.com> Cc: Greg Thelen <gthelen@google.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2014-10-10 06:28:52 +08:00
for (i = 0; i < nr; i++)
free_swap_cache(pagep[i]);
release_pages(pagep, nr);
}
static inline bool swap_use_vma_readahead(void)
{
return READ_ONCE(enable_vma_readahead) && !atomic_read(&nr_rotate_swap);
}
/*
* Lookup a swap entry in the swap cache. A found page will be returned
* unlocked and with its refcount incremented - we rely on the kernel
* lock getting page table operations atomic even if we drop the page
* lock before returning.
*/
mm, swap: VMA based swap readahead The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patch, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:36 +08:00
struct page *lookup_swap_cache(swp_entry_t entry, struct vm_area_struct *vma,
unsigned long addr)
{
struct page *page;
mm, swap: use offset of swap entry as key of swap cache This patch is to improve the performance of swap cache operations when the type of the swap device is not 0. Originally, the whole swap entry value is used as the key of the swap cache, even though there is one radix tree for each swap device. If the type of the swap device is not 0, the height of the radix tree of the swap cache will be increased unnecessary, especially on 64bit architecture. For example, for a 1GB swap device on the x86_64 architecture, the height of the radix tree of the swap cache is 11. But if the offset of the swap entry is used as the key of the swap cache, the height of the radix tree of the swap cache is 4. The increased height causes unnecessary radix tree descending and increased cache footprint. This patch reduces the height of the radix tree of the swap cache via using the offset of the swap entry instead of the whole swap entry value as the key of the swap cache. In 32 processes sequential swap out test case on a Xeon E5 v3 system with RAM disk as swap, the lock contention for the spinlock of the swap cache is reduced from 20.15% to 12.19%, when the type of the swap device is 1. Use the whole swap entry as key, perf-profile.calltrace.cycles-pp._raw_spin_lock_irq.__add_to_swap_cache.add_to_swap_cache.add_to_swap.shrink_page_list: 10.37, perf-profile.calltrace.cycles-pp._raw_spin_lock_irqsave.__remove_mapping.shrink_page_list.shrink_inactive_list.shrink_node_memcg: 9.78, Use the swap offset as key, perf-profile.calltrace.cycles-pp._raw_spin_lock_irq.__add_to_swap_cache.add_to_swap_cache.add_to_swap.shrink_page_list: 6.25, perf-profile.calltrace.cycles-pp._raw_spin_lock_irqsave.__remove_mapping.shrink_page_list.shrink_inactive_list.shrink_node_memcg: 5.94, Link: http://lkml.kernel.org/r/1473270649-27229-1-git-send-email-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Michal Hocko <mhocko@kernel.org> Cc: Vladimir Davydov <vdavydov.dev@gmail.com> Cc: "Kirill A. Shutemov" <kirill.shutemov@linux.intel.com> Cc: Dave Hansen <dave.hansen@linux.intel.com> Cc: Dan Williams <dan.j.williams@intel.com> Cc: Joonsoo Kim <iamjoonsoo.kim@lge.com> Cc: Hugh Dickins <hughd@google.com> Cc: Mel Gorman <mgorman@techsingularity.net> Cc: Minchan Kim <minchan@kernel.org> Cc: Aaron Lu <aaron.lu@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2016-10-08 08:00:21 +08:00
page = find_get_page(swap_address_space(entry), swp_offset(entry));
mm, swap: VMA based swap readahead The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patch, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:36 +08:00
INC_CACHE_INFO(find_total);
if (page) {
bool vma_ra = swap_use_vma_readahead();
bool readahead;
INC_CACHE_INFO(find_success);
/*
* At the moment, we don't support PG_readahead for anon THP
* so let's bail out rather than confusing the readahead stat.
*/
mm, swap: VMA based swap readahead The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patch, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:36 +08:00
if (unlikely(PageTransCompound(page)))
return page;
mm, swap: VMA based swap readahead The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patch, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:36 +08:00
readahead = TestClearPageReadahead(page);
if (vma && vma_ra) {
unsigned long ra_val;
int win, hits;
ra_val = GET_SWAP_RA_VAL(vma);
win = SWAP_RA_WIN(ra_val);
hits = SWAP_RA_HITS(ra_val);
mm, swap: VMA based swap readahead The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patch, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:36 +08:00
if (readahead)
hits = min_t(int, hits + 1, SWAP_RA_HITS_MAX);
atomic_long_set(&vma->swap_readahead_info,
SWAP_RA_VAL(addr, win, hits));
}
mm, swap: VMA based swap readahead The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patch, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:36 +08:00
if (readahead) {
mm, swap: add swap readahead hit statistics Patch series "mm, swap: VMA based swap readahead", v4. The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory space. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patchset, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. In addition to the swap readahead changes, some new sysfs interface is added to show the efficiency of the readahead algorithm and some other swap statistics. This new implementation will incur more small random read, on SSD, the improved correctness of estimation and readahead target should beat the potential increased overhead, this is also illustrated in the test results below. But on HDD, the overhead may beat the benefit, so the original implementation will be used by default. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. This patch (of 5): The statistics for total readahead pages and total readahead hits are recorded and exported via the following sysfs interface. /sys/kernel/mm/swap/ra_hits /sys/kernel/mm/swap/ra_total With them, the efficiency of the swap readahead could be measured, so that the swap readahead algorithm and parameters could be tuned accordingly. [akpm@linux-foundation.org: don't display swap stats if CONFIG_SWAP=n] Link: http://lkml.kernel.org/r/20170807054038.1843-2-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:29 +08:00
count_vm_event(SWAP_RA_HIT);
if (!vma || !vma_ra)
mm, swap: VMA based swap readahead The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patch, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:36 +08:00
atomic_inc(&swapin_readahead_hits);
mm, swap: add swap readahead hit statistics Patch series "mm, swap: VMA based swap readahead", v4. The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory space. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patchset, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. In addition to the swap readahead changes, some new sysfs interface is added to show the efficiency of the readahead algorithm and some other swap statistics. This new implementation will incur more small random read, on SSD, the improved correctness of estimation and readahead target should beat the potential increased overhead, this is also illustrated in the test results below. But on HDD, the overhead may beat the benefit, so the original implementation will be used by default. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. This patch (of 5): The statistics for total readahead pages and total readahead hits are recorded and exported via the following sysfs interface. /sys/kernel/mm/swap/ra_hits /sys/kernel/mm/swap/ra_total With them, the efficiency of the swap readahead could be measured, so that the swap readahead algorithm and parameters could be tuned accordingly. [akpm@linux-foundation.org: don't display swap stats if CONFIG_SWAP=n] Link: http://lkml.kernel.org/r/20170807054038.1843-2-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:29 +08:00
}
swap: add a simple detector for inappropriate swapin readahead This is a patch to improve swap readahead algorithm. It's from Hugh and I slightly changed it. Hugh's original changelog: swapin readahead does a blind readahead, whether or not the swapin is sequential. This may be ok on harddisk, because large reads have relatively small costs, and if the readahead pages are unneeded they can be reclaimed easily - though, what if their allocation forced reclaim of useful pages? But on SSD devices large reads are more expensive than small ones: if the readahead pages are unneeded, reading them in caused significant overhead. This patch adds very simplistic random read detection. Stealing the PageReadahead technique from Konstantin Khlebnikov's patch, avoiding the vma/anon_vma sophistications of Shaohua Li's patch, swapin_nr_pages() simply looks at readahead's current success rate, and narrows or widens its readahead window accordingly. There is little science to its heuristic: it's about as stupid as can be whilst remaining effective. The table below shows elapsed times (in centiseconds) when running a single repetitive swapping load across a 1000MB mapping in 900MB ram with 1GB swap (the harddisk tests had taken painfully too long when I used mem=500M, but SSD shows similar results for that). Vanilla is the 3.6-rc7 kernel on which I started; Shaohua denotes his Sep 3 patch in mmotm and linux-next; HughOld denotes my Oct 1 patch which Shaohua showed to be defective; HughNew this Nov 14 patch, with page_cluster as usual at default of 3 (8-page reads); HughPC4 this same patch with page_cluster 4 (16-page reads); HughPC0 with page_cluster 0 (1-page reads: no readahead). HDD for swapping to harddisk, SSD for swapping to VertexII SSD. Seq for sequential access to the mapping, cycling five times around; Rand for the same number of random touches. Anon for a MAP_PRIVATE anon mapping; Shmem for a MAP_SHARED anon mapping, equivalent to tmpfs. One weakness of Shaohua's vma/anon_vma approach was that it did not optimize Shmem: seen below. Konstantin's approach was perhaps mistuned, 50% slower on Seq: did not compete and is not shown below. HDD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0 Seq Anon 73921 76210 75611 76904 78191 121542 Seq Shmem 73601 73176 73855 72947 74543 118322 Rand Anon 895392 831243 871569 845197 846496 841680 Rand Shmem 1058375 1053486 827935 764955 764376 756489 SSD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0 Seq Anon 24634 24198 24673 25107 21614 70018 Seq Shmem 24959 24932 25052 25703 22030 69678 Rand Anon 43014 26146 28075 25989 26935 25901 Rand Shmem 45349 45215 28249 24268 24138 24332 These tests are, of course, two extremes of a very simple case: under heavier mixed loads I've not yet observed any consistent improvement or degradation, and wider testing would be welcome. Shaohua Li: Test shows Vanilla is slightly better in sequential workload than Hugh's patch. I observed with Hugh's patch sometimes the readahead size is shrinked too fast (from 8 to 1 immediately) in sequential workload if there is no hit. And in such case, continuing doing readahead is good actually. I don't prepare a sophisticated algorithm for the sequential workload because so far we can't guarantee sequential accessed pages are swap out sequentially. So I slightly change Hugh's heuristic - don't shrink readahead size too fast. Here is my test result (unit second, 3 runs average): Vanilla Hugh New Seq 356 370 360 Random 4525 2447 2444 Attached graph is the swapin/swapout throughput I collected with 'vmstat 2'. The first part is running a random workload (till around 1200 of the x-axis) and the second part is running a sequential workload. swapin and swapout throughput are almost identical in steady state in both workloads. These are expected behavior. while in Vanilla, swapin is much bigger than swapout especially in random workload (because wrong readahead). Original patches by: Shaohua Li and Konstantin Khlebnikov. [fengguang.wu@intel.com: swapin_nr_pages() can be static] Signed-off-by: Hugh Dickins <hughd@google.com> Signed-off-by: Shaohua Li <shli@fusionio.com> Signed-off-by: Fengguang Wu <fengguang.wu@intel.com> Cc: Rik van Riel <riel@redhat.com> Cc: Wu Fengguang <fengguang.wu@intel.com> Cc: Minchan Kim <minchan@kernel.org> Cc: Konstantin Khlebnikov <khlebnikov@openvz.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2014-02-07 04:04:21 +08:00
}
return page;
}
struct page *__read_swap_cache_async(swp_entry_t entry, gfp_t gfp_mask,
struct vm_area_struct *vma, unsigned long addr,
bool *new_page_allocated)
{
struct page *found_page, *new_page = NULL;
struct address_space *swapper_space = swap_address_space(entry);
int err;
*new_page_allocated = false;
do {
/*
* First check the swap cache. Since this is normally
* called after lookup_swap_cache() failed, re-calling
* that would confuse statistics.
*/
mm, swap: use offset of swap entry as key of swap cache This patch is to improve the performance of swap cache operations when the type of the swap device is not 0. Originally, the whole swap entry value is used as the key of the swap cache, even though there is one radix tree for each swap device. If the type of the swap device is not 0, the height of the radix tree of the swap cache will be increased unnecessary, especially on 64bit architecture. For example, for a 1GB swap device on the x86_64 architecture, the height of the radix tree of the swap cache is 11. But if the offset of the swap entry is used as the key of the swap cache, the height of the radix tree of the swap cache is 4. The increased height causes unnecessary radix tree descending and increased cache footprint. This patch reduces the height of the radix tree of the swap cache via using the offset of the swap entry instead of the whole swap entry value as the key of the swap cache. In 32 processes sequential swap out test case on a Xeon E5 v3 system with RAM disk as swap, the lock contention for the spinlock of the swap cache is reduced from 20.15% to 12.19%, when the type of the swap device is 1. Use the whole swap entry as key, perf-profile.calltrace.cycles-pp._raw_spin_lock_irq.__add_to_swap_cache.add_to_swap_cache.add_to_swap.shrink_page_list: 10.37, perf-profile.calltrace.cycles-pp._raw_spin_lock_irqsave.__remove_mapping.shrink_page_list.shrink_inactive_list.shrink_node_memcg: 9.78, Use the swap offset as key, perf-profile.calltrace.cycles-pp._raw_spin_lock_irq.__add_to_swap_cache.add_to_swap_cache.add_to_swap.shrink_page_list: 6.25, perf-profile.calltrace.cycles-pp._raw_spin_lock_irqsave.__remove_mapping.shrink_page_list.shrink_inactive_list.shrink_node_memcg: 5.94, Link: http://lkml.kernel.org/r/1473270649-27229-1-git-send-email-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Michal Hocko <mhocko@kernel.org> Cc: Vladimir Davydov <vdavydov.dev@gmail.com> Cc: "Kirill A. Shutemov" <kirill.shutemov@linux.intel.com> Cc: Dave Hansen <dave.hansen@linux.intel.com> Cc: Dan Williams <dan.j.williams@intel.com> Cc: Joonsoo Kim <iamjoonsoo.kim@lge.com> Cc: Hugh Dickins <hughd@google.com> Cc: Mel Gorman <mgorman@techsingularity.net> Cc: Minchan Kim <minchan@kernel.org> Cc: Aaron Lu <aaron.lu@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2016-10-08 08:00:21 +08:00
found_page = find_get_page(swapper_space, swp_offset(entry));
if (found_page)
break;
mm/swap: skip readahead only when swap slot cache is enabled Because during swap off, a swap entry may have swap_map[] == SWAP_HAS_CACHE (for example, just allocated). If we return NULL in __read_swap_cache_async(), the swap off will abort. So when swap slot cache is disabled, (for swap off), we will wait for page to be put into swap cache in such race condition. This should not be a problem for swap slot cache, because swap slot cache should be drained after clearing swap_slot_cache_enabled. [ying.huang@intel.com: fix memory leak in __read_swap_cache_async()] Link: http://lkml.kernel.org/r/874lzt6znd.fsf@yhuang-dev.intel.com Link: http://lkml.kernel.org/r/5e2c5f6abe8e6eb0797408897b1bba80938e9b9d.1484082593.git.tim.c.chen@linux.intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Signed-off-by: Tim Chen <tim.c.chen@linux.intel.com> Cc: Aaron Lu <aaron.lu@intel.com> Cc: Andi Kleen <ak@linux.intel.com> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Christian Borntraeger <borntraeger@de.ibm.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Hillf Danton <hillf.zj@alibaba-inc.com> Cc: Huang Ying <ying.huang@intel.com> Cc: Hugh Dickins <hughd@google.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Corbet <corbet@lwn.net> escreveu: Cc: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Vladimir Davydov <vdavydov.dev@gmail.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-02-23 07:45:46 +08:00
/*
* Just skip read ahead for unused swap slot.
