Extrapolating on the existing framework to track rt/dl utilization using
pelt signals, add a similar mechanism to track thermal pressure. The
difference here from rt/dl utilization tracking is that, instead of
tracking time spent by a CPU running a RT/DL task through util_avg, the
average thermal pressure is tracked through load_avg. This is because
thermal pressure signal is weighted time "delta" capacity unlike util_avg
which is binary. "delta capacity" here means delta between the actual
capacity of a CPU and the decreased capacity a CPU due to a thermal event.
In order to track average thermal pressure, a new sched_avg variable
avg_thermal is introduced. Function update_thermal_load_avg can be called
to do the periodic bookkeeping (accumulate, decay and average) of the
thermal pressure.
Reviewed-by: Vincent Guittot <vincent.guittot@linaro.org>
Signed-off-by: Thara Gopinath <thara.gopinath@linaro.org>
Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org>
Signed-off-by: Ingo Molnar <mingo@kernel.org>
Link: https://lkml.kernel.org/r/20200222005213.3873-2-thara.gopinath@linaro.org
Now that runnable_load_avg has been removed, we can replace it by a new
signal that will highlight the runnable pressure on a cfs_rq. This signal
track the waiting time of tasks on rq and can help to better define the
state of rqs.
At now, only util_avg is used to define the state of a rq:
A rq with more that around 80% of utilization and more than 1 tasks is
considered as overloaded.
But the util_avg signal of a rq can become temporaly low after that a task
migrated onto another rq which can bias the classification of the rq.
When tasks compete for the same rq, their runnable average signal will be
higher than util_avg as it will include the waiting time and we can use
this signal to better classify cfs_rqs.
The new runnable_avg will track the runnable time of a task which simply
adds the waiting time to the running time. The runnable _avg of cfs_rq
will be the /Sum of se's runnable_avg and the runnable_avg of group entity
will follow the one of the rq similarly to util_avg.
Signed-off-by: Vincent Guittot <vincent.guittot@linaro.org>
Signed-off-by: Mel Gorman <mgorman@techsingularity.net>
Signed-off-by: Ingo Molnar <mingo@kernel.org>
Reviewed-by: "Dietmar Eggemann <dietmar.eggemann@arm.com>"
Acked-by: Peter Zijlstra <a.p.zijlstra@chello.nl>
Cc: Juri Lelli <juri.lelli@redhat.com>
Cc: Valentin Schneider <valentin.schneider@arm.com>
Cc: Phil Auld <pauld@redhat.com>
Cc: Hillf Danton <hdanton@sina.com>
Link: https://lore.kernel.org/r/20200224095223.13361-9-mgorman@techsingularity.net
Now that runnable_load_avg is no more used, we can remove it to make
space for a new signal.
Signed-off-by: Vincent Guittot <vincent.guittot@linaro.org>
Signed-off-by: Mel Gorman <mgorman@techsingularity.net>
Signed-off-by: Ingo Molnar <mingo@kernel.org>
Reviewed-by: "Dietmar Eggemann <dietmar.eggemann@arm.com>"
Acked-by: Peter Zijlstra <a.p.zijlstra@chello.nl>
Cc: Juri Lelli <juri.lelli@redhat.com>
Cc: Valentin Schneider <valentin.schneider@arm.com>
Cc: Phil Auld <pauld@redhat.com>
Cc: Hillf Danton <hdanton@sina.com>
Link: https://lore.kernel.org/r/20200224095223.13361-8-mgorman@techsingularity.net
Because of the:
if (!load)
runnable = running = 0;
clause in ___update_load_sum(), all the actual users of @contrib in
accumulate_sum():
if (load)
sa->load_sum += load * contrib;
if (runnable)
sa->runnable_load_sum += runnable * contrib;
if (running)
sa->util_sum += contrib << SCHED_CAPACITY_SHIFT;
don't happen, and therefore we don't care what @contrib actually is and
calculating it is pointless.
If we count the times when @load equals zero and not as below:
if (load) {
load_is_not_zero_count++;
contrib = __accumulate_pelt_segments(periods,
1024 - sa->period_contrib,delta);
} else
load_is_zero_count++;
As we can see, load_is_zero_count is much bigger than
load_is_zero_count, and the gap is gradually widening:
load_is_zero_count: 6016044 times
load_is_not_zero_count: 244316 times
19:50:43 up 1 min, 1 user, load average: 0.09, 0.06, 0.02
load_is_zero_count: 7956168 times
load_is_not_zero_count: 261472 times
19:51:42 up 2 min, 1 user, load average: 0.03, 0.05, 0.01
load_is_zero_count: 10199896 times
load_is_not_zero_count: 278364 times
19:52:51 up 3 min, 1 user, load average: 0.06, 0.05, 0.01
load_is_zero_count: 14333700 times
load_is_not_zero_count: 318424 times
19:54:53 up 5 min, 1 user, load average: 0.01, 0.03, 0.00
Perhaps we can gain some performance advantage by saving these
unnecessary calculation.
