[PATCH v3 0/7] sched: Implement shared runqueue in CFS
From: David Vernet
Date: Wed Aug 09 2023 - 18:12:56 EST
Changes
-------
This is v3 of the shared runqueue patchset. This patch set is based off
of commit 88c56cfeaec4 ("sched/fair: Block nohz tick_stop when cfs
bandwidth in use") on the sched/core branch of tip.git.
v1 (RFC): https://lore.kernel.org/lkml/20230613052004.2836135-1-void@xxxxxxxxxxxxx/
v2: https://lore.kernel.org/lkml/20230710200342.358255-1-void@xxxxxxxxxxxxx/
v2 -> v3 changes:
- Don't leave stale tasks in the lists when the SHARED_RUNQ feature is
disabled (Abel Wu)
- Use raw spin lock instead of spinlock_t (Peter)
- Fix return value from shared_runq_pick_next_task() to match the
semantics expected by newidle_balance() (Gautham, Abel)
- Fold patch __enqueue_entity() / __dequeue_entity() into previous patch
(Peter)
- Skip <= LLC domains in newidle_balance() if SHARED_RUNQ is enabled
(Peter)
- Properly support hotplug and recreating sched domains (Peter)
- Avoid unnecessary task_rq_unlock() + raw_spin_rq_lock() when src_rq ==
target_rq in shared_runq_pick_next_task() (Abel)
- Only issue list_del_init() in shared_runq_dequeue_task() if the task
is still in the list after acquiring the lock (Aaron Lu)
- Slightly change shared_runq_shard_idx() to make it more likely to keep
SMT siblings on the same bucket (Peter)
v1 -> v2 changes:
- Change name from swqueue to shared_runq (Peter)
- Shard per-LLC shared runqueues to avoid contention on scheduler-heavy
workloads (Peter)
- Pull tasks from the shared_runq in newidle_balance() rather than in
pick_next_task_fair() (Peter and Vincent)
- Rename a few functions to reflect their actual purpose. For example,
shared_runq_dequeue_task() instead of swqueue_remove_task() (Peter)
- Expose move_queued_task() from core.c rather than migrate_task_to()
(Peter)
- Properly check is_cpu_allowed() when pulling a task from a shared_runq
to ensure it can actually be migrated (Peter and Gautham)
- Dropped RFC tag
Overview
========
The scheduler must constantly strike a balance between work
conservation, and avoiding costly migrations which harm performance due
to e.g. decreased cache locality. The matter is further complicated by
the topology of the system. Migrating a task between cores on the same
LLC may be more optimal than keeping a task local to the CPU, whereas
migrating a task between LLCs or NUMA nodes may tip the balance in the
other direction.
With that in mind, while CFS is by and large mostly a work conserving
scheduler, there are certain instances where the scheduler will choose
to keep a task local to a CPU, when it would have been more optimal to
migrate it to an idle core.
An example of such a workload is the HHVM / web workload at Meta. HHVM
is a VM that JITs Hack and PHP code in service of web requests. Like
other JIT / compilation workloads, it tends to be heavily CPU bound, and
exhibit generally poor cache locality. To try and address this, we set
several debugfs (/sys/kernel/debug/sched) knobs on our HHVM workloads:
- migration_cost_ns -> 0
- latency_ns -> 20000000
- min_granularity_ns -> 10000000
- wakeup_granularity_ns -> 12000000
These knobs are intended both to encourage the scheduler to be as work
conserving as possible (migration_cost_ns -> 0), and also to keep tasks
running for relatively long time slices so as to avoid the overhead of
context switching (the other knobs). Collectively, these knobs provide a
substantial performance win; resulting in roughly a 20% improvement in
throughput. Worth noting, however, is that this improvement is _not_ at
full machine saturation.
That said, even with these knobs, we noticed that CPUs were still going
idle even when the host was overcommitted. In response, we wrote the
"shared runqueue" (SHARED_RUNQ) feature proposed in this patch set. The
idea behind SHARED_RUNQ is simple: it enables the scheduler to be more
aggressively work conserving by placing a waking task into a sharded
per-LLC FIFO queue that can be pulled from by another core in the LLC
FIFO queue which can then be pulled from before it goes idle.