* During swap_off when swap_slot_cache is disabled,
* we have to handle the race between putting
* swap entry in swap cache and marking swap slot
* as SWAP_HAS_CACHE. That's done in later part of code or
* else swap_off will be aborted if we return NULL.
*/
if (!__swp_swapcount(entry) && swap_slot_cache_enabled)
break;
/*
* Get a new page to read into from swap.
*/
if (!new_page) {
new_page = alloc_page_vma(gfp_mask, vma, addr);
if (!new_page)
break; /* Out of memory */
}
/*
* Swap entry may have been freed since our caller observed it.
*/
err = swapcache_prepare(entry);
if (err == -EEXIST) {
/*
* We might race against get_swap_page() and stumble
* across a SWAP_HAS_CACHE swap_map entry whose page
* has not been brought into the swapcache yet.
*/
cond_resched();
continue;
} else if (err) /* swp entry is obsolete ? */
break;
/* May fail (-ENOMEM) if XArray node allocation failed. */
__SetPageLocked(new_page);
mm: use __SetPageSwapBacked and dont ClearPageSwapBacked v3.16 commit 07a427884348 ("mm: shmem: avoid atomic operation during shmem_getpage_gfp") rightly replaced one instance of SetPageSwapBacked by __SetPageSwapBacked, pointing out that the newly allocated page is not yet visible to other users (except speculative get_page_unless_zero- ers, who may not update page flags before their further checks). That was part of a series in which Mel was focused on tmpfs profiles: but almost all SetPageSwapBacked uses can be so optimized, with the same justification. Remove ClearPageSwapBacked from __read_swap_cache_async() error path: it's not an error to free a page with PG_swapbacked set. Follow a convention of __SetPageLocked, __SetPageSwapBacked instead of doing it differently in different places; but that's for tidiness - if the ordering actually mattered, we should not be using the __variants. There's probably scope for further __SetPageFlags in other places, but SwapBacked is the one I'm interested in at the moment. Signed-off-by: Hugh Dickins <hughd@google.com> Cc: "Kirill A. Shutemov" <kirill.shutemov@linux.intel.com> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Andres Lagar-Cavilla <andreslc@google.com> Cc: Yang Shi <yang.shi@linaro.org> Cc: Ning Qu <quning@gmail.com> Reviewed-by: Mel Gorman <mgorman@techsingularity.net> Cc: Konstantin Khlebnikov <koct9i@gmail.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2016-05-20 08:12:41 +08:00
__SetPageSwapBacked(new_page);
err = add_to_swap_cache(new_page, entry, gfp_mask & GFP_KERNEL);
if (likely(!err)) {
/* Initiate read into locked page */
mm: workingset: tell cache transitions from workingset thrashing Refaults happen during transitions between workingsets as well as in-place thrashing. Knowing the difference between the two has a range of applications, including measuring the impact of memory shortage on the system performance, as well as the ability to smarter balance pressure between the filesystem cache and the swap-backed workingset. During workingset transitions, inactive cache refaults and pushes out established active cache. When that active cache isn't stale, however, and also ends up refaulting, that's bonafide thrashing. Introduce a new page flag that tells on eviction whether the page has been active or not in its lifetime. This bit is then stored in the shadow entry, to classify refaults as transitioning or thrashing. How many page->flags does this leave us with on 32-bit? 20 bits are always page flags 21 if you have an MMU 23 with the zone bits for DMA, Normal, HighMem, Movable 29 with the sparsemem section bits 30 if PAE is enabled 31 with this patch. So on 32-bit PAE, that leaves 1 bit for distinguishing two NUMA nodes. If that's not enough, the system can switch to discontigmem and re-gain the 6 or 7 sparsemem section bits. Link: http://lkml.kernel.org/r/20180828172258.3185-3-hannes@cmpxchg.org Signed-off-by: Johannes Weiner <hannes@cmpxchg.org> Acked-by: Peter Zijlstra (Intel) <peterz@infradead.org> Tested-by: Daniel Drake <drake@endlessm.com> Tested-by: Suren Baghdasaryan <surenb@google.com> Cc: Christopher Lameter <cl@linux.com> Cc: Ingo Molnar <mingo@redhat.com> Cc: Johannes Weiner <jweiner@fb.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Enderborg <peter.enderborg@sony.com> Cc: Randy Dunlap <rdunlap@infradead.org> Cc: Shakeel Butt <shakeelb@google.com> Cc: Tejun Heo <tj@kernel.org> Cc: Vinayak Menon <vinmenon@codeaurora.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2018-10-27 06:06:04 +08:00
SetPageWorkingset(new_page);
lru_cache_add_anon(new_page);
*new_page_allocated = true;
return new_page;
}
__ClearPageLocked(new_page);
/*
* add_to_swap_cache() doesn't return -EEXIST, so we can safely
* clear SWAP_HAS_CACHE flag.
*/
put_swap_page(new_page, entry);
} while (err != -ENOMEM);
if (new_page)
mm, fs: get rid of PAGE_CACHE_* and page_cache_{get,release} macros PAGE_CACHE_{SIZE,SHIFT,MASK,ALIGN} macros were introduced *long* time ago with promise that one day it will be possible to implement page cache with bigger chunks than PAGE_SIZE. This promise never materialized. And unlikely will. We have many places where PAGE_CACHE_SIZE assumed to be equal to PAGE_SIZE. And it's constant source of confusion on whether PAGE_CACHE_* or PAGE_* constant should be used in a particular case, especially on the border between fs and mm. Global switching to PAGE_CACHE_SIZE != PAGE_SIZE would cause to much breakage to be doable. Let's stop pretending that pages in page cache are special. They are not. The changes are pretty straight-forward: - <foo> << (PAGE_CACHE_SHIFT - PAGE_SHIFT) -> <foo>; - <foo> >> (PAGE_CACHE_SHIFT - PAGE_SHIFT) -> <foo>; - PAGE_CACHE_{SIZE,SHIFT,MASK,ALIGN} -> PAGE_{SIZE,SHIFT,MASK,ALIGN}; - page_cache_get() -> get_page(); - page_cache_release() -> put_page(); This patch contains automated changes generated with coccinelle using script below. For some reason, coccinelle doesn't patch header files. I've called spatch for them manually. The only adjustment after coccinelle is revert of changes to PAGE_CAHCE_ALIGN definition: we are going to drop it later. There are few places in the code where coccinelle didn't reach. I'll fix them manually in a separate patch. Comments and documentation also will be addressed with the separate patch. virtual patch @@ expression E; @@ - E << (PAGE_CACHE_SHIFT - PAGE_SHIFT) + E @@ expression E; @@ - E >> (PAGE_CACHE_SHIFT - PAGE_SHIFT) + E @@ @@ - PAGE_CACHE_SHIFT + PAGE_SHIFT @@ @@ - PAGE_CACHE_SIZE + PAGE_SIZE @@ @@ - PAGE_CACHE_MASK + PAGE_MASK @@ expression E; @@ - PAGE_CACHE_ALIGN(E) + PAGE_ALIGN(E) @@ expression E; @@ - page_cache_get(E) + get_page(E) @@ expression E; @@ - page_cache_release(E) + put_page(E) Signed-off-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> Acked-by: Michal Hocko <mhocko@suse.com> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2016-04-01 20:29:47 +08:00
put_page(new_page);
return found_page;
}
/*
* Locate a page of swap in physical memory, reserving swap cache space
* and reading the disk if it is not already cached.
* A failure return means that either the page allocation failed or that
* the swap entry is no longer in use.
*/
struct page *read_swap_cache_async(swp_entry_t entry, gfp_t gfp_mask,
swap: add block io poll in swapin path For fast flash disk, async IO could introduce overhead because of context switch. block-mq now supports IO poll, which improves performance and latency a lot. swapin is a good place to use this technique, because the task is waiting for the swapin page to continue execution. In my virtual machine, directly read 4k data from a NVMe with iopoll is about 60% better than that without poll. With iopoll support in swapin patch, my microbenchmark (a task does random memory write) is about 10%~25% faster. CPU utilization increases a lot though, 2x and even 3x CPU utilization. This will depend on disk speed. While iopoll in swapin isn't intended for all usage cases, it's a win for latency sensistive workloads with high speed swap disk. block layer has knob to control poll in runtime. If poll isn't enabled in block layer, there should be no noticeable change in swapin. I got a chance to run the same test in a NVMe with DRAM as the media. In simple fio IO test, blkpoll boosts 50% performance in single thread test and ~20% in 8 threads test. So this is the base line. In above swap test, blkpoll boosts ~27% performance in single thread test. blkpoll uses 2x CPU time though. If we enable hybid polling, the performance gain has very slight drop but CPU time is only 50% worse than that without blkpoll. Also we can adjust parameter of hybid poll, with it, the CPU time penality is reduced further. In 8 threads test, blkpoll doesn't help though. The performance is similar to that without blkpoll, but cpu utilization is similar too. There is lock contention in swap path. The cpu time spending on blkpoll isn't high. So overall, blkpoll swapin isn't worse than that without it. The swapin readahead might read several pages in in the same time and form a big IO request. Since the IO will take longer time, it doesn't make sense to do poll, so the patch only does iopoll for single page swapin. [akpm@linux-foundation.org: coding-style fixes] Link: http://lkml.kernel.org/r/070c3c3e40b711e7b1390002c991e86a-b5408f0@7511894063d3764ff01ea8111f5a004d7dd700ed078797c204a24e620ddb965c Signed-off-by: Shaohua Li <shli@fb.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Huang Ying <ying.huang@intel.com> Cc: Jens Axboe <axboe@fb.com> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-11 06:47:11 +08:00
struct vm_area_struct *vma, unsigned long addr, bool do_poll)
{
bool page_was_allocated;
struct page *retpage = __read_swap_cache_async(entry, gfp_mask,
vma, addr, &page_was_allocated);
if (page_was_allocated)
swap: add block io poll in swapin path For fast flash disk, async IO could introduce overhead because of context switch. block-mq now supports IO poll, which improves performance and latency a lot. swapin is a good place to use this technique, because the task is waiting for the swapin page to continue execution. In my virtual machine, directly read 4k data from a NVMe with iopoll is about 60% better than that without poll. With iopoll support in swapin patch, my microbenchmark (a task does random memory write) is about 10%~25% faster. CPU utilization increases a lot though, 2x and even 3x CPU utilization. This will depend on disk speed. While iopoll in swapin isn't intended for all usage cases, it's a win for latency sensistive workloads with high speed swap disk. block layer has knob to control poll in runtime. If poll isn't enabled in block layer, there should be no noticeable change in swapin. I got a chance to run the same test in a NVMe with DRAM as the media. In simple fio IO test, blkpoll boosts 50% performance in single thread test and ~20% in 8 threads test. So this is the base line. In above swap test, blkpoll boosts ~27% performance in single thread test. blkpoll uses 2x CPU time though. If we enable hybid polling, the performance gain has very slight drop but CPU time is only 50% worse than that without blkpoll. Also we can adjust parameter of hybid poll, with it, the CPU time penality is reduced further. In 8 threads test, blkpoll doesn't help though. The performance is similar to that without blkpoll, but cpu utilization is similar too. There is lock contention in swap path. The cpu time spending on blkpoll isn't high. So overall, blkpoll swapin isn't worse than that without it. The swapin readahead might read several pages in in the same time and form a big IO request. Since the IO will take longer time, it doesn't make sense to do poll, so the patch only does iopoll for single page swapin. [akpm@linux-foundation.org: coding-style fixes] Link: http://lkml.kernel.org/r/070c3c3e40b711e7b1390002c991e86a-b5408f0@7511894063d3764ff01ea8111f5a004d7dd700ed078797c204a24e620ddb965c Signed-off-by: Shaohua Li <shli@fb.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Huang Ying <ying.huang@intel.com> Cc: Jens Axboe <axboe@fb.com> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-11 06:47:11 +08:00
swap_readpage(retpage, do_poll);
return retpage;
}
mm, swap: VMA based swap readahead The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patch, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:36 +08:00
static unsigned int __swapin_nr_pages(unsigned long prev_offset,
unsigned long offset,
int hits,
int max_pages,
int prev_win)