Signed-off-by: Peng Wang <rocking@linux.alibaba.com>
Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org>
Reviewed-by: Vincent Guittot < vincent.guittot@linaro.org>
Link: https://lkml.kernel.org/r/1576208740-35609-1-git-send-email-rocking@linux.alibaba.com
The current implementation of load tracking invariance scales the
contribution with current frequency and uarch performance (only for
utilization) of the CPU. One main result of this formula is that the
figures are capped by current capacity of CPU. Another one is that the
load_avg is not invariant because not scaled with uarch.
The util_avg of a periodic task that runs r time slots every p time slots
varies in the range :
U * (1-y^r)/(1-y^p) * y^i < Utilization < U * (1-y^r)/(1-y^p)
with U is the max util_avg value = SCHED_CAPACITY_SCALE
At a lower capacity, the range becomes:
U * C * (1-y^r')/(1-y^p) * y^i' < Utilization < U * C * (1-y^r')/(1-y^p)
with C reflecting the compute capacity ratio between current capacity and
max capacity.
so C tries to compensate changes in (1-y^r') but it can't be accurate.
Instead of scaling the contribution value of PELT algo, we should scale the
running time. The PELT signal aims to track the amount of computation of
tasks and/or rq so it seems more correct to scale the running time to
reflect the effective amount of computation done since the last update.
In order to be fully invariant, we need to apply the same amount of
running time and idle time whatever the current capacity. Because running
at lower capacity implies that the task will run longer, we have to ensure
that the same amount of idle time will be applied when system becomes idle
and no idle time has been "stolen". But reaching the maximum utilization
value (SCHED_CAPACITY_SCALE) means that the task is seen as an
always-running task whatever the capacity of the CPU (even at max compute
capacity). In this case, we can discard this "stolen" idle times which
becomes meaningless.
In order to achieve this time scaling, a new clock_pelt is created per rq.
The increase of this clock scales with current capacity when something
is running on rq and synchronizes with clock_task when rq is idle. With
this mechanism, we ensure the same running and idle time whatever the
current capacity. This also enables to simplify the pelt algorithm by
removing all references of uarch and frequency and applying the same
contribution to utilization and loads. Furthermore, the scaling is done
only once per update of clock (update_rq_clock_task()) instead of during
each update of sched_entities and cfs/rt/dl_rq of the rq like the current
implementation. This is interesting when cgroup are involved as shown in
the results below:
On a hikey (octo Arm64 platform).
Performance cpufreq governor and only shallowest c-state to remove variance
generated by those power features so we only track the impact of pelt algo.
each test runs 16 times:
./perf bench sched pipe
(higher is better)
kernel tip/sched/core + patch
ops/seconds ops/seconds diff
cgroup
root 59652(+/- 0.18%) 59876(+/- 0.24%) +0.38%
level1 55608(+/- 0.27%) 55923(+/- 0.24%) +0.57%
level2 52115(+/- 0.29%) 52564(+/- 0.22%) +0.86%
hackbench -l 1000
(lower is better)
kernel tip/sched/core + patch
duration(sec) duration(sec) diff
cgroup
root 4.453(+/- 2.37%) 4.383(+/- 2.88%) -1.57%
level1 4.859(+/- 8.50%) 4.830(+/- 7.07%) -0.60%
level2 5.063(+/- 9.83%) 4.928(+/- 9.66%) -2.66%
Then, the responsiveness of PELT is improved when CPU is not running at max
capacity with this new algorithm. I have put below some examples of
duration to reach some typical load values according to the capacity of the
CPU with current implementation and with this patch. These values has been
computed based on the geometric series and the half period value:
Util (%) max capacity half capacity(mainline) half capacity(w/ patch)
972 (95%) 138ms not reachable 276ms
486 (47.5%) 30ms 138ms 60ms
256 (25%) 13ms 32ms 26ms
On my hikey (octo Arm64 platform) with schedutil governor, the time to
reach max OPP when starting from a null utilization, decreases from 223ms
with current scale invariance down to 121ms with the new algorithm.