With this simple change, we were able to achieve a 1 - 1.6% improvement
in throughput, as well as a small, consistent improvement in p95 and p99
latencies, in HHVM. These performance improvements were in addition to
the wins from the debugfs knobs mentioned above, and to other benchmarks
outlined below in the Results section.
Design
======
Note that the design described here reflects sharding, which is the
implementation added in the final patch of the series (following the
initial unsharded implementation added in patch 6/7). The design is
described that way in this commit summary as the benchmarks described in
the results section below all reflect a sharded SHARED_RUNQ.
The design of SHARED_RUNQ is quite simple. A shared_runq is simply a
list of struct shared_runq_shard objects, which itself is simply a
struct list_head of tasks, and a spinlock:
struct shared_runq_shard {
struct list_head list;
raw_spinlock_t lock;
} ____cacheline_aligned;
struct shared_runq {
u32 num_shards;
struct shared_runq_shard shards[];
} ____cacheline_aligned;
We create a struct shared_runq per LLC, ensuring they're in their own
cachelines to avoid false sharing between CPUs on different LLCs, and we
create a number of struct shared_runq_shard objects that are housed
there.
When a task first wakes up, it enqueues itself in the shared_runq_shard
of its current LLC at the end of enqueue_task_fair(). Enqueues only
happen if the task was not manually migrated to the current core by
select_task_rq(), and is not pinned to a specific CPU.
A core will pull a task from the shards in its LLC's shared_runq at the
beginning of newidle_balance().
Difference between SHARED_RUNQ and SIS_NODE
===========================================
In [0] Peter proposed a patch that addresses Tejun's observations that
when workqueues are targeted towards a specific LLC on his Zen2 machine
with small CCXs, that there would be significant idle time due to
select_idle_sibling() not considering anything outside of the current
LLC.
This patch (SIS_NODE) is essentially the complement to the proposal
here. SID_NODE causes waking tasks to look for idle cores in neighboring
LLCs on the same die, whereas SHARED_RUNQ causes cores about to go idle
to look for enqueued tasks. That said, in its current form, the two
features at are a different scope as SIS_NODE searches for idle cores
between LLCs, while SHARED_RUNQ enqueues tasks within a single LLC.
The patch was since removed in [1], and we compared the results to
SHARED_RUNQ (previously called "swqueue") in [2]. SIS_NODE did not
outperform SHARED_RUNQ on any of the benchmarks, so we elect to not
compare against it again for this v2 patch set.
[0]: https://lore.kernel.org/all/20230530113249.GA156198@xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx/
[1]: https://lore.kernel.org/all/20230605175636.GA4253@xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx/
[2]: https://lore.kernel.org/lkml/20230613052004.2836135-1-void@xxxxxxxxxxxxx/
Worth noting as well is that pointed out in [3] that the logic behind
including SIS_NODE in the first place should apply to SHARED_RUNQ
(meaning that e.g. very small Zen2 CPUs with only 3/4 cores per LLC
should benefit from having a single shared_runq stretch across multiple
LLCs). I drafted a patch that implements this by having a minimum LLC
size for creating a shard, and stretches a shared_runq across multiple
LLCs if they're smaller than that size, and sent it to Tejun to test on
his Zen2. Tejun reported back that SIS_NODE did not seem to make a
difference:
[3]: https://lore.kernel.org/lkml/20230711114207.GK3062772@xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx/
o____________o__________o
| mean | Variance |
o------------o----------o
Vanilla: | 108.84s | 0.0057 |
NO_SHARED_RUNQ: | 108.82s | 0.119s |
SHARED_RUNQ: | 108.17s | 0.038s |
SHARED_RUNQ w/ SIS_NODE: | 108.87s | 0.111s |
o------------o----------o
I similarly tried running kcompile on SHARED_RUNQ with SIS_NODE on my
7950X Zen3, but didn't see any gain relative to plain SHARED_RUNQ (though
a gain was observed relative to NO_SHARED_RUNQ, as described below).
Results
=======
Note that the motivation for the shared runqueue feature was originally
arrived at using experiments in the sched_ext framework that's currently
being proposed upstream. The ~1 - 1.6% improvement in HHVM throughput
is similarly visible using work-conserving sched_ext schedulers (even
very simple ones like global FIFO).
In both single and multi socket / CCX hosts, this can measurably improve
performance. In addition to the performance gains observed on our
internal web workloads, we also observed an improvement in common
workloads such as kernel compile and hackbench, when running shared
runqueue.