swap: add a simple detector for inappropriate swapin readahead This is a patch to improve swap readahead algorithm. It's from Hugh and I slightly changed it. Hugh's original changelog: swapin readahead does a blind readahead, whether or not the swapin is sequential. This may be ok on harddisk, because large reads have relatively small costs, and if the readahead pages are unneeded they can be reclaimed easily - though, what if their allocation forced reclaim of useful pages? But on SSD devices large reads are more expensive than small ones: if the readahead pages are unneeded, reading them in caused significant overhead. This patch adds very simplistic random read detection. Stealing the PageReadahead technique from Konstantin Khlebnikov's patch, avoiding the vma/anon_vma sophistications of Shaohua Li's patch, swapin_nr_pages() simply looks at readahead's current success rate, and narrows or widens its readahead window accordingly. There is little science to its heuristic: it's about as stupid as can be whilst remaining effective. The table below shows elapsed times (in centiseconds) when running a single repetitive swapping load across a 1000MB mapping in 900MB ram with 1GB swap (the harddisk tests had taken painfully too long when I used mem=500M, but SSD shows similar results for that). Vanilla is the 3.6-rc7 kernel on which I started; Shaohua denotes his Sep 3 patch in mmotm and linux-next; HughOld denotes my Oct 1 patch which Shaohua showed to be defective; HughNew this Nov 14 patch, with page_cluster as usual at default of 3 (8-page reads); HughPC4 this same patch with page_cluster 4 (16-page reads); HughPC0 with page_cluster 0 (1-page reads: no readahead). HDD for swapping to harddisk, SSD for swapping to VertexII SSD. Seq for sequential access to the mapping, cycling five times around; Rand for the same number of random touches. Anon for a MAP_PRIVATE anon mapping; Shmem for a MAP_SHARED anon mapping, equivalent to tmpfs. One weakness of Shaohua's vma/anon_vma approach was that it did not optimize Shmem: seen below. Konstantin's approach was perhaps mistuned, 50% slower on Seq: did not compete and is not shown below. HDD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0 Seq Anon 73921 76210 75611 76904 78191 121542 Seq Shmem 73601 73176 73855 72947 74543 118322 Rand Anon 895392 831243 871569 845197 846496 841680 Rand Shmem 1058375 1053486 827935 764955 764376 756489 SSD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0 Seq Anon 24634 24198 24673 25107 21614 70018 Seq Shmem 24959 24932 25052 25703 22030 69678 Rand Anon 43014 26146 28075 25989 26935 25901 Rand Shmem 45349 45215 28249 24268 24138 24332 These tests are, of course, two extremes of a very simple case: under heavier mixed loads I've not yet observed any consistent improvement or degradation, and wider testing would be welcome. Shaohua Li: Test shows Vanilla is slightly better in sequential workload than Hugh's patch. I observed with Hugh's patch sometimes the readahead size is shrinked too fast (from 8 to 1 immediately) in sequential workload if there is no hit. And in such case, continuing doing readahead is good actually. I don't prepare a sophisticated algorithm for the sequential workload because so far we can't guarantee sequential accessed pages are swap out sequentially. So I slightly change Hugh's heuristic - don't shrink readahead size too fast. Here is my test result (unit second, 3 runs average): Vanilla Hugh New Seq 356 370 360 Random 4525 2447 2444 Attached graph is the swapin/swapout throughput I collected with 'vmstat 2'. The first part is running a random workload (till around 1200 of the x-axis) and the second part is running a sequential workload. swapin and swapout throughput are almost identical in steady state in both workloads. These are expected behavior. while in Vanilla, swapin is much bigger than swapout especially in random workload (because wrong readahead). Original patches by: Shaohua Li and Konstantin Khlebnikov. [fengguang.wu@intel.com: swapin_nr_pages() can be static] Signed-off-by: Hugh Dickins <hughd@google.com> Signed-off-by: Shaohua Li <shli@fusionio.com> Signed-off-by: Fengguang Wu <fengguang.wu@intel.com> Cc: Rik van Riel <riel@redhat.com> Cc: Wu Fengguang <fengguang.wu@intel.com> Cc: Minchan Kim <minchan@kernel.org> Cc: Konstantin Khlebnikov <khlebnikov@openvz.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2014-02-07 04:04:21 +08:00
{
mm, swap: VMA based swap readahead The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patch, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:36 +08:00
unsigned int pages, last_ra;
swap: add a simple detector for inappropriate swapin readahead This is a patch to improve swap readahead algorithm. It's from Hugh and I slightly changed it. Hugh's original changelog: swapin readahead does a blind readahead, whether or not the swapin is sequential. This may be ok on harddisk, because large reads have relatively small costs, and if the readahead pages are unneeded they can be reclaimed easily - though, what if their allocation forced reclaim of useful pages? But on SSD devices large reads are more expensive than small ones: if the readahead pages are unneeded, reading them in caused significant overhead. This patch adds very simplistic random read detection. Stealing the PageReadahead technique from Konstantin Khlebnikov's patch, avoiding the vma/anon_vma sophistications of Shaohua Li's patch, swapin_nr_pages() simply looks at readahead's current success rate, and narrows or widens its readahead window accordingly. There is little science to its heuristic: it's about as stupid as can be whilst remaining effective. The table below shows elapsed times (in centiseconds) when running a single repetitive swapping load across a 1000MB mapping in 900MB ram with 1GB swap (the harddisk tests had taken painfully too long when I used mem=500M, but SSD shows similar results for that). Vanilla is the 3.6-rc7 kernel on which I started; Shaohua denotes his Sep 3 patch in mmotm and linux-next; HughOld denotes my Oct 1 patch which Shaohua showed to be defective; HughNew this Nov 14 patch, with page_cluster as usual at default of 3 (8-page reads); HughPC4 this same patch with page_cluster 4 (16-page reads); HughPC0 with page_cluster 0 (1-page reads: no readahead). HDD for swapping to harddisk, SSD for swapping to VertexII SSD. Seq for sequential access to the mapping, cycling five times around; Rand for the same number of random touches. Anon for a MAP_PRIVATE anon mapping; Shmem for a MAP_SHARED anon mapping, equivalent to tmpfs. One weakness of Shaohua's vma/anon_vma approach was that it did not optimize Shmem: seen below. Konstantin's approach was perhaps mistuned, 50% slower on Seq: did not compete and is not shown below. HDD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0 Seq Anon 73921 76210 75611 76904 78191 121542 Seq Shmem 73601 73176 73855 72947 74543 118322 Rand Anon 895392 831243 871569 845197 846496 841680 Rand Shmem 1058375 1053486 827935 764955 764376 756489 SSD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0 Seq Anon 24634 24198 24673 25107 21614 70018 Seq Shmem 24959 24932 25052 25703 22030 69678 Rand Anon 43014 26146 28075 25989 26935 25901 Rand Shmem 45349 45215 28249 24268 24138 24332 These tests are, of course, two extremes of a very simple case: under heavier mixed loads I've not yet observed any consistent improvement or degradation, and wider testing would be welcome. Shaohua Li: Test shows Vanilla is slightly better in sequential workload than Hugh's patch. I observed with Hugh's patch sometimes the readahead size is shrinked too fast (from 8 to 1 immediately) in sequential workload if there is no hit. And in such case, continuing doing readahead is good actually. I don't prepare a sophisticated algorithm for the sequential workload because so far we can't guarantee sequential accessed pages are swap out sequentially. So I slightly change Hugh's heuristic - don't shrink readahead size too fast. Here is my test result (unit second, 3 runs average): Vanilla Hugh New Seq 356 370 360 Random 4525 2447 2444 Attached graph is the swapin/swapout throughput I collected with 'vmstat 2'. The first part is running a random workload (till around 1200 of the x-axis) and the second part is running a sequential workload. swapin and swapout throughput are almost identical in steady state in both workloads. These are expected behavior. while in Vanilla, swapin is much bigger than swapout especially in random workload (because wrong readahead). Original patches by: Shaohua Li and Konstantin Khlebnikov. [fengguang.wu@intel.com: swapin_nr_pages() can be static] Signed-off-by: Hugh Dickins <hughd@google.com> Signed-off-by: Shaohua Li <shli@fusionio.com> Signed-off-by: Fengguang Wu <fengguang.wu@intel.com> Cc: Rik van Riel <riel@redhat.com> Cc: Wu Fengguang <fengguang.wu@intel.com> Cc: Minchan Kim <minchan@kernel.org> Cc: Konstantin Khlebnikov <khlebnikov@openvz.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2014-02-07 04:04:21 +08:00
/*
* This heuristic has been found to work well on both sequential and
* random loads, swapping to hard disk or to SSD: please don't ask
* what the "+ 2" means, it just happens to work well, that's all.
*/
mm, swap: VMA based swap readahead The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patch, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:36 +08:00
pages = hits + 2;
swap: add a simple detector for inappropriate swapin readahead This is a patch to improve swap readahead algorithm. It's from Hugh and I slightly changed it. Hugh's original changelog: swapin readahead does a blind readahead, whether or not the swapin is sequential. This may be ok on harddisk, because large reads have relatively small costs, and if the readahead pages are unneeded they can be reclaimed easily - though, what if their allocation forced reclaim of useful pages? But on SSD devices large reads are more expensive than small ones: if the readahead pages are unneeded, reading them in caused significant overhead. This patch adds very simplistic random read detection. Stealing the PageReadahead technique from Konstantin Khlebnikov's patch, avoiding the vma/anon_vma sophistications of Shaohua Li's patch, swapin_nr_pages() simply looks at readahead's current success rate, and narrows or widens its readahead window accordingly. There is little science to its heuristic: it's about as stupid as can be whilst remaining effective. The table below shows elapsed times (in centiseconds) when running a single repetitive swapping load across a 1000MB mapping in 900MB ram with 1GB swap (the harddisk tests had taken painfully too long when I used mem=500M, but SSD shows similar results for that). Vanilla is the 3.6-rc7 kernel on which I started; Shaohua denotes his Sep 3 patch in mmotm and linux-next; HughOld denotes my Oct 1 patch which Shaohua showed to be defective; HughNew this Nov 14 patch, with page_cluster as usual at default of 3 (8-page reads); HughPC4 this same patch with page_cluster 4 (16-page reads); HughPC0 with page_cluster 0 (1-page reads: no readahead). HDD for swapping to harddisk, SSD for swapping to VertexII SSD. Seq for sequential access to the mapping, cycling five times around; Rand for the same number of random touches. Anon for a MAP_PRIVATE anon mapping; Shmem for a MAP_SHARED anon mapping, equivalent to tmpfs. One weakness of Shaohua's vma/anon_vma approach was that it did not optimize Shmem: seen below. Konstantin's approach was perhaps mistuned, 50% slower on Seq: did not compete and is not shown below. HDD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0 Seq Anon 73921 76210 75611 76904 78191 121542 Seq Shmem 73601 73176 73855 72947 74543 118322 Rand Anon 895392 831243 871569 845197 846496 841680 Rand Shmem 1058375 1053486 827935 764955 764376 756489 SSD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0 Seq Anon 24634 24198 24673 25107 21614 70018 Seq Shmem 24959 24932 25052 25703 22030 69678 Rand Anon 43014 26146 28075 25989 26935 25901 Rand Shmem 45349 45215 28249 24268 24138 24332 These tests are, of course, two extremes of a very simple case: under heavier mixed loads I've not yet observed any consistent improvement or degradation, and wider testing would be welcome. Shaohua Li: Test shows Vanilla is slightly better in sequential workload than Hugh's patch. I observed with Hugh's patch sometimes the readahead size is shrinked too fast (from 8 to 1 immediately) in sequential workload if there is no hit. And in such case, continuing doing readahead is good actually. I don't prepare a sophisticated algorithm for the sequential workload because so far we can't guarantee sequential accessed pages are swap out sequentially. So I slightly change Hugh's heuristic - don't shrink readahead size too fast. Here is my test result (unit second, 3 runs average): Vanilla Hugh New Seq 356 370 360 Random 4525 2447 2444 Attached graph is the swapin/swapout throughput I collected with 'vmstat 2'. The first part is running a random workload (till around 1200 of the x-axis) and the second part is running a sequential workload. swapin and swapout throughput are almost identical in steady state in both workloads. These are expected behavior. while in Vanilla, swapin is much bigger than swapout especially in random workload (because wrong readahead). Original patches by: Shaohua Li and Konstantin Khlebnikov. [fengguang.wu@intel.com: swapin_nr_pages() can be static] Signed-off-by: Hugh Dickins <hughd@google.com> Signed-off-by: Shaohua Li <shli@fusionio.com> Signed-off-by: Fengguang Wu <fengguang.wu@intel.com> Cc: Rik van Riel <riel@redhat.com> Cc: Wu Fengguang <fengguang.wu@intel.com> Cc: Minchan Kim <minchan@kernel.org> Cc: Konstantin Khlebnikov <khlebnikov@openvz.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2014-02-07 04:04:21 +08:00
if (pages == 2) {
/*
* We can have no readahead hits to judge by: but must not get
* stuck here forever, so check for an adjacent offset instead
* (and don't even bother to check whether swap type is same).
