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Each text file under Documentation follows a different format. Some doesn't even have titles! Change its representation to follow the adopted standard, using ReST markups for it to be parseable by Sphinx: - mark document title; - mark literal blocks. Signed-off-by: Mauro Carvalho Chehab <mchehab@s-opensource.com> Signed-off-by: Jonathan Corbet <corbet@lwn.net>
164 lines
7.4 KiB
Plaintext
164 lines
7.4 KiB
Plaintext
=======================================
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The padata parallel execution mechanism
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=======================================
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:Last updated: for 2.6.36
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Padata is a mechanism by which the kernel can farm work out to be done in
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parallel on multiple CPUs while retaining the ordering of tasks. It was
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developed for use with the IPsec code, which needs to be able to perform
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encryption and decryption on large numbers of packets without reordering
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those packets. The crypto developers made a point of writing padata in a
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sufficiently general fashion that it could be put to other uses as well.
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The first step in using padata is to set up a padata_instance structure for
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overall control of how tasks are to be run::
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#include <linux/padata.h>
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struct padata_instance *padata_alloc(struct workqueue_struct *wq,
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const struct cpumask *pcpumask,
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const struct cpumask *cbcpumask);
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The pcpumask describes which processors will be used to execute work
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submitted to this instance in parallel. The cbcpumask defines which
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processors are allowed to be used as the serialization callback processor.
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The workqueue wq is where the work will actually be done; it should be
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a multithreaded queue, naturally.
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To allocate a padata instance with the cpu_possible_mask for both
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cpumasks this helper function can be used::
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struct padata_instance *padata_alloc_possible(struct workqueue_struct *wq);
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Note: Padata maintains two kinds of cpumasks internally. The user supplied
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cpumasks, submitted by padata_alloc/padata_alloc_possible and the 'usable'
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cpumasks. The usable cpumasks are always a subset of active CPUs in the
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user supplied cpumasks; these are the cpumasks padata actually uses. So
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it is legal to supply a cpumask to padata that contains offline CPUs.
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Once an offline CPU in the user supplied cpumask comes online, padata
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is going to use it.
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There are functions for enabling and disabling the instance::
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int padata_start(struct padata_instance *pinst);
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void padata_stop(struct padata_instance *pinst);
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These functions are setting or clearing the "PADATA_INIT" flag;
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if that flag is not set, other functions will refuse to work.
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padata_start returns zero on success (flag set) or -EINVAL if the
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padata cpumask contains no active CPU (flag not set).
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padata_stop clears the flag and blocks until the padata instance
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is unused.
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The list of CPUs to be used can be adjusted with these functions::
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int padata_set_cpumasks(struct padata_instance *pinst,
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cpumask_var_t pcpumask,
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cpumask_var_t cbcpumask);
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int padata_set_cpumask(struct padata_instance *pinst, int cpumask_type,
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cpumask_var_t cpumask);
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int padata_add_cpu(struct padata_instance *pinst, int cpu, int mask);
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int padata_remove_cpu(struct padata_instance *pinst, int cpu, int mask);
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Changing the CPU masks are expensive operations, though, so it should not be
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done with great frequency.
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It's possible to change both cpumasks of a padata instance with
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padata_set_cpumasks by specifying the cpumasks for parallel execution (pcpumask)
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and for the serial callback function (cbcpumask). padata_set_cpumask is used to
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change just one of the cpumasks. Here cpumask_type is one of PADATA_CPU_SERIAL,
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PADATA_CPU_PARALLEL and cpumask specifies the new cpumask to use.
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To simply add or remove one CPU from a certain cpumask the functions
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padata_add_cpu/padata_remove_cpu are used. cpu specifies the CPU to add or
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remove and mask is one of PADATA_CPU_SERIAL, PADATA_CPU_PARALLEL.
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If a user is interested in padata cpumask changes, he can register to
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the padata cpumask change notifier::
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int padata_register_cpumask_notifier(struct padata_instance *pinst,
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struct notifier_block *nblock);
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To unregister from that notifier::
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int padata_unregister_cpumask_notifier(struct padata_instance *pinst,
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struct notifier_block *nblock);
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The padata cpumask change notifier notifies about changes of the usable
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cpumasks, i.e. the subset of active CPUs in the user supplied cpumask.
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Padata calls the notifier chain with::
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blocking_notifier_call_chain(&pinst->cpumask_change_notifier,
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notification_mask,
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&pd_new->cpumask);
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Here cpumask_change_notifier is registered notifier, notification_mask
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is one of PADATA_CPU_SERIAL, PADATA_CPU_PARALLEL and cpumask is a pointer
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to a struct padata_cpumask that contains the new cpumask information.
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Actually submitting work to the padata instance requires the creation of a
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padata_priv structure::
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struct padata_priv {
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/* Other stuff here... */
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void (*parallel)(struct padata_priv *padata);
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void (*serial)(struct padata_priv *padata);
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};
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This structure will almost certainly be embedded within some larger
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structure specific to the work to be done. Most of its fields are private to
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padata, but the structure should be zeroed at initialisation time, and the
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parallel() and serial() functions should be provided. Those functions will
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be called in the process of getting the work done as we will see
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momentarily.
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The submission of work is done with::
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int padata_do_parallel(struct padata_instance *pinst,
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struct padata_priv *padata, int cb_cpu);
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The pinst and padata structures must be set up as described above; cb_cpu
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specifies which CPU will be used for the final callback when the work is
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done; it must be in the current instance's CPU mask. The return value from
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padata_do_parallel() is zero on success, indicating that the work is in
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progress. -EBUSY means that somebody, somewhere else is messing with the
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instance's CPU mask, while -EINVAL is a complaint about cb_cpu not being
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in that CPU mask or about a not running instance.
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Each task submitted to padata_do_parallel() will, in turn, be passed to
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exactly one call to the above-mentioned parallel() function, on one CPU, so
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true parallelism is achieved by submitting multiple tasks. Despite the
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fact that the workqueue is used to make these calls, parallel() is run with
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software interrupts disabled and thus cannot sleep. The parallel()
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function gets the padata_priv structure pointer as its lone parameter;
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information about the actual work to be done is probably obtained by using
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container_of() to find the enclosing structure.
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Note that parallel() has no return value; the padata subsystem assumes that
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parallel() will take responsibility for the task from this point. The work
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need not be completed during this call, but, if parallel() leaves work
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outstanding, it should be prepared to be called again with a new job before
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the previous one completes. When a task does complete, parallel() (or
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whatever function actually finishes the job) should inform padata of the
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fact with a call to::
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void padata_do_serial(struct padata_priv *padata);
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At some point in the future, padata_do_serial() will trigger a call to the
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serial() function in the padata_priv structure. That call will happen on
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the CPU requested in the initial call to padata_do_parallel(); it, too, is
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done through the workqueue, but with local software interrupts disabled.
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Note that this call may be deferred for a while since the padata code takes
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pains to ensure that tasks are completed in the order in which they were
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submitted.
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The one remaining function in the padata API should be called to clean up
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when a padata instance is no longer needed::
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void padata_free(struct padata_instance *pinst);
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This function will busy-wait while any remaining tasks are completed, so it
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might be best not to call it while there is work outstanding. Shutting
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down the workqueue, if necessary, should be done separately.
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