On the other hand, some workloads suffer from SHARED_RUNQ. Workloads
that hammer the runqueue hard, such as netperf UDP_RR, or schbench -L
-m 52 -p 512 -r 10 -t 1. This can be mitigated somewhat by sharding the
shared datastructures within a CCX, but it doesn't seem to eliminate all
contention in every scenario. On the positive side, it seems that
sharding does not materially harm the benchmarks run for this patch
series; and in fact seems to improve some workloads such as kernel
compile.
Note that for the kernel compile workloads below, the compilation was
done by running make -j$(nproc) built-in.a on several different types of
hosts configured with make allyesconfig on commit a27648c74210 ("afs:
Fix setting of mtime when creating a file/dir/symlink") on Linus' tree
(boost and turbo were disabled on all of these hosts when the
experiments were performed).
Finally, note that these results were from the patch set built off of
commit ebb83d84e49b ("sched/core: Avoid multiple calling
update_rq_clock() in __cfsb_csd_unthrottle()") on the sched/core branch
of tip.git for easy comparison with the v2 patch set results. The
patches in their final form from this set were rebased onto commit
88c56cfeaec4 ("sched/fair: Block nohz tick_stop when cfs bandwidth in
use") on the sched/core branch of tip.git.
=== Single-socket | 16 core / 32 thread | 2-CCX | AMD 7950X Zen4 ===
CPU max MHz: 5879.8818
CPU min MHz: 3000.0000
Command: make -j$(nproc) built-in.a
o____________o__________o
| mean | Variance |
o------------o----------o
NO_SHARED_RUNQ: | 581.95s | 2.639s |
SHARED_RUNQ: | 577.02s | 0.084s |
o------------o----------o
Takeaway: SHARED_RUNQ results in a statistically significant ~.85%
improvement over NO_SHARED_RUNQ. This suggests that enqueuing tasks in
the shared runqueue on every enqueue improves work conservation, and
thanks to sharding, does not result in contention.
Command: hackbench --loops 10000
o____________o__________o
| mean | Variance |
o------------o----------o
NO_SHARED_RUNQ: | 2.2492s | .00001s |
SHARED_RUNQ: | 2.0217s | .00065s |
o------------o----------o
Takeaway: SHARED_RUNQ in both forms performs exceptionally well compared
to NO_SHARED_RUNQ here, beating it by over 10%. This was a surprising
result given that it seems advantageous to err on the side of avoiding
migration in hackbench given that tasks are short lived in sending only
10k bytes worth of messages, but the results of the benchmark would seem
to suggest that minimizing runqueue delays is preferable.
Command:
for i in `seq 128`; do
netperf -6 -t UDP_RR -c -C -l $runtime &
done
o_______________________o
| Throughput | Variance |
o-----------------------o
NO_SHARED_RUNQ: | 25037.45 | 2243.44 |
SHARED_RUNQ: | 24952.50 | 1268.06 |
o-----------------------o
Takeaway: No statistical significance, though it is worth noting that
there is no regression for shared runqueue on the 7950X, while there is
a small regression on the Skylake and Milan hosts for SHARED_RUNQ as
described below.
=== Single-socket | 18 core / 36 thread | 1-CCX | Intel Skylake ===
CPU max MHz: 1601.0000
CPU min MHz: 800.0000
Command: make -j$(nproc) built-in.a
o____________o__________o
| mean | Variance |
o------------o----------o
NO_SHARED_RUNQ: | 1517.44s | 2.8322s |
SHARED_RUNQ: | 1516.51s | 2.9450s |
o------------o----------o
Takeaway: There's on statistically significant gain here. I observed
what I claimed was a .23% win in v2, but it appears that this is not
actually statistically significant.
Command: hackbench --loops 10000
o____________o__________o
| mean | Variance |
o------------o----------o
NO_SHARED_RUNQ: | 5.3370s | .0012s |
SHARED_RUNQ: | 5.2668s | .0033s |
o------------o----------o
Takeaway: SHARED_RUNQ results in a ~1.3% improvement over
NO_SHARED_RUNQ. Also statistically significant, but smaller than the
10+% improvement observed on the 7950X.