*/
if (offset != prev_offset + 1 && offset != prev_offset - 1)
pages = 1;
} else {
unsigned int roundup = 4;
while (roundup < pages)
roundup <<= 1;
pages = roundup;
}
if (pages > max_pages)
pages = max_pages;
/* Don't shrink readahead too fast */
mm, swap: VMA based swap readahead The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patch, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:36 +08:00
last_ra = prev_win / 2;
swap: add a simple detector for inappropriate swapin readahead This is a patch to improve swap readahead algorithm. It's from Hugh and I slightly changed it. Hugh's original changelog: swapin readahead does a blind readahead, whether or not the swapin is sequential. This may be ok on harddisk, because large reads have relatively small costs, and if the readahead pages are unneeded they can be reclaimed easily - though, what if their allocation forced reclaim of useful pages? But on SSD devices large reads are more expensive than small ones: if the readahead pages are unneeded, reading them in caused significant overhead. This patch adds very simplistic random read detection. Stealing the PageReadahead technique from Konstantin Khlebnikov's patch, avoiding the vma/anon_vma sophistications of Shaohua Li's patch, swapin_nr_pages() simply looks at readahead's current success rate, and narrows or widens its readahead window accordingly. There is little science to its heuristic: it's about as stupid as can be whilst remaining effective. The table below shows elapsed times (in centiseconds) when running a single repetitive swapping load across a 1000MB mapping in 900MB ram with 1GB swap (the harddisk tests had taken painfully too long when I used mem=500M, but SSD shows similar results for that). Vanilla is the 3.6-rc7 kernel on which I started; Shaohua denotes his Sep 3 patch in mmotm and linux-next; HughOld denotes my Oct 1 patch which Shaohua showed to be defective; HughNew this Nov 14 patch, with page_cluster as usual at default of 3 (8-page reads); HughPC4 this same patch with page_cluster 4 (16-page reads); HughPC0 with page_cluster 0 (1-page reads: no readahead). HDD for swapping to harddisk, SSD for swapping to VertexII SSD. Seq for sequential access to the mapping, cycling five times around; Rand for the same number of random touches. Anon for a MAP_PRIVATE anon mapping; Shmem for a MAP_SHARED anon mapping, equivalent to tmpfs. One weakness of Shaohua's vma/anon_vma approach was that it did not optimize Shmem: seen below. Konstantin's approach was perhaps mistuned, 50% slower on Seq: did not compete and is not shown below. HDD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0 Seq Anon 73921 76210 75611 76904 78191 121542 Seq Shmem 73601 73176 73855 72947 74543 118322 Rand Anon 895392 831243 871569 845197 846496 841680 Rand Shmem 1058375 1053486 827935 764955 764376 756489 SSD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0 Seq Anon 24634 24198 24673 25107 21614 70018 Seq Shmem 24959 24932 25052 25703 22030 69678 Rand Anon 43014 26146 28075 25989 26935 25901 Rand Shmem 45349 45215 28249 24268 24138 24332 These tests are, of course, two extremes of a very simple case: under heavier mixed loads I've not yet observed any consistent improvement or degradation, and wider testing would be welcome. Shaohua Li: Test shows Vanilla is slightly better in sequential workload than Hugh's patch. I observed with Hugh's patch sometimes the readahead size is shrinked too fast (from 8 to 1 immediately) in sequential workload if there is no hit. And in such case, continuing doing readahead is good actually. I don't prepare a sophisticated algorithm for the sequential workload because so far we can't guarantee sequential accessed pages are swap out sequentially. So I slightly change Hugh's heuristic - don't shrink readahead size too fast. Here is my test result (unit second, 3 runs average): Vanilla Hugh New Seq 356 370 360 Random 4525 2447 2444 Attached graph is the swapin/swapout throughput I collected with 'vmstat 2'. The first part is running a random workload (till around 1200 of the x-axis) and the second part is running a sequential workload. swapin and swapout throughput are almost identical in steady state in both workloads. These are expected behavior. while in Vanilla, swapin is much bigger than swapout especially in random workload (because wrong readahead). Original patches by: Shaohua Li and Konstantin Khlebnikov. [fengguang.wu@intel.com: swapin_nr_pages() can be static] Signed-off-by: Hugh Dickins <hughd@google.com> Signed-off-by: Shaohua Li <shli@fusionio.com> Signed-off-by: Fengguang Wu <fengguang.wu@intel.com> Cc: Rik van Riel <riel@redhat.com> Cc: Wu Fengguang <fengguang.wu@intel.com> Cc: Minchan Kim <minchan@kernel.org> Cc: Konstantin Khlebnikov <khlebnikov@openvz.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2014-02-07 04:04:21 +08:00
if (pages < last_ra)
pages = last_ra;
mm, swap: VMA based swap readahead The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patch, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:36 +08:00
return pages;
}
static unsigned long swapin_nr_pages(unsigned long offset)
{
static unsigned long prev_offset;
unsigned int hits, pages, max_pages;
static atomic_t last_readahead_pages;
max_pages = 1 << READ_ONCE(page_cluster);
if (max_pages <= 1)
return 1;
hits = atomic_xchg(&swapin_readahead_hits, 0);
pages = __swapin_nr_pages(prev_offset, offset, hits, max_pages,
atomic_read(&last_readahead_pages));
if (!hits)
prev_offset = offset;
swap: add a simple detector for inappropriate swapin readahead This is a patch to improve swap readahead algorithm. It's from Hugh and I slightly changed it. Hugh's original changelog: swapin readahead does a blind readahead, whether or not the swapin is sequential. This may be ok on harddisk, because large reads have relatively small costs, and if the readahead pages are unneeded they can be reclaimed easily - though, what if their allocation forced reclaim of useful pages? But on SSD devices large reads are more expensive than small ones: if the readahead pages are unneeded, reading them in caused significant overhead. This patch adds very simplistic random read detection. Stealing the PageReadahead technique from Konstantin Khlebnikov's patch, avoiding the vma/anon_vma sophistications of Shaohua Li's patch, swapin_nr_pages() simply looks at readahead's current success rate, and narrows or widens its readahead window accordingly. There is little science to its heuristic: it's about as stupid as can be whilst remaining effective. The table below shows elapsed times (in centiseconds) when running a single repetitive swapping load across a 1000MB mapping in 900MB ram with 1GB swap (the harddisk tests had taken painfully too long when I used mem=500M, but SSD shows similar results for that). Vanilla is the 3.6-rc7 kernel on which I started; Shaohua denotes his Sep 3 patch in mmotm and linux-next; HughOld denotes my Oct 1 patch which Shaohua showed to be defective; HughNew this Nov 14 patch, with page_cluster as usual at default of 3 (8-page reads); HughPC4 this same patch with page_cluster 4 (16-page reads); HughPC0 with page_cluster 0 (1-page reads: no readahead). HDD for swapping to harddisk, SSD for swapping to VertexII SSD. Seq for sequential access to the mapping, cycling five times around; Rand for the same number of random touches. Anon for a MAP_PRIVATE anon mapping; Shmem for a MAP_SHARED anon mapping, equivalent to tmpfs. One weakness of Shaohua's vma/anon_vma approach was that it did not optimize Shmem: seen below. Konstantin's approach was perhaps mistuned, 50% slower on Seq: did not compete and is not shown below. HDD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0 Seq Anon 73921 76210 75611 76904 78191 121542 Seq Shmem 73601 73176 73855 72947 74543 118322 Rand Anon 895392 831243 871569 845197 846496 841680 Rand Shmem 1058375 1053486 827935 764955 764376 756489 SSD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0 Seq Anon 24634 24198 24673 25107 21614 70018 Seq Shmem 24959 24932 25052 25703 22030 69678 Rand Anon 43014 26146 28075 25989 26935 25901 Rand Shmem 45349 45215 28249 24268 24138 24332 These tests are, of course, two extremes of a very simple case: under heavier mixed loads I've not yet observed any consistent improvement or degradation, and wider testing would be welcome. Shaohua Li: Test shows Vanilla is slightly better in sequential workload than Hugh's patch. I observed with Hugh's patch sometimes the readahead size is shrinked too fast (from 8 to 1 immediately) in sequential workload if there is no hit. And in such case, continuing doing readahead is good actually. I don't prepare a sophisticated algorithm for the sequential workload because so far we can't guarantee sequential accessed pages are swap out sequentially. So I slightly change Hugh's heuristic - don't shrink readahead size too fast. Here is my test result (unit second, 3 runs average): Vanilla Hugh New Seq 356 370 360 Random 4525 2447 2444 Attached graph is the swapin/swapout throughput I collected with 'vmstat 2'. The first part is running a random workload (till around 1200 of the x-axis) and the second part is running a sequential workload. swapin and swapout throughput are almost identical in steady state in both workloads. These are expected behavior. while in Vanilla, swapin is much bigger than swapout especially in random workload (because wrong readahead). Original patches by: Shaohua Li and Konstantin Khlebnikov. [fengguang.wu@intel.com: swapin_nr_pages() can be static] Signed-off-by: Hugh Dickins <hughd@google.com> Signed-off-by: Shaohua Li <shli@fusionio.com> Signed-off-by: Fengguang Wu <fengguang.wu@intel.com> Cc: Rik van Riel <riel@redhat.com> Cc: Wu Fengguang <fengguang.wu@intel.com> Cc: Minchan Kim <minchan@kernel.org> Cc: Konstantin Khlebnikov <khlebnikov@openvz.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2014-02-07 04:04:21 +08:00
atomic_set(&last_readahead_pages, pages);
return pages;
}
/**
* swap_cluster_readahead - swap in pages in hope we need them soon
* @entry: swap entry of this memory
* @gfp_mask: memory allocation flags
* @vmf: fault information
*
* Returns the struct page for entry and addr, after queueing swapin.
*
* Primitive swap readahead code. We simply read an aligned block of
* (1 << page_cluster) entries in the swap area. This method is chosen
* because it doesn't cost us any seek time. We also make sure to queue
* the 'original' request together with the readahead ones...
*
* This has been extended to use the NUMA policies from the mm triggering
* the readahead.
*
* Caller must hold down_read on the vma->vm_mm if vmf->vma is not NULL.
*/
struct page *swap_cluster_readahead(swp_entry_t entry, gfp_t gfp_mask,
struct vm_fault *vmf)
{
struct page *page;
swap: add a simple detector for inappropriate swapin readahead This is a patch to improve swap readahead algorithm. It's from Hugh and I slightly changed it. Hugh's original changelog: swapin readahead does a blind readahead, whether or not the swapin is sequential. This may be ok on harddisk, because large reads have relatively small costs, and if the readahead pages are unneeded they can be reclaimed easily - though, what if their allocation forced reclaim of useful pages? But on SSD devices large reads are more expensive than small ones: if the readahead pages are unneeded, reading them in caused significant overhead. This patch adds very simplistic random read detection. Stealing the PageReadahead technique from Konstantin Khlebnikov's patch, avoiding the vma/anon_vma sophistications of Shaohua Li's patch, swapin_nr_pages() simply looks at readahead's current success rate, and narrows or widens its readahead window accordingly. There is little science to its heuristic: it's about as stupid as can be whilst remaining effective. The table below shows elapsed times (in centiseconds) when running a single repetitive swapping load across a 1000MB mapping in 900MB ram with 1GB swap (the harddisk tests had taken painfully too long when I used mem=500M, but SSD shows similar results for that). Vanilla is the 3.6-rc7 kernel on which I started; Shaohua denotes his Sep 3 patch in mmotm and linux-next; HughOld denotes my Oct 1 patch which Shaohua showed to be defective; HughNew this Nov 14 patch, with page_cluster as usual at default of 3 (8-page reads); HughPC4 this same patch with page_cluster 4 (16-page reads); HughPC0 with page_cluster 0 (1-page reads: no readahead). HDD for swapping to harddisk, SSD for swapping to VertexII SSD. Seq for sequential access to the mapping, cycling five times around; Rand for the same number of random touches. Anon for a MAP_PRIVATE anon mapping; Shmem for a MAP_SHARED anon mapping, equivalent to tmpfs. One weakness of Shaohua's vma/anon_vma approach was that it did not optimize Shmem: seen below. Konstantin's approach was perhaps mistuned, 50% slower on Seq: did not compete and is not shown below. HDD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0 Seq Anon 73921 76210 75611 76904 78191 121542 Seq Shmem 73601 73176 73855 72947 74543 118322 Rand Anon 895392 831243 871569 845197 846496 841680 Rand Shmem 1058375 1053486 827935 764955 764376 756489 SSD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0 Seq Anon 24634 24198 24673 25107 21614 70018 Seq Shmem 24959 24932 25052 25703 22030 69678 Rand Anon 43014 26146 28075 25989 26935 25901 Rand Shmem 45349 45215 28249 24268 24138 24332 These tests are, of course, two extremes of a very simple case: under heavier mixed loads I've not yet observed any consistent improvement or degradation, and wider testing would be welcome. Shaohua Li: Test shows Vanilla is slightly better in sequential workload than Hugh's patch. I observed with Hugh's patch sometimes the readahead size is shrinked too fast (from 8 to 1 immediately) in sequential workload if there is no hit. And in such case, continuing doing readahead is good actually. I don't prepare a sophisticated algorithm for the sequential workload because so far we can't guarantee sequential accessed pages are swap out sequentially. So I slightly change Hugh's heuristic - don't shrink readahead size too fast. Here is my test result (unit second, 3 runs average): Vanilla Hugh New Seq 356 370 360 Random 4525 2447 2444 Attached graph is the swapin/swapout throughput I collected with 'vmstat 2'. The first part is running a random workload (till around 1200 of the x-axis) and the second part is running a sequential workload. swapin and swapout throughput are almost identical in steady state in both workloads. These are expected behavior. while in Vanilla, swapin is much bigger than swapout especially in random workload (because wrong readahead). Original patches by: Shaohua Li and Konstantin Khlebnikov. [fengguang.wu@intel.com: swapin_nr_pages() can be static] Signed-off-by: Hugh Dickins <hughd@google.com> Signed-off-by: Shaohua Li <shli@fusionio.com> Signed-off-by: Fengguang Wu <fengguang.wu@intel.com> Cc: Rik van Riel <riel@redhat.com> Cc: Wu Fengguang <fengguang.wu@intel.com> Cc: Minchan Kim <minchan@kernel.org> Cc: Konstantin Khlebnikov <khlebnikov@openvz.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2014-02-07 04:04:21 +08:00