Signed-off-by: Vincent Guittot <vincent.guittot@linaro.org>
Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org>
Cc: Linus Torvalds <torvalds@linux-foundation.org>
Cc: Mike Galbraith <efault@gmx.de>
Cc: Morten.Rasmussen@arm.com
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: bsegall@google.com
Cc: dietmar.eggemann@arm.com
Cc: patrick.bellasi@arm.com
Cc: pjt@google.com
Cc: pkondeti@codeaurora.org
Cc: quentin.perret@arm.com
Cc: rjw@rjwysocki.net
Cc: srinivas.pandruvada@linux.intel.com
Cc: thara.gopinath@linaro.org
Link: https://lkml.kernel.org/r/1548257214-13745-3-git-send-email-vincent.guittot@linaro.org
Signed-off-by: Ingo Molnar <mingo@kernel.org>
A CFS (SCHED_OTHER, SCHED_BATCH or SCHED_IDLE policy) task's
se->runnable_weight must always be in sync with its se->load.weight.
se->runnable_weight is set to se->load.weight when the task is
forked (init_entity_runnable_average()) or reniced (reweight_entity()).
There are two cases in set_load_weight() which since they currently only
set se->load.weight could lead to a situation in which se->load.weight
is different to se->runnable_weight for a CFS task:
(1) A task switches to SCHED_IDLE.
(2) A SCHED_FIFO, SCHED_RR or SCHED_DEADLINE task which has been reniced
(during which only its static priority gets set) switches to
SCHED_OTHER or SCHED_BATCH.
Set se->runnable_weight to se->load.weight in these two cases to prevent
this. This eliminates the need to explicitly set it to se->load.weight
during PELT updates in the CFS scheduler fastpath.
Signed-off-by: Dietmar Eggemann <dietmar.eggemann@arm.com>
Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org>
Cc: Joel Fernandes <joelaf@google.com>
Cc: Linus Torvalds <torvalds@linux-foundation.org>
Cc: Morten Rasmussen <morten.rasmussen@arm.com>
Cc: Patrick Bellasi <patrick.bellasi@arm.com>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Quentin Perret <quentin.perret@arm.com>
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: Vincent Guittot <vincent.guittot@linaro.org>
Link: http://lkml.kernel.org/r/20180803140538.1178-1-dietmar.eggemann@arm.com
Signed-off-by: Ingo Molnar <mingo@kernel.org>
Create a config for enabling irq load tracking in the scheduler.
irq load tracking is useful only when irq or paravirtual time is
accounted but it's only possible with SMP for now.
Also use __maybe_unused to remove the compilation warning in
update_rq_clock_task() that has been introduced by:
2e62c4743a ("sched/fair: Remove #ifdefs from scale_rt_capacity()")
Suggested-by: Ingo Molnar <mingo@redhat.com>
Reported-by: Dou Liyang <douly.fnst@cn.fujitsu.com>
Reported-by: Miguel Ojeda <miguel.ojeda.sandonis@gmail.com>
Signed-off-by: Vincent Guittot <vincent.guittot@linaro.org>
Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org>
Cc: Linus Torvalds <torvalds@linux-foundation.org>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: bp@alien8.de
Cc: dou_liyang@163.com
Fixes: 2e62c4743a ("sched/fair: Remove #ifdefs from scale_rt_capacity()")
Link: http://lkml.kernel.org/r/1537867062-27285-1-git-send-email-vincent.guittot@linaro.org
Signed-off-by: Ingo Molnar <mingo@kernel.org>
interrupt and steal time are the only remaining activities tracked by
rt_avg. Like for sched classes, we can use PELT to track their average
utilization of the CPU. But unlike sched class, we don't track when
entering/leaving interrupt; Instead, we take into account the time spent
under interrupt context when we update rqs' clock (rq_clock_task).
This also means that we have to decay the normal context time and account
for interrupt time during the update.
That's also important to note that because:
rq_clock == rq_clock_task + interrupt time
and rq_clock_task is used by a sched class to compute its utilization, the
util_avg of a sched class only reflects the utilization of the time spent
in normal context and not of the whole time of the CPU. The utilization of
interrupt gives an more accurate level of utilization of CPU.
The CPU utilization is:
avg_irq + (1 - avg_irq / max capacity) * /Sum avg_rq
Most of the time, avg_irq is small and neglictible so the use of the
approximation CPU utilization = /Sum avg_rq was enough.
Signed-off-by: Vincent Guittot <vincent.guittot@linaro.org>
Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org>
Cc: Linus Torvalds <torvalds@linux-foundation.org>
Cc: Morten.Rasmussen@arm.com
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: claudio@evidence.eu.com
Cc: daniel.lezcano@linaro.org
Cc: dietmar.eggemann@arm.com
Cc: joel@joelfernandes.org
Cc: juri.lelli@redhat.com
Cc: luca.abeni@santannapisa.it
Cc: patrick.bellasi@arm.com
Cc: quentin.perret@arm.com
Cc: rjw@rjwysocki.net
Cc: valentin.schneider@arm.com
Cc: viresh.kumar@linaro.org
Link: http://lkml.kernel.org/r/1530200714-4504-7-git-send-email-vincent.guittot@linaro.org
Signed-off-by: Ingo Molnar <mingo@kernel.org>