Command: netperf -n $(nproc) -l 60 -t TCP_RR
for i in `seq 128`; do
netperf -6 -t UDP_RR -c -C -l $runtime &
done
o_______________________o
| Throughput | Variance |
o-----------------------o
NO_SHARED_RUNQ: | 15699.32 | 377.01 |
SHARED_RUNQ: | 14966.42 | 714.13 |
o-----------------------o
Takeaway: NO_SHARED_RUNQ beats SHARED_RUNQ by ~4.6%. This result makes
sense -- the workload is very heavy on the runqueue, so enqueuing tasks
in the shared runqueue in __enqueue_entity() would intuitively result in
increased contention on the shard lock.
=== Single-socket | 72-core | 6-CCX | AMD Milan Zen3 ===
CPU max MHz: 700.0000
CPU min MHz: 700.0000
Command: make -j$(nproc) built-in.a
o____________o__________o
| mean | Variance |
o------------o----------o
NO_SHARED_RUNQ: | 1568.55s | 0.1568s |
SHARED_RUNQ: | 1568.26s | 1.2168s |
o------------o----------o
Takeaway: No statistically significant difference here. It might be
worth experimenting with work stealing in a follow-on patch set.
Command: hackbench --loops 10000
o____________o__________o
| mean | Variance |
o------------o----------o
NO_SHARED_RUNQ: | 5.2716s | .00143s |
SHARED_RUNQ: | 5.1716s | .00289s |
o------------o----------o
Takeaway: SHARED_RUNQ again wins, by about 2%.
Command: netperf -n $(nproc) -l 60 -t TCP_RR
for i in `seq 128`; do
netperf -6 -t UDP_RR -c -C -l $runtime &
done
o_______________________o
| Throughput | Variance |
o-----------------------o
NO_SHARED_RUNQ: | 17482.03 | 4675.99 |
SHARED_RUNQ: | 16697.25 | 9812.23 |
o-----------------------o
Takeaway: Similar to the Skylake runs, NO_SHARED_RUNQ still beats
SHARED_RUNQ, this time by ~4.5%. It's worth noting that in v2, the
NO_SHARED_RUNQ was only ~1.8% faster. The variance is very high here, so
the results of this benchmark should be taken with a large grain of
salt (noting that we do consistently see NO_SHARED_RUNQ on top due to
not contending on the shard lock).
Finally, let's look at how sharding affects the following schbench
incantation suggested by Chris in [4]:
schbench -L -m 52 -p 512 -r 10 -t 1
[4]: https://lore.kernel.org/lkml/c8419d9b-2b31-2190-3058-3625bdbcb13d@xxxxxxxx/
The TL;DR is that sharding improves things a lot, but doesn't completely
fix the problem. Here are the results from running the schbench command
on the 18 core / 36 thread single CCX, single-socket Skylake:
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
class name con-bounces contentions waittime-min waittime-max waittime-total waittime-avg acq-bounces acquisitions holdtime-min holdtime-max holdtime-total holdtime-avg
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
&shard->lock: 31510503 31510711 0.08 19.98 168932319.64 5.36 31700383 31843851 0.03 17.50 10273968.33 0.32
------------
&shard->lock 15731657 [<0000000068c0fd75>] pick_next_task_fair+0x4dd/0x510
&shard->lock 15756516 [<000000001faf84f9>] enqueue_task_fair+0x459/0x530
&shard->lock 21766 [<00000000126ec6ab>] newidle_balance+0x45a/0x650
&shard->lock 772 [<000000002886c365>] dequeue_task_fair+0x4c9/0x540
------------
&shard->lock 23458 [<00000000126ec6ab>] newidle_balance+0x45a/0x650
&shard->lock 16505108 [<000000001faf84f9>] enqueue_task_fair+0x459/0x530
&shard->lock 14981310 [<0000000068c0fd75>] pick_next_task_fair+0x4dd/0x510
&shard->lock 835 [<000000002886c365>] dequeue_task_fair+0x4c9/0x540
These results are when we create only 3 shards (16 logical cores per
shard), so the contention may be a result of overly-coarse sharding. If
we run the schbench incantation with no sharding whatsoever, we see the
following significantly worse lock stats contention:
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
class name con-bounces contentions waittime-min waittime-max waittime-total waittime-avg acq-bounces acquisitions holdtime-min holdtime-max holdtime-total holdtime-avg
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
&shard->lock: 117868635 118361486 0.09 393.01 1250954097.25 10.57 119345882 119780601 0.05 343.35 38313419.51 0.32
------------
&shard->lock 59169196 [<0000000060507011>] __enqueue_entity+0xdc/0x110
&shard->lock 59084239 [<00000000f1c67316>] __dequeue_entity+0x78/0xa0
&shard->lock 108051 [<00000000084a6193>] newidle_balance+0x45a/0x650
------------
&shard->lock 60028355 [<0000000060507011>] __enqueue_entity+0xdc/0x110
&shard->lock 119882 [<00000000084a6193>] newidle_balance+0x45a/0x650
&shard->lock 58213249 [<00000000f1c67316>] __dequeue_entity+0x78/0xa0
The contention is ~3-4x worse if we don't shard at all. This roughly
matches the fact that we had 3 shards on the first workload run above.
If we make the shards even smaller, the contention is comparably much
lower:
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
class name con-bounces contentions waittime-min waittime-max waittime-total waittime-avg acq-bounces acquisitions holdtime-min holdtime-max holdtime-total holdtime-avg
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
&shard->lock: 13839849 13877596 0.08 13.23 5389564.95 0.39 46910241 48069307 0.06 16.40 16534469.35 0.34
------------
&shard->lock 3559 [<00000000ea455dcc>] newidle_balance+0x45a/0x650
&shard->lock 6992418 [<000000002266f400>] __dequeue_entity+0x78/0xa0
&shard->lock 6881619 [<000000002a62f2e0>] __enqueue_entity+0xdc/0x110
------------
&shard->lock 6640140 [<000000002266f400>] __dequeue_entity+0x78/0xa0
&shard->lock 3523 [<00000000ea455dcc>] newidle_balance+0x45a/0x650
&shard->lock 7233933 [<000000002a62f2e0>] __enqueue_entity+0xdc/0x110
Interestingly, SHARED_RUNQ performs worse than NO_SHARED_RUNQ on the schbench
benchmark on Milan as well, but we contend more on the rq lock than the
shard lock:
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
class name con-bounces contentions waittime-min waittime-max waittime-total waittime-avg acq-bounces acquisitions holdtime-min holdtime-max holdtime-total holdtime-avg
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
&rq->__lock: 9617614 9656091 0.10 79.64 69665812.00 7.21 18092700 67652829 0.11 82.38 344524858.87 5.09
-----------
&rq->__lock 6301611 [<000000003e63bf26>] task_rq_lock+0x43/0xe0
&rq->__lock 2530807 [<00000000516703f0>] __schedule+0x72/0xaa0
&rq->__lock 109360 [<0000000011be1562>] raw_spin_rq_lock_nested+0xa/0x10
&rq->__lock 178218 [<00000000c38a30f9>] sched_ttwu_pending+0x3d/0x170
-----------
&rq->__lock 3245506 [<00000000516703f0>] __schedule+0x72/0xaa0
&rq->__lock 1294355 [<00000000c38a30f9>] sched_ttwu_pending+0x3d/0x170
&rq->__lock 2837804 [<000000003e63bf26>] task_rq_lock+0x43/0xe0
&rq->__lock 1627866 [<0000000011be1562>] raw_spin_rq_lock_nested+0xa/0x10
..................................................................................................................................................................................................
&shard->lock: 7338558 7343244 0.10 35.97 7173949.14 0.98 30200858 32679623 0.08 35.59 16270584.52 0.50
------------
&shard->lock 2004142 [<00000000f8aa2c91>] __dequeue_entity+0x78/0xa0
&shard->lock 2611264 [<00000000473978cc>] newidle_balance+0x45a/0x650
&shard->lock 2727838 [<0000000028f55bb5>] __enqueue_entity+0xdc/0x110
------------
&shard->lock 2737232 [<00000000473978cc>] newidle_balance+0x45a/0x650
&shard->lock 1693341 [<00000000f8aa2c91>] __dequeue_entity+0x78/0xa0
&shard->lock 2912671 [<0000000028f55bb5>] __enqueue_entity+0xdc/0x110
...................................................................................................................................................................................................
If we look at the lock stats with SHARED_RUNQ disabled, the rq lock still
contends the most, but it's significantly less than with it enabled:
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
class name con-bounces contentions waittime-min waittime-max waittime-total waittime-avg acq-bounces acquisitions holdtime-min holdtime-max holdtime-total holdtime-avg
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
&rq->__lock: 791277 791690 0.12 110.54 4889787.63 6.18 1575996 62390275 0.13 112.66 316262440.56 5.07
-----------
&rq->__lock 263343 [<00000000516703f0>] __schedule+0x72/0xaa0
&rq->__lock 19394 [<0000000011be1562>] raw_spin_rq_lock_nested+0xa/0x10
&rq->__lock 4143 [<000000003b542e83>] __task_rq_lock+0x51/0xf0
&rq->__lock 51094 [<00000000c38a30f9>] sched_ttwu_pending+0x3d/0x170
-----------
&rq->__lock 23756 [<0000000011be1562>] raw_spin_rq_lock_nested+0xa/0x10
&rq->__lock 379048 [<00000000516703f0>] __schedule+0x72/0xaa0
&rq->__lock 677 [<000000003b542e83>] __task_rq_lock+0x51/0xf0
Worth noting is that increasing the granularity of the shards in general
improves very runqueue-heavy workloads such as netperf UDP_RR and this
schbench command, but it doesn't necessarily make a big difference for
every workload, or for sufficiently small CCXs such as the 7950X. It may
make sense to eventually allow users to control this with a debugfs
knob, but for now we'll elect to choose a default that resulted in good
performance for the benchmarks run for this patch series.
Conclusion
==========
SHARED_RUNQ in this form provides statistically significant wins for
several types of workloads, and various CPU topologies. The reason for
this is roughly the same for all workloads: SHARED_RUNQ encourages work
conservation inside of a CCX by having a CPU do an O(# per-LLC shards)
iteration over the shared_runq shards in an LLC. We could similarly do
an O(n) iteration over all of the runqueues in the current LLC when a
core is going idle, but that's quite costly (especially for larger
LLCs), and sharded SHARED_RUNQ seems to provide a performant middle
ground between doing an O(n) walk, and doing an O(1) pull from a single
per-LLC shared runq.
For the workloads above, kernel compile and hackbench were clear winners
for SHARED_RUNQ (especially in __enqueue_entity()). The reason for the
improvement in kernel compile is of course that we have a heavily
CPU-bound workload where cache locality doesn't mean much; getting a CPU
is the #1 goal. As mentioned above, while I didn't expect to see an
improvement in hackbench, the results of the benchmark suggest that
minimizing runqueue delays is preferable to optimizing for L1/L2
locality.
Not all workloads benefit from SHARED_RUNQ, however. Workloads that
hammer the runqueue hard, such as netperf UDP_RR, or schbench -L -m 52
-p 512 -r 10 -t 1, tend to run into contention on the shard locks;
especially when enqueuing tasks in __enqueue_entity(). This can be
mitigated significantly by sharding the shared datastructures within a
CCX, but it doesn't eliminate all contention, as described above.
Worth noting as well is that Gautham Shenoy ran some interesting
experiments on a few more ideas in [5], such as walking the shared_runq
on the pop path until a task is found that can be migrated to the
calling CPU. I didn't run those experiments in this patch set, but it
might be worth doing so.
[5]: https://lore.kernel.org/lkml/ZJkqeXkPJMTl49GB@xxxxxxxxxxxxxxxxxxxxxx/
Gautham also ran some other benchmarks in [6], which we may want to
again try on this v3, but with boost disabled.
[6]: https://lore.kernel.org/lkml/ZLpMGVPDXqWEu+gm@xxxxxxxxxxxxxxxxxxxxxx/
Finally, while SHARED_RUNQ in this form encourages work conservation, it
of course does not guarantee it given that we don't implement any kind
of work stealing between shared_runq's. In the future, we could
potentially push CPU utilization even higher by enabling work stealing
between shared_runq's, likely between CCXs on the same NUMA node.
Originally-by: Roman Gushchin <roman.gushchin@xxxxxxxxx>
Signed-off-by: David Vernet <void@xxxxxxxxxxxxx>
David Vernet (7):
sched: Expose move_queued_task() from core.c
sched: Move is_cpu_allowed() into sched.h
sched: Check cpu_active() earlier in newidle_balance()
sched: Enable sched_feat callbacks on enable/disable
sched/fair: Add SHARED_RUNQ sched feature and skeleton calls
sched: Implement shared runqueue in CFS