unsigned long entry_offset = swp_offset(entry);
unsigned long offset = entry_offset;
unsigned long start_offset, end_offset;
swap: add a simple detector for inappropriate swapin readahead This is a patch to improve swap readahead algorithm. It's from Hugh and I slightly changed it. Hugh's original changelog: swapin readahead does a blind readahead, whether or not the swapin is sequential. This may be ok on harddisk, because large reads have relatively small costs, and if the readahead pages are unneeded they can be reclaimed easily - though, what if their allocation forced reclaim of useful pages? But on SSD devices large reads are more expensive than small ones: if the readahead pages are unneeded, reading them in caused significant overhead. This patch adds very simplistic random read detection. Stealing the PageReadahead technique from Konstantin Khlebnikov's patch, avoiding the vma/anon_vma sophistications of Shaohua Li's patch, swapin_nr_pages() simply looks at readahead's current success rate, and narrows or widens its readahead window accordingly. There is little science to its heuristic: it's about as stupid as can be whilst remaining effective. The table below shows elapsed times (in centiseconds) when running a single repetitive swapping load across a 1000MB mapping in 900MB ram with 1GB swap (the harddisk tests had taken painfully too long when I used mem=500M, but SSD shows similar results for that). Vanilla is the 3.6-rc7 kernel on which I started; Shaohua denotes his Sep 3 patch in mmotm and linux-next; HughOld denotes my Oct 1 patch which Shaohua showed to be defective; HughNew this Nov 14 patch, with page_cluster as usual at default of 3 (8-page reads); HughPC4 this same patch with page_cluster 4 (16-page reads); HughPC0 with page_cluster 0 (1-page reads: no readahead). HDD for swapping to harddisk, SSD for swapping to VertexII SSD. Seq for sequential access to the mapping, cycling five times around; Rand for the same number of random touches. Anon for a MAP_PRIVATE anon mapping; Shmem for a MAP_SHARED anon mapping, equivalent to tmpfs. One weakness of Shaohua's vma/anon_vma approach was that it did not optimize Shmem: seen below. Konstantin's approach was perhaps mistuned, 50% slower on Seq: did not compete and is not shown below. HDD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0 Seq Anon 73921 76210 75611 76904 78191 121542 Seq Shmem 73601 73176 73855 72947 74543 118322 Rand Anon 895392 831243 871569 845197 846496 841680 Rand Shmem 1058375 1053486 827935 764955 764376 756489 SSD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0 Seq Anon 24634 24198 24673 25107 21614 70018 Seq Shmem 24959 24932 25052 25703 22030 69678 Rand Anon 43014 26146 28075 25989 26935 25901 Rand Shmem 45349 45215 28249 24268 24138 24332 These tests are, of course, two extremes of a very simple case: under heavier mixed loads I've not yet observed any consistent improvement or degradation, and wider testing would be welcome. Shaohua Li: Test shows Vanilla is slightly better in sequential workload than Hugh's patch. I observed with Hugh's patch sometimes the readahead size is shrinked too fast (from 8 to 1 immediately) in sequential workload if there is no hit. And in such case, continuing doing readahead is good actually. I don't prepare a sophisticated algorithm for the sequential workload because so far we can't guarantee sequential accessed pages are swap out sequentially. So I slightly change Hugh's heuristic - don't shrink readahead size too fast. Here is my test result (unit second, 3 runs average): Vanilla Hugh New Seq 356 370 360 Random 4525 2447 2444 Attached graph is the swapin/swapout throughput I collected with 'vmstat 2'. The first part is running a random workload (till around 1200 of the x-axis) and the second part is running a sequential workload. swapin and swapout throughput are almost identical in steady state in both workloads. These are expected behavior. while in Vanilla, swapin is much bigger than swapout especially in random workload (because wrong readahead). Original patches by: Shaohua Li and Konstantin Khlebnikov. [fengguang.wu@intel.com: swapin_nr_pages() can be static] Signed-off-by: Hugh Dickins <hughd@google.com> Signed-off-by: Shaohua Li <shli@fusionio.com> Signed-off-by: Fengguang Wu <fengguang.wu@intel.com> Cc: Rik van Riel <riel@redhat.com> Cc: Wu Fengguang <fengguang.wu@intel.com> Cc: Minchan Kim <minchan@kernel.org> Cc: Konstantin Khlebnikov <khlebnikov@openvz.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2014-02-07 04:04:21 +08:00
unsigned long mask;
mm, swap: fix false error message in __swp_swapcount() When a page fault occurs for a swap entry, the physical swap readahead (not the VMA base swap readahead) may readahead several swap entries after the fault swap entry. The readahead algorithm calculates some of the swap entries to readahead via increasing the offset of the fault swap entry without checking whether they are beyond the end of the swap device and it relys on the __swp_swapcount() and swapcache_prepare() to check it. Although __swp_swapcount() checks for the swap entry passed in, it will complain with the error message as follow for the expected invalid swap entry. This may make the end users confused. swap_info_get: Bad swap offset entry 0200f8a7 To fix the false error message, the swap entry checking is added in swapin_readahead() to avoid to pass the out-of-bound swap entries and the swap entry reserved for the swap header to __swp_swapcount() and swapcache_prepare(). Link: http://lkml.kernel.org/r/20171102054225.22897-1-ying.huang@intel.com Fixes: e8c26ab60598 ("mm/swap: skip readahead for unreferenced swap slots") Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Reported-by: Christian Kujau <lists@nerdbynature.de> Acked-by: Minchan Kim <minchan@kernel.org> Suggested-by: Minchan Kim <minchan@kernel.org> Cc: Tim Chen <tim.c.chen@linux.intel.com> Cc: Michal Hocko <mhocko@suse.com> Cc: Hugh Dickins <hughd@google.com> Cc: <stable@vger.kernel.org> [4.11+] Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-11-16 09:33:15 +08:00
struct swap_info_struct *si = swp_swap_info(entry);
swap: allow swap readahead to be merged Swap readahead works fine, but the I/O to disk is almost always done in page size requests, despite the fact that readahead submits 1<<page-cluster pages at a time. On older kernels the old per device plugging behavior might have captured this and merged the requests, but currently all comes down to much more I/Os than required. On a single device this might not be an issue, but as soon as a server runs on shared san resources savin I/Os not only improves swapin throughput but also provides a lower resource utilization. With a load running KVM in a lot of memory overcommitment (the hot memory is 1.5 times the host memory) swapping throughput improves significantly and the lead feels more responsive as well as achieves more throughput. In a test setup with 16 swap disks running blocktrace on one of those disks shows the improved merging: Prior: Reads Queued: 560,888, 2,243MiB Writes Queued: 226,242, 904,968KiB Read Dispatches: 544,701, 2,243MiB Write Dispatches: 159,318, 904,968KiB Reads Requeued: 0 Writes Requeued: 0 Reads Completed: 544,716, 2,243MiB Writes Completed: 159,321, 904,980KiB Read Merges: 16,187, 64,748KiB Write Merges: 61,744, 246,976KiB IO unplugs: 149,614 Timer unplugs: 2,940 With the patch: Reads Queued: 734,315, 2,937MiB Writes Queued: 300,188, 1,200MiB Read Dispatches: 214,972, 2,937MiB Write Dispatches: 215,176, 1,200MiB Reads Requeued: 0 Writes Requeued: 0 Reads Completed: 214,971, 2,937MiB Writes Completed: 215,177, 1,200MiB Read Merges: 519,343, 2,077MiB Write Merges: 73,325, 293,300KiB IO unplugs: 337,130 Timer unplugs: 11,184 I got ~10% to ~40% more throughput in my cases and at the same time much lower cpu consumption when broken down per transferred kilobyte (the majority of that due to saved interrupts and better cache handling). In a shared SAN others might get an additional benefit as well, because this now causes less protocol overhead. Signed-off-by: Christian Ehrhardt <ehrhardt@linux.vnet.ibm.com> Acked-by: Rik van Riel <riel@redhat.com> Acked-by: Jens Axboe <axboe@kernel.dk> Reviewed-by: Minchan Kim <minchan@kernel.org> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2012-08-01 07:41:44 +08:00
struct blk_plug plug;
bool do_poll = true, page_allocated;
struct vm_area_struct *vma = vmf->vma;
unsigned long addr = vmf->address;
swap: add a simple detector for inappropriate swapin readahead This is a patch to improve swap readahead algorithm. It's from Hugh and I slightly changed it. Hugh's original changelog: swapin readahead does a blind readahead, whether or not the swapin is sequential. This may be ok on harddisk, because large reads have relatively small costs, and if the readahead pages are unneeded they can be reclaimed easily - though, what if their allocation forced reclaim of useful pages? But on SSD devices large reads are more expensive than small ones: if the readahead pages are unneeded, reading them in caused significant overhead. This patch adds very simplistic random read detection. Stealing the PageReadahead technique from Konstantin Khlebnikov's patch, avoiding the vma/anon_vma sophistications of Shaohua Li's patch, swapin_nr_pages() simply looks at readahead's current success rate, and narrows or widens its readahead window accordingly. There is little science to its heuristic: it's about as stupid as can be whilst remaining effective. The table below shows elapsed times (in centiseconds) when running a single repetitive swapping load across a 1000MB mapping in 900MB ram with 1GB swap (the harddisk tests had taken painfully too long when I used mem=500M, but SSD shows similar results for that). Vanilla is the 3.6-rc7 kernel on which I started; Shaohua denotes his Sep 3 patch in mmotm and linux-next; HughOld denotes my Oct 1 patch which Shaohua showed to be defective; HughNew this Nov 14 patch, with page_cluster as usual at default of 3 (8-page reads); HughPC4 this same patch with page_cluster 4 (16-page reads); HughPC0 with page_cluster 0 (1-page reads: no readahead). HDD for swapping to harddisk, SSD for swapping to VertexII SSD. Seq for sequential access to the mapping, cycling five times around; Rand for the same number of random touches. Anon for a MAP_PRIVATE anon mapping; Shmem for a MAP_SHARED anon mapping, equivalent to tmpfs. One weakness of Shaohua's vma/anon_vma approach was that it did not optimize Shmem: seen below. Konstantin's approach was perhaps mistuned, 50% slower on Seq: did not compete and is not shown below. HDD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0 Seq Anon 73921 76210 75611 76904 78191 121542 Seq Shmem 73601 73176 73855 72947 74543 118322 Rand Anon 895392 831243 871569 845197 846496 841680 Rand Shmem 1058375 1053486 827935 764955 764376 756489 SSD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0 Seq Anon 24634 24198 24673 25107 21614 70018 Seq Shmem 24959 24932 25052 25703 22030 69678 Rand Anon 43014 26146 28075 25989 26935 25901 Rand Shmem 45349 45215 28249 24268 24138 24332 These tests are, of course, two extremes of a very simple case: under heavier mixed loads I've not yet observed any consistent improvement or degradation, and wider testing would be welcome. Shaohua Li: Test shows Vanilla is slightly better in sequential workload than Hugh's patch. I observed with Hugh's patch sometimes the readahead size is shrinked too fast (from 8 to 1 immediately) in sequential workload if there is no hit. And in such case, continuing doing readahead is good actually. I don't prepare a sophisticated algorithm for the sequential workload because so far we can't guarantee sequential accessed pages are swap out sequentially. So I slightly change Hugh's heuristic - don't shrink readahead size too fast. Here is my test result (unit second, 3 runs average): Vanilla Hugh New Seq 356 370 360 Random 4525 2447 2444 Attached graph is the swapin/swapout throughput I collected with 'vmstat 2'. The first part is running a random workload (till around 1200 of the x-axis) and the second part is running a sequential workload. swapin and swapout throughput are almost identical in steady state in both workloads. These are expected behavior. while in Vanilla, swapin is much bigger than swapout especially in random workload (because wrong readahead). Original patches by: Shaohua Li and Konstantin Khlebnikov. [fengguang.wu@intel.com: swapin_nr_pages() can be static] Signed-off-by: Hugh Dickins <hughd@google.com> Signed-off-by: Shaohua Li <shli@fusionio.com> Signed-off-by: Fengguang Wu <fengguang.wu@intel.com> Cc: Rik van Riel <riel@redhat.com> Cc: Wu Fengguang <fengguang.wu@intel.com> Cc: Minchan Kim <minchan@kernel.org> Cc: Konstantin Khlebnikov <khlebnikov@openvz.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2014-02-07 04:04:21 +08:00
mask = swapin_nr_pages(offset) - 1;
if (!mask)
goto skip;
swap: add block io poll in swapin path For fast flash disk, async IO could introduce overhead because of context switch. block-mq now supports IO poll, which improves performance and latency a lot. swapin is a good place to use this technique, because the task is waiting for the swapin page to continue execution. In my virtual machine, directly read 4k data from a NVMe with iopoll is about 60% better than that without poll. With iopoll support in swapin patch, my microbenchmark (a task does random memory write) is about 10%~25% faster. CPU utilization increases a lot though, 2x and even 3x CPU utilization. This will depend on disk speed. While iopoll in swapin isn't intended for all usage cases, it's a win for latency sensistive workloads with high speed swap disk. block layer has knob to control poll in runtime. If poll isn't enabled in block layer, there should be no noticeable change in swapin. I got a chance to run the same test in a NVMe with DRAM as the media. In simple fio IO test, blkpoll boosts 50% performance in single thread test and ~20% in 8 threads test. So this is the base line. In above swap test, blkpoll boosts ~27% performance in single thread test. blkpoll uses 2x CPU time though. If we enable hybid polling, the performance gain has very slight drop but CPU time is only 50% worse than that without blkpoll. Also we can adjust parameter of hybid poll, with it, the CPU time penality is reduced further. In 8 threads test, blkpoll doesn't help though. The performance is similar to that without blkpoll, but cpu utilization is similar too. There is lock contention in swap path. The cpu time spending on blkpoll isn't high. So overall, blkpoll swapin isn't worse than that without it. The swapin readahead might read several pages in in the same time and form a big IO request. Since the IO will take longer time, it doesn't make sense to do poll, so the patch only does iopoll for single page swapin. [akpm@linux-foundation.org: coding-style fixes] Link: http://lkml.kernel.org/r/070c3c3e40b711e7b1390002c991e86a-b5408f0@7511894063d3764ff01ea8111f5a004d7dd700ed078797c204a24e620ddb965c Signed-off-by: Shaohua Li <shli@fb.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Huang Ying <ying.huang@intel.com> Cc: Jens Axboe <axboe@fb.com> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-11 06:47:11 +08:00
do_poll = false;
/* Read a page_cluster sized and aligned cluster around offset. */
start_offset = offset & ~mask;
end_offset = offset | mask;
if (!start_offset) /* First page is swap header. */
start_offset++;
mm, swap: fix false error message in __swp_swapcount() When a page fault occurs for a swap entry, the physical swap readahead (not the VMA base swap readahead) may readahead several swap entries after the fault swap entry. The readahead algorithm calculates some of the swap entries to readahead via increasing the offset of the fault swap entry without checking whether they are beyond the end of the swap device and it relys on the __swp_swapcount() and swapcache_prepare() to check it. Although __swp_swapcount() checks for the swap entry passed in, it will complain with the error message as follow for the expected invalid swap entry. This may make the end users confused. swap_info_get: Bad swap offset entry 0200f8a7 To fix the false error message, the swap entry checking is added in swapin_readahead() to avoid to pass the out-of-bound swap entries and the swap entry reserved for the swap header to __swp_swapcount() and swapcache_prepare(). Link: http://lkml.kernel.org/r/20171102054225.22897-1-ying.huang@intel.com Fixes: e8c26ab60598 ("mm/swap: skip readahead for unreferenced swap slots") Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Reported-by: Christian Kujau <lists@nerdbynature.de> Acked-by: Minchan Kim <minchan@kernel.org> Suggested-by: Minchan Kim <minchan@kernel.org> Cc: Tim Chen <tim.c.chen@linux.intel.com> Cc: Michal Hocko <mhocko@suse.com> Cc: Hugh Dickins <hughd@google.com> Cc: <stable@vger.kernel.org> [4.11+] Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-11-16 09:33:15 +08:00
if (end_offset >= si->max)
end_offset = si->max - 1;
swap: allow swap readahead to be merged Swap readahead works fine, but the I/O to disk is almost always done in page size requests, despite the fact that readahead submits 1<<page-cluster pages at a time. On older kernels the old per device plugging behavior might have captured this and merged the requests, but currently all comes down to much more I/Os than required. On a single device this might not be an issue, but as soon as a server runs on shared san resources savin I/Os not only improves swapin throughput but also provides a lower resource utilization. With a load running KVM in a lot of memory overcommitment (the hot memory is 1.5 times the host memory) swapping throughput improves significantly and the lead feels more responsive as well as achieves more throughput. In a test setup with 16 swap disks running blocktrace on one of those disks shows the improved merging: Prior: Reads Queued: 560,888, 2,243MiB Writes Queued: 226,242, 904,968KiB Read Dispatches: 544,701, 2,243MiB Write Dispatches: 159,318, 904,968KiB Reads Requeued: 0 Writes Requeued: 0 Reads Completed: 544,716, 2,243MiB Writes Completed: 159,321, 904,980KiB Read Merges: 16,187, 64,748KiB Write Merges: 61,744, 246,976KiB IO unplugs: 149,614 Timer unplugs: 2,940 With the patch: Reads Queued: 734,315, 2,937MiB Writes Queued: 300,188, 1,200MiB Read Dispatches: 214,972, 2,937MiB Write Dispatches: 215,176, 1,200MiB Reads Requeued: 0 Writes Requeued: 0 Reads Completed: 214,971, 2,937MiB Writes Completed: 215,177, 1,200MiB Read Merges: 519,343, 2,077MiB Write Merges: 73,325, 293,300KiB IO unplugs: 337,130 Timer unplugs: 11,184 I got ~10% to ~40% more throughput in my cases and at the same time much lower cpu consumption when broken down per transferred kilobyte (the majority of that due to saved interrupts and better cache handling). In a shared SAN others might get an additional benefit as well, because this now causes less protocol overhead. Signed-off-by: Christian Ehrhardt <ehrhardt@linux.vnet.ibm.com> Acked-by: Rik van Riel <riel@redhat.com> Acked-by: Jens Axboe <axboe@kernel.dk> Reviewed-by: Minchan Kim <minchan@kernel.org> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2012-08-01 07:41:44 +08:00
blk_start_plug(&plug);
for (offset = start_offset; offset <= end_offset ; offset++) {
/* Ok, do the async read-ahead now */
page = __read_swap_cache_async(
swp_entry(swp_type(entry), offset),
gfp_mask, vma, addr, &page_allocated);
if (!page)
continue;
if (page_allocated) {
swap_readpage(page, false);
if (offset != entry_offset) {
SetPageReadahead(page);
count_vm_event(SWAP_RA);
}
mm, swap: add swap readahead hit statistics Patch series "mm, swap: VMA based swap readahead", v4. The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory space. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patchset, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. In addition to the swap readahead changes, some new sysfs interface is added to show the efficiency of the readahead algorithm and some other swap statistics. This new implementation will incur more small random read, on SSD, the improved correctness of estimation and readahead target should beat the potential increased overhead, this is also illustrated in the test results below. But on HDD, the overhead may beat the benefit, so the original implementation will be used by default. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. This patch (of 5): The statistics for total readahead pages and total readahead hits are recorded and exported via the following sysfs interface. /sys/kernel/mm/swap/ra_hits /sys/kernel/mm/swap/ra_total With them, the efficiency of the swap readahead could be measured, so that the swap readahead algorithm and parameters could be tuned accordingly. [akpm@linux-foundation.org: don't display swap stats if CONFIG_SWAP=n] Link: http://lkml.kernel.org/r/20170807054038.1843-2-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:29 +08:00
}
mm, fs: get rid of PAGE_CACHE_* and page_cache_{get,release} macros PAGE_CACHE_{SIZE,SHIFT,MASK,ALIGN} macros were introduced *long* time ago with promise that one day it will be possible to implement page cache with bigger chunks than PAGE_SIZE. This promise never materialized. And unlikely will. We have many places where PAGE_CACHE_SIZE assumed to be equal to PAGE_SIZE. And it's constant source of confusion on whether PAGE_CACHE_* or PAGE_* constant should be used in a particular case, especially on the border between fs and mm. Global switching to PAGE_CACHE_SIZE != PAGE_SIZE would cause to much breakage to be doable. Let's stop pretending that pages in page cache are special. They are not. The changes are pretty straight-forward: - <foo> << (PAGE_CACHE_SHIFT - PAGE_SHIFT) -> <foo>; - <foo> >> (PAGE_CACHE_SHIFT - PAGE_SHIFT) -> <foo>; - PAGE_CACHE_{SIZE,SHIFT,MASK,ALIGN} -> PAGE_{SIZE,SHIFT,MASK,ALIGN}; - page_cache_get() -> get_page(); - page_cache_release() -> put_page(); This patch contains automated changes generated with coccinelle using script below. For some reason, coccinelle doesn't patch header files. I've called spatch for them manually. The only adjustment after coccinelle is revert of changes to PAGE_CAHCE_ALIGN definition: we are going to drop it later. There are few places in the code where coccinelle didn't reach. I'll fix them manually in a separate patch. Comments and documentation also will be addressed with the separate patch. virtual patch @@ expression E; @@ - E << (PAGE_CACHE_SHIFT - PAGE_SHIFT) + E @@ expression E; @@ - E >> (PAGE_CACHE_SHIFT - PAGE_SHIFT) + E @@ @@ - PAGE_CACHE_SHIFT + PAGE_SHIFT @@ @@ - PAGE_CACHE_SIZE + PAGE_SIZE @@ @@ - PAGE_CACHE_MASK + PAGE_MASK @@ expression E; @@ - PAGE_CACHE_ALIGN(E) + PAGE_ALIGN(E) @@ expression E; @@ - page_cache_get(E) + get_page(E) @@ expression E; @@ - page_cache_release(E) + put_page(E) Signed-off-by: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> Acked-by: Michal Hocko <mhocko@suse.com> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2016-04-01 20:29:47 +08:00
put_page(page);
}
swap: allow swap readahead to be merged Swap readahead works fine, but the I/O to disk is almost always done in page size requests, despite the fact that readahead submits 1<<page-cluster pages at a time. On older kernels the old per device plugging behavior might have captured this and merged the requests, but currently all comes down to much more I/Os than required. On a single device this might not be an issue, but as soon as a server runs on shared san resources savin I/Os not only improves swapin throughput but also provides a lower resource utilization. With a load running KVM in a lot of memory overcommitment (the hot memory is 1.5 times the host memory) swapping throughput improves significantly and the lead feels more responsive as well as achieves more throughput. In a test setup with 16 swap disks running blocktrace on one of those disks shows the improved merging: Prior: Reads Queued: 560,888, 2,243MiB Writes Queued: 226,242, 904,968KiB Read Dispatches: 544,701, 2,243MiB Write Dispatches: 159,318, 904,968KiB Reads Requeued: 0 Writes Requeued: 0 Reads Completed: 544,716, 2,243MiB Writes Completed: 159,321, 904,980KiB Read Merges: 16,187, 64,748KiB Write Merges: 61,744, 246,976KiB IO unplugs: 149,614 Timer unplugs: 2,940 With the patch: Reads Queued: 734,315, 2,937MiB Writes Queued: 300,188, 1,200MiB Read Dispatches: 214,972, 2,937MiB Write Dispatches: 215,176, 1,200MiB Reads Requeued: 0 Writes Requeued: 0 Reads Completed: 214,971, 2,937MiB Writes Completed: 215,177, 1,200MiB Read Merges: 519,343, 2,077MiB Write Merges: 73,325, 293,300KiB IO unplugs: 337,130 Timer unplugs: 11,184 I got ~10% to ~40% more throughput in my cases and at the same time much lower cpu consumption when broken down per transferred kilobyte (the majority of that due to saved interrupts and better cache handling). In a shared SAN others might get an additional benefit as well, because this now causes less protocol overhead. Signed-off-by: Christian Ehrhardt <ehrhardt@linux.vnet.ibm.com> Acked-by: Rik van Riel <riel@redhat.com> Acked-by: Jens Axboe <axboe@kernel.dk> Reviewed-by: Minchan Kim <minchan@kernel.org> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2012-08-01 07:41:44 +08:00
blk_finish_plug(&plug);
lru_add_drain(); /* Push any new pages onto the LRU now */
swap: add a simple detector for inappropriate swapin readahead This is a patch to improve swap readahead algorithm. It's from Hugh and I slightly changed it. Hugh's original changelog: swapin readahead does a blind readahead, whether or not the swapin is sequential. This may be ok on harddisk, because large reads have relatively small costs, and if the readahead pages are unneeded they can be reclaimed easily - though, what if their allocation forced reclaim of useful pages? But on SSD devices large reads are more expensive than small ones: if the readahead pages are unneeded, reading them in caused significant overhead. This patch adds very simplistic random read detection. Stealing the PageReadahead technique from Konstantin Khlebnikov's patch, avoiding the vma/anon_vma sophistications of Shaohua Li's patch, swapin_nr_pages() simply looks at readahead's current success rate, and narrows or widens its readahead window accordingly. There is little science to its heuristic: it's about as stupid as can be whilst remaining effective. The table below shows elapsed times (in centiseconds) when running a single repetitive swapping load across a 1000MB mapping in 900MB ram with 1GB swap (the harddisk tests had taken painfully too long when I used mem=500M, but SSD shows similar results for that). Vanilla is the 3.6-rc7 kernel on which I started; Shaohua denotes his Sep 3 patch in mmotm and linux-next; HughOld denotes my Oct 1 patch which Shaohua showed to be defective; HughNew this Nov 14 patch, with page_cluster as usual at default of 3 (8-page reads); HughPC4 this same patch with page_cluster 4 (16-page reads); HughPC0 with page_cluster 0 (1-page reads: no readahead). HDD for swapping to harddisk, SSD for swapping to VertexII SSD. Seq for sequential access to the mapping, cycling five times around; Rand for the same number of random touches. Anon for a MAP_PRIVATE anon mapping; Shmem for a MAP_SHARED anon mapping, equivalent to tmpfs. One weakness of Shaohua's vma/anon_vma approach was that it did not optimize Shmem: seen below. Konstantin's approach was perhaps mistuned, 50% slower on Seq: did not compete and is not shown below. HDD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0 Seq Anon 73921 76210 75611 76904 78191 121542 Seq Shmem 73601 73176 73855 72947 74543 118322 Rand Anon 895392 831243 871569 845197 846496 841680 Rand Shmem 1058375 1053486 827935 764955 764376 756489 SSD Vanilla Shaohua HughOld HughNew HughPC4 HughPC0 Seq Anon 24634 24198 24673 25107 21614 70018 Seq Shmem 24959 24932 25052 25703 22030 69678 Rand Anon 43014 26146 28075 25989 26935 25901 Rand Shmem 45349 45215 28249 24268 24138 24332 These tests are, of course, two extremes of a very simple case: under heavier mixed loads I've not yet observed any consistent improvement or degradation, and wider testing would be welcome. Shaohua Li: Test shows Vanilla is slightly better in sequential workload than Hugh's patch. I observed with Hugh's patch sometimes the readahead size is shrinked too fast (from 8 to 1 immediately) in sequential workload if there is no hit. And in such case, continuing doing readahead is good actually. I don't prepare a sophisticated algorithm for the sequential workload because so far we can't guarantee sequential accessed pages are swap out sequentially. So I slightly change Hugh's heuristic - don't shrink readahead size too fast. Here is my test result (unit second, 3 runs average): Vanilla Hugh New Seq 356 370 360 Random 4525 2447 2444 Attached graph is the swapin/swapout throughput I collected with 'vmstat 2'. The first part is running a random workload (till around 1200 of the x-axis) and the second part is running a sequential workload. swapin and swapout throughput are almost identical in steady state in both workloads. These are expected behavior. while in Vanilla, swapin is much bigger than swapout especially in random workload (because wrong readahead). Original patches by: Shaohua Li and Konstantin Khlebnikov. [fengguang.wu@intel.com: swapin_nr_pages() can be static] Signed-off-by: Hugh Dickins <hughd@google.com> Signed-off-by: Shaohua Li <shli@fusionio.com> Signed-off-by: Fengguang Wu <fengguang.wu@intel.com> Cc: Rik van Riel <riel@redhat.com> Cc: Wu Fengguang <fengguang.wu@intel.com> Cc: Minchan Kim <minchan@kernel.org> Cc: Konstantin Khlebnikov <khlebnikov@openvz.org> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2014-02-07 04:04:21 +08:00
skip:
swap: add block io poll in swapin path For fast flash disk, async IO could introduce overhead because of context switch. block-mq now supports IO poll, which improves performance and latency a lot. swapin is a good place to use this technique, because the task is waiting for the swapin page to continue execution. In my virtual machine, directly read 4k data from a NVMe with iopoll is about 60% better than that without poll. With iopoll support in swapin patch, my microbenchmark (a task does random memory write) is about 10%~25% faster. CPU utilization increases a lot though, 2x and even 3x CPU utilization. This will depend on disk speed. While iopoll in swapin isn't intended for all usage cases, it's a win for latency sensistive workloads with high speed swap disk. block layer has knob to control poll in runtime. If poll isn't enabled in block layer, there should be no noticeable change in swapin. I got a chance to run the same test in a NVMe with DRAM as the media. In simple fio IO test, blkpoll boosts 50% performance in single thread test and ~20% in 8 threads test. So this is the base line. In above swap test, blkpoll boosts ~27% performance in single thread test. blkpoll uses 2x CPU time though. If we enable hybid polling, the performance gain has very slight drop but CPU time is only 50% worse than that without blkpoll. Also we can adjust parameter of hybid poll, with it, the CPU time penality is reduced further. In 8 threads test, blkpoll doesn't help though. The performance is similar to that without blkpoll, but cpu utilization is similar too. There is lock contention in swap path. The cpu time spending on blkpoll isn't high. So overall, blkpoll swapin isn't worse than that without it. The swapin readahead might read several pages in in the same time and form a big IO request. Since the IO will take longer time, it doesn't make sense to do poll, so the patch only does iopoll for single page swapin. [akpm@linux-foundation.org: coding-style fixes] Link: http://lkml.kernel.org/r/070c3c3e40b711e7b1390002c991e86a-b5408f0@7511894063d3764ff01ea8111f5a004d7dd700ed078797c204a24e620ddb965c Signed-off-by: Shaohua Li <shli@fb.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Huang Ying <ying.huang@intel.com> Cc: Jens Axboe <axboe@fb.com> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-07-11 06:47:11 +08:00
return read_swap_cache_async(entry, gfp_mask, vma, addr, do_poll);
}
mm/swap: split swap cache into 64MB trunks The patch is to improve the scalability of the swap out/in via using fine grained locks for the swap cache. In current kernel, one address space will be used for each swap device. And in the common configuration, the number of the swap device is very small (one is typical). This causes the heavy lock contention on the radix tree of the address space if multiple tasks swap out/in concurrently. But in fact, there is no dependency between pages in the swap cache. So that, we can split the one shared address space for each swap device into several address spaces to reduce the lock contention. In the patch, the shared address space is split into 64MB trunks. 64MB is chosen to balance the memory space usage and effect of lock contention reduction. The size of struct address_space on x86_64 architecture is 408B, so with the patch, 6528B more memory will be used for every 1GB swap space on x86_64 architecture. One address space is still shared for the swap entries in the same 64M trunks. To avoid lock contention for the first round of swap space allocation, the order of the swap clusters in the initial free clusters list is changed. The swap space distance between the consecutive swap clusters in the free cluster list is at least 64M. After the first round of allocation, the swap clusters are expected to be freed randomly, so the lock contention should be reduced effectively. Link: http://lkml.kernel.org/r/735bab895e64c930581ffb0a05b661e01da82bc5.1484082593.git.tim.c.chen@linux.intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Signed-off-by: Tim Chen <tim.c.chen@linux.intel.com> Cc: Aaron Lu <aaron.lu@intel.com> Cc: Andi Kleen <ak@linux.intel.com> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Christian Borntraeger <borntraeger@de.ibm.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Hillf Danton <hillf.zj@alibaba-inc.com> Cc: Huang Ying <ying.huang@intel.com> Cc: Hugh Dickins <hughd@google.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Corbet <corbet@lwn.net> escreveu: Cc: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Vladimir Davydov <vdavydov.dev@gmail.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-02-23 07:45:26 +08:00
int init_swap_address_space(unsigned int type, unsigned long nr_pages)
{
struct address_space *spaces, *space;
unsigned int i, nr;
nr = DIV_ROUND_UP(nr_pages, SWAP_ADDRESS_SPACE_PAGES);
treewide: kvzalloc() -> kvcalloc() The kvzalloc() function has a 2-factor argument form, kvcalloc(). This patch replaces cases of: kvzalloc(a * b, gfp) with: kvcalloc(a * b, gfp) as well as handling cases of: kvzalloc(a * b * c, gfp) with: kvzalloc(array3_size(a, b, c), gfp) as it's slightly less ugly than: kvcalloc(array_size(a, b), c, gfp) This does, however, attempt to ignore constant size factors like: kvzalloc(4 * 1024, gfp) though any constants defined via macros get caught up in the conversion. Any factors with a sizeof() of "unsigned char", "char", and "u8" were dropped, since they're redundant. The Coccinelle script used for this was: // Fix redundant parens around sizeof(). @@ type TYPE; expression THING, E; @@ ( kvzalloc( - (sizeof(TYPE)) * E + sizeof(TYPE) * E , ...) | kvzalloc( - (sizeof(THING)) * E + sizeof(THING) * E , ...) ) // Drop single-byte sizes and redundant parens. @@ expression COUNT; typedef u8; typedef __u8; @@ ( kvzalloc( - sizeof(u8) * (COUNT) + COUNT , ...) | kvzalloc( - sizeof(__u8) * (COUNT) + COUNT , ...) | kvzalloc( - sizeof(char) * (COUNT) + COUNT , ...) | kvzalloc( - sizeof(unsigned char) * (COUNT) + COUNT , ...) | kvzalloc( - sizeof(u8) * COUNT + COUNT , ...) | kvzalloc( - sizeof(__u8) * COUNT + COUNT , ...) | kvzalloc( - sizeof(char) * COUNT + COUNT , ...) | kvzalloc( - sizeof(unsigned char) * COUNT + COUNT , ...) ) // 2-factor product with sizeof(type/expression) and identifier or constant. @@ type TYPE; expression THING; identifier COUNT_ID; constant COUNT_CONST; @@ ( - kvzalloc + kvcalloc ( - sizeof(TYPE) * (COUNT_ID) + COUNT_ID, sizeof(TYPE) , ...) | - kvzalloc + kvcalloc ( - sizeof(TYPE) * COUNT_ID + COUNT_ID, sizeof(TYPE) , ...) | - kvzalloc + kvcalloc ( - sizeof(TYPE) * (COUNT_CONST) + COUNT_CONST, sizeof(TYPE) , ...) | - kvzalloc + kvcalloc ( - sizeof(TYPE) * COUNT_CONST + COUNT_CONST, sizeof(TYPE) , ...) | - kvzalloc + kvcalloc ( - sizeof(THING) * (COUNT_ID) + COUNT_ID, sizeof(THING) , ...) | - kvzalloc + kvcalloc ( - sizeof(THING) * COUNT_ID + COUNT_ID, sizeof(THING) , ...) | - kvzalloc + kvcalloc ( - sizeof(THING) * (COUNT_CONST) + COUNT_CONST, sizeof(THING) , ...) | - kvzalloc + kvcalloc ( - sizeof(THING) * COUNT_CONST + COUNT_CONST, sizeof(THING) , ...) ) // 2-factor product, only identifiers. @@ identifier SIZE, COUNT; @@ - kvzalloc + kvcalloc ( - SIZE * COUNT + COUNT, SIZE , ...) // 3-factor product with 1 sizeof(type) or sizeof(expression), with // redundant parens removed. @@ expression THING; identifier STRIDE, COUNT; type TYPE; @@ ( kvzalloc( - sizeof(TYPE) * (COUNT) * (STRIDE) + array3_size(COUNT, STRIDE, sizeof(TYPE)) , ...) | kvzalloc( - sizeof(TYPE) * (COUNT) * STRIDE + array3_size(COUNT, STRIDE, sizeof(TYPE)) , ...) | kvzalloc( - sizeof(TYPE) * COUNT * (STRIDE) + array3_size(COUNT, STRIDE, sizeof(TYPE)) , ...) | kvzalloc( - sizeof(TYPE) * COUNT * STRIDE + array3_size(COUNT, STRIDE, sizeof(TYPE)) , ...) | kvzalloc( - sizeof(THING) * (COUNT) * (STRIDE) + array3_size(COUNT, STRIDE, sizeof(THING)) , ...) | kvzalloc( - sizeof(THING) * (COUNT) * STRIDE + array3_size(COUNT, STRIDE, sizeof(THING)) , ...) | kvzalloc( - sizeof(THING) * COUNT * (STRIDE) + array3_size(COUNT, STRIDE, sizeof(THING)) , ...) | kvzalloc( - sizeof(THING) * COUNT * STRIDE + array3_size(COUNT, STRIDE, sizeof(THING)) , ...) ) // 3-factor product with 2 sizeof(variable), with redundant parens removed. @@ expression THING1, THING2; identifier COUNT; type TYPE1, TYPE2; @@ ( kvzalloc( - sizeof(TYPE1) * sizeof(TYPE2) * COUNT + array3_size(COUNT, sizeof(TYPE1), sizeof(TYPE2)) , ...) | kvzalloc( - sizeof(TYPE1) * sizeof(THING2) * (COUNT) + array3_size(COUNT, sizeof(TYPE1), sizeof(TYPE2)) , ...) | kvzalloc( - sizeof(THING1) * sizeof(THING2) * COUNT + array3_size(COUNT, sizeof(THING1), sizeof(THING2)) , ...) | kvzalloc( - sizeof(THING1) * sizeof(THING2) * (COUNT) + array3_size(COUNT, sizeof(THING1), sizeof(THING2)) , ...) | kvzalloc( - sizeof(TYPE1) * sizeof(THING2) * COUNT + array3_size(COUNT, sizeof(TYPE1), sizeof(THING2)) , ...) | kvzalloc( - sizeof(TYPE1) * sizeof(THING2) * (COUNT) + array3_size(COUNT, sizeof(TYPE1), sizeof(THING2)) , ...) ) // 3-factor product, only identifiers, with redundant parens removed. @@ identifier STRIDE, SIZE, COUNT; @@ ( kvzalloc( - (COUNT) * STRIDE * SIZE + array3_size(COUNT, STRIDE, SIZE) , ...) | kvzalloc( - COUNT * (STRIDE) * SIZE + array3_size(COUNT, STRIDE, SIZE) , ...) | kvzalloc( - COUNT * STRIDE * (SIZE) + array3_size(COUNT, STRIDE, SIZE) , ...) | kvzalloc( - (COUNT) * (STRIDE) * SIZE + array3_size(COUNT, STRIDE, SIZE) , ...) | kvzalloc( - COUNT * (STRIDE) * (SIZE) + array3_size(COUNT, STRIDE, SIZE) , ...) | kvzalloc( - (COUNT) * STRIDE * (SIZE) + array3_size(COUNT, STRIDE, SIZE) , ...) | kvzalloc( - (COUNT) * (STRIDE) * (SIZE) + array3_size(COUNT, STRIDE, SIZE) , ...) | kvzalloc( - COUNT * STRIDE * SIZE + array3_size(COUNT, STRIDE, SIZE) , ...) ) // Any remaining multi-factor products, first at least 3-factor products, // when they're not all constants... @@ expression E1, E2, E3; constant C1, C2, C3; @@ ( kvzalloc(C1 * C2 * C3, ...) | kvzalloc( - (E1) * E2 * E3 + array3_size(E1, E2, E3) , ...) | kvzalloc( - (E1) * (E2) * E3 + array3_size(E1, E2, E3) , ...) | kvzalloc( - (E1) * (E2) * (E3) + array3_size(E1, E2, E3) , ...) | kvzalloc( - E1 * E2 * E3 + array3_size(E1, E2, E3) , ...) ) // And then all remaining 2 factors products when they're not all constants, // keeping sizeof() as the second factor argument. @@ expression THING, E1, E2; type TYPE; constant C1, C2, C3; @@ ( kvzalloc(sizeof(THING) * C2, ...) | kvzalloc(sizeof(TYPE) * C2, ...) | kvzalloc(C1 * C2 * C3, ...) | kvzalloc(C1 * C2, ...) | - kvzalloc + kvcalloc ( - sizeof(TYPE) * (E2) + E2, sizeof(TYPE) , ...) | - kvzalloc + kvcalloc ( - sizeof(TYPE) * E2 + E2, sizeof(TYPE) , ...) | - kvzalloc + kvcalloc ( - sizeof(THING) * (E2) + E2, sizeof(THING) , ...) | - kvzalloc + kvcalloc ( - sizeof(THING) * E2 + E2, sizeof(THING) , ...) | - kvzalloc + kvcalloc ( - (E1) * E2 + E1, E2 , ...) | - kvzalloc + kvcalloc ( - (E1) * (E2) + E1, E2 , ...) | - kvzalloc + kvcalloc ( - E1 * E2 + E1, E2 , ...) ) Signed-off-by: Kees Cook <keescook@chromium.org>
2018-06-13 05:04:48 +08:00
spaces = kvcalloc(nr, sizeof(struct address_space), GFP_KERNEL);
mm/swap: split swap cache into 64MB trunks The patch is to improve the scalability of the swap out/in via using fine grained locks for the swap cache. In current kernel, one address space will be used for each swap device. And in the common configuration, the number of the swap device is very small (one is typical). This causes the heavy lock contention on the radix tree of the address space if multiple tasks swap out/in concurrently. But in fact, there is no dependency between pages in the swap cache. So that, we can split the one shared address space for each swap device into several address spaces to reduce the lock contention. In the patch, the shared address space is split into 64MB trunks. 64MB is chosen to balance the memory space usage and effect of lock contention reduction. The size of struct address_space on x86_64 architecture is 408B, so with the patch, 6528B more memory will be used for every 1GB swap space on x86_64 architecture. One address space is still shared for the swap entries in the same 64M trunks. To avoid lock contention for the first round of swap space allocation, the order of the swap clusters in the initial free clusters list is changed. The swap space distance between the consecutive swap clusters in the free cluster list is at least 64M. After the first round of allocation, the swap clusters are expected to be freed randomly, so the lock contention should be reduced effectively. Link: http://lkml.kernel.org/r/735bab895e64c930581ffb0a05b661e01da82bc5.1484082593.git.tim.c.chen@linux.intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Signed-off-by: Tim Chen <tim.c.chen@linux.intel.com> Cc: Aaron Lu <aaron.lu@intel.com> Cc: Andi Kleen <ak@linux.intel.com> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Christian Borntraeger <borntraeger@de.ibm.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Hillf Danton <hillf.zj@alibaba-inc.com> Cc: Huang Ying <ying.huang@intel.com> Cc: Hugh Dickins <hughd@google.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Corbet <corbet@lwn.net> escreveu: Cc: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Vladimir Davydov <vdavydov.dev@gmail.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-02-23 07:45:26 +08:00
if (!spaces)
return -ENOMEM;
for (i = 0; i < nr; i++) {
space = spaces + i;
xa_init_flags(&space->i_pages, XA_FLAGS_LOCK_IRQ);
mm/swap: split swap cache into 64MB trunks The patch is to improve the scalability of the swap out/in via using fine grained locks for the swap cache. In current kernel, one address space will be used for each swap device. And in the common configuration, the number of the swap device is very small (one is typical). This causes the heavy lock contention on the radix tree of the address space if multiple tasks swap out/in concurrently. But in fact, there is no dependency between pages in the swap cache. So that, we can split the one shared address space for each swap device into several address spaces to reduce the lock contention. In the patch, the shared address space is split into 64MB trunks. 64MB is chosen to balance the memory space usage and effect of lock contention reduction. The size of struct address_space on x86_64 architecture is 408B, so with the patch, 6528B more memory will be used for every 1GB swap space on x86_64 architecture. One address space is still shared for the swap entries in the same 64M trunks. To avoid lock contention for the first round of swap space allocation, the order of the swap clusters in the initial free clusters list is changed. The swap space distance between the consecutive swap clusters in the free cluster list is at least 64M. After the first round of allocation, the swap clusters are expected to be freed randomly, so the lock contention should be reduced effectively. Link: http://lkml.kernel.org/r/735bab895e64c930581ffb0a05b661e01da82bc5.1484082593.git.tim.c.chen@linux.intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Signed-off-by: Tim Chen <tim.c.chen@linux.intel.com> Cc: Aaron Lu <aaron.lu@intel.com> Cc: Andi Kleen <ak@linux.intel.com> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Christian Borntraeger <borntraeger@de.ibm.com> Cc: Dave Hansen <dave.hansen@intel.com> Cc: Hillf Danton <hillf.zj@alibaba-inc.com> Cc: Huang Ying <ying.huang@intel.com> Cc: Hugh Dickins <hughd@google.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Jonathan Corbet <corbet@lwn.net> escreveu: Cc: Kirill A. Shutemov <kirill.shutemov@linux.intel.com> Cc: Michal Hocko <mhocko@kernel.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Vladimir Davydov <vdavydov.dev@gmail.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-02-23 07:45:26 +08:00
atomic_set(&space->i_mmap_writable, 0);
space->a_ops = &swap_aops;
/* swap cache doesn't use writeback related tags */
mapping_set_no_writeback_tags(space);
}
nr_swapper_spaces[type] = nr;
rcu_assign_pointer(swapper_spaces[type], spaces);
return 0;
}
void exit_swap_address_space(unsigned int type)
{
struct address_space *spaces;
spaces = swapper_spaces[type];
nr_swapper_spaces[type] = 0;
rcu_assign_pointer(swapper_spaces[type], NULL);
synchronize_rcu();
kvfree(spaces);
}
mm, swap: VMA based swap readahead The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patch, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:36 +08:00
static inline void swap_ra_clamp_pfn(struct vm_area_struct *vma,
unsigned long faddr,
unsigned long lpfn,
unsigned long rpfn,
unsigned long *start,
unsigned long *end)
{
*start = max3(lpfn, PFN_DOWN(vma->vm_start),
PFN_DOWN(faddr & PMD_MASK));
*end = min3(rpfn, PFN_DOWN(vma->vm_end),
PFN_DOWN((faddr & PMD_MASK) + PMD_SIZE));
}
static void swap_ra_info(struct vm_fault *vmf,
struct vma_swap_readahead *ra_info)
mm, swap: VMA based swap readahead The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patch, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:36 +08:00
{
struct vm_area_struct *vma = vmf->vma;
unsigned long ra_val;
mm, swap: VMA based swap readahead The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patch, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:36 +08:00
swp_entry_t entry;
unsigned long faddr, pfn, fpfn;
unsigned long start, end;
pte_t *pte, *orig_pte;
mm, swap: VMA based swap readahead The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patch, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:36 +08:00
unsigned int max_win, hits, prev_win, win, left;
#ifndef CONFIG_64BIT
pte_t *tpte;
#endif
mm, swap: use page-cluster as max window of VMA based swap readahead When the VMA based swap readahead was introduced, a new knob /sys/kernel/mm/swap/vma_ra_max_order was added as the max window of VMA swap readahead. This is to make it possible to use different max window for VMA based readahead and original physical readahead. But Minchan Kim pointed out that this will cause a regression because setting page-cluster sysctl to zero cannot disable swap readahead with the change. To fix the regression, the page-cluster sysctl is used as the max window of both the VMA based swap readahead and original physical swap readahead. If more fine grained control is needed in the future, more knobs can be added as the subordinate knobs of the page-cluster sysctl. The vma_ra_max_order knob is deleted. Because the knob was introduced in v4.14-rc1, and this patch is targeting being merged before v4.14 releasing, there should be no existing users of this newly added ABI. Link: http://lkml.kernel.org/r/20171011070847.16003-1-ying.huang@intel.com Fixes: ec560175c0b6fce ("mm, swap: VMA based swap readahead") Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Reported-by: Minchan Kim <minchan@kernel.org> Acked-by: Minchan Kim <minchan@kernel.org> Acked-by: Michal Hocko <mhocko@suse.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-10-14 06:58:29 +08:00
max_win = 1 << min_t(unsigned int, READ_ONCE(page_cluster),
SWAP_RA_ORDER_CEILING);
if (max_win == 1) {
ra_info->win = 1;
return;
mm, swap: use page-cluster as max window of VMA based swap readahead When the VMA based swap readahead was introduced, a new knob /sys/kernel/mm/swap/vma_ra_max_order was added as the max window of VMA swap readahead. This is to make it possible to use different max window for VMA based readahead and original physical readahead. But Minchan Kim pointed out that this will cause a regression because setting page-cluster sysctl to zero cannot disable swap readahead with the change. To fix the regression, the page-cluster sysctl is used as the max window of both the VMA based swap readahead and original physical swap readahead. If more fine grained control is needed in the future, more knobs can be added as the subordinate knobs of the page-cluster sysctl. The vma_ra_max_order knob is deleted. Because the knob was introduced in v4.14-rc1, and this patch is targeting being merged before v4.14 releasing, there should be no existing users of this newly added ABI. Link: http://lkml.kernel.org/r/20171011070847.16003-1-ying.huang@intel.com Fixes: ec560175c0b6fce ("mm, swap: VMA based swap readahead") Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Reported-by: Minchan Kim <minchan@kernel.org> Acked-by: Minchan Kim <minchan@kernel.org> Acked-by: Michal Hocko <mhocko@suse.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-10-14 06:58:29 +08:00
}
mm, swap: VMA based swap readahead The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patch, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:36 +08:00
faddr = vmf->address;
orig_pte = pte = pte_offset_map(vmf->pmd, faddr);
entry = pte_to_swp_entry(*pte);
if ((unlikely(non_swap_entry(entry)))) {
pte_unmap(orig_pte);
return;
}
mm, swap: VMA based swap readahead The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patch, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:36 +08:00
fpfn = PFN_DOWN(faddr);
ra_val = GET_SWAP_RA_VAL(vma);
pfn = PFN_DOWN(SWAP_RA_ADDR(ra_val));
prev_win = SWAP_RA_WIN(ra_val);
hits = SWAP_RA_HITS(ra_val);
ra_info->win = win = __swapin_nr_pages(pfn, fpfn, hits,
mm, swap: VMA based swap readahead The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patch, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:36 +08:00
max_win, prev_win);
atomic_long_set(&vma->swap_readahead_info,
SWAP_RA_VAL(faddr, win, 0));
if (win == 1) {
pte_unmap(orig_pte);
return;
}
mm, swap: VMA based swap readahead The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patch, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:36 +08:00
/* Copy the PTEs because the page table may be unmapped */
if (fpfn == pfn + 1)
swap_ra_clamp_pfn(vma, faddr, fpfn, fpfn + win, &start, &end);
else if (pfn == fpfn + 1)
swap_ra_clamp_pfn(vma, faddr, fpfn - win + 1, fpfn + 1,
&start, &end);
else {
left = (win - 1) / 2;
swap_ra_clamp_pfn(vma, faddr, fpfn - left, fpfn + win - left,
&start, &end);
}
ra_info->nr_pte = end - start;
ra_info->offset = fpfn - start;
pte -= ra_info->offset;
mm, swap: VMA based swap readahead The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patch, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:36 +08:00
#ifdef CONFIG_64BIT
ra_info->ptes = pte;
mm, swap: VMA based swap readahead The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patch, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:36 +08:00
#else
tpte = ra_info->ptes;
mm, swap: VMA based swap readahead The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patch, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:36 +08:00
for (pfn = start; pfn != end; pfn++)
*tpte++ = *pte++;
#endif
pte_unmap(orig_pte);
mm, swap: VMA based swap readahead The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patch, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:36 +08:00
}
static struct page *swap_vma_readahead(swp_entry_t fentry, gfp_t gfp_mask,
struct vm_fault *vmf)
mm, swap: VMA based swap readahead The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patch, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:36 +08:00
{
struct blk_plug plug;
struct vm_area_struct *vma = vmf->vma;
struct page *page;
pte_t *pte, pentry;
swp_entry_t entry;
unsigned int i;
bool page_allocated;
struct vma_swap_readahead ra_info = {0,};
mm, swap: VMA based swap readahead The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patch, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:36 +08:00
swap_ra_info(vmf, &ra_info);
if (ra_info.win == 1)
mm, swap: VMA based swap readahead The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patch, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:36 +08:00
goto skip;
blk_start_plug(&plug);
for (i = 0, pte = ra_info.ptes; i < ra_info.nr_pte;
mm, swap: VMA based swap readahead The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patch, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:36 +08:00
i++, pte++) {
pentry = *pte;
if (pte_none(pentry))
continue;
if (pte_present(pentry))
continue;
entry = pte_to_swp_entry(pentry);
if (unlikely(non_swap_entry(entry)))
continue;
page = __read_swap_cache_async(entry, gfp_mask, vma,
vmf->address, &page_allocated);
if (!page)
continue;
if (page_allocated) {
swap_readpage(page, false);
if (i != ra_info.offset) {
mm, swap: VMA based swap readahead The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patch, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:36 +08:00
SetPageReadahead(page);
count_vm_event(SWAP_RA);
}
}
put_page(page);
}
blk_finish_plug(&plug);
lru_add_drain();
skip:
return read_swap_cache_async(fentry, gfp_mask, vma, vmf->address,
ra_info.win == 1);
mm, swap: VMA based swap readahead The swap readahead is an important mechanism to reduce the swap in latency. Although pure sequential memory access pattern isn't very popular for anonymous memory, the space locality is still considered valid. In the original swap readahead implementation, the consecutive blocks in swap device are readahead based on the global space locality estimation. But the consecutive blocks in swap device just reflect the order of page reclaiming, don't necessarily reflect the access pattern in virtual memory. And the different tasks in the system may have different access patterns, which makes the global space locality estimation incorrect. In this patch, when page fault occurs, the virtual pages near the fault address will be readahead instead of the swap slots near the fault swap slot in swap device. This avoid to readahead the unrelated swap slots. At the same time, the swap readahead is changed to work on per-VMA from globally. So that the different access patterns of the different VMAs could be distinguished, and the different readahead policy could be applied accordingly. The original core readahead detection and scaling algorithm is reused, because it is an effect algorithm to detect the space locality. The test and result is as follow, Common test condition ===================== Test Machine: Xeon E5 v3 (2 sockets, 72 threads, 32G RAM) Swap device: NVMe disk Micro-benchmark with combined access pattern ============================================ vm-scalability, sequential swap test case, 4 processes to eat 50G virtual memory space, repeat the sequential memory writing until 300 seconds. The first round writing will trigger swap out, the following rounds will trigger sequential swap in and out. At the same time, run vm-scalability random swap test case in background, 8 processes to eat 30G virtual memory space, repeat the random memory write until 300 seconds. This will trigger random swap-in in the background. This is a combined workload with sequential and random memory accessing at the same time. The result (for sequential workload) is as follow, Base Optimized ---- --------- throughput 345413 KB/s 414029 KB/s (+19.9%) latency.average 97.14 us 61.06 us (-37.1%) latency.50th 2 us 1 us latency.60th 2 us 1 us latency.70th 98 us 2 us latency.80th 160 us 2 us latency.90th 260 us 217 us latency.95th 346 us 369 us latency.99th 1.34 ms 1.09 ms ra_hit% 52.69% 99.98% The original swap readahead algorithm is confused by the background random access workload, so readahead hit rate is lower. The VMA-base readahead algorithm works much better. Linpack ======= The test memory size is bigger than RAM to trigger swapping. Base Optimized ---- --------- elapsed_time 393.49 s 329.88 s (-16.2%) ra_hit% 86.21% 98.82% The score of base and optimized kernel hasn't visible changes. But the elapsed time reduced and readahead hit rate improved, so the optimized kernel runs better for startup and tear down stages. And the absolute value of readahead hit rate is high, shows that the space locality is still valid in some practical workloads. Link: http://lkml.kernel.org/r/20170807054038.1843-4-ying.huang@intel.com Signed-off-by: "Huang, Ying" <ying.huang@intel.com> Cc: Johannes Weiner <hannes@cmpxchg.org> Cc: Minchan Kim <minchan@kernel.org> Cc: Rik van Riel <riel@redhat.com> Cc: Shaohua Li <shli@kernel.org> Cc: Hugh Dickins <hughd@google.com> Cc: Fengguang Wu <fengguang.wu@intel.com> Cc: Tim Chen <tim.c.chen@intel.com> Cc: Dave Hansen <dave.hansen@intel.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2017-09-07 07:24:36 +08:00
}
/**
* swapin_readahead - swap in pages in hope we need them soon
* @entry: swap entry of this memory
* @gfp_mask: memory allocation flags
* @vmf: fault information
*
* Returns the struct page for entry and addr, after queueing swapin.
*
* It's a main entry function for swap readahead. By the configuration,
* it will read ahead blocks by cluster-based(ie, physical disk based)
* or vma-based(ie, virtual address based on faulty address) readahead.
*/
struct page *swapin_readahead(swp_entry_t entry, gfp_t gfp_mask,
struct vm_fault *vmf)
{
return swap_use_vma_readahead() ?
swap_vma_readahead(entry, gfp_mask, vmf) :
swap_cluster_readahead(entry, gfp_mask, vmf);
}
#ifdef CONFIG_SYSFS
static ssize_t vma_ra_enabled_show(struct kobject *kobj,
struct kobj_attribute *attr, char *buf)
{
return sprintf(buf, "%s\n", enable_vma_readahead ? "true" : "false");
}
static ssize_t vma_ra_enabled_store(struct kobject *kobj,
struct kobj_attribute *attr,
const char *buf, size_t count)
{
if (!strncmp(buf, "true", 4) || !strncmp(buf, "1", 1))
enable_vma_readahead = true;
else if (!strncmp(buf, "false", 5) || !strncmp(buf, "0", 1))
enable_vma_readahead = false;
else
return -EINVAL;
return count;
}
static struct kobj_attribute vma_ra_enabled_attr =
__ATTR(vma_ra_enabled, 0644, vma_ra_enabled_show,
vma_ra_enabled_store);
static struct attribute *swap_attrs[] = {
&vma_ra_enabled_attr.attr,
NULL,
};
static struct attribute_group swap_attr_group = {
.attrs = swap_attrs,
};
static int __init swap_init_sysfs(void)
{
int err;
struct kobject *swap_kobj;
swap_kobj = kobject_create_and_add("swap", mm_kobj);
if (!swap_kobj) {
pr_err("failed to create swap kobject\n");
return -ENOMEM;
}
err = sysfs_create_group(swap_kobj, &swap_attr_group);
if (err) {
pr_err("failed to register swap group\n");
goto delete_obj;
}
return 0;
delete_obj:
kobject_put(swap_kobj);
return err;
}
subsys_initcall(swap_init_sysfs);
#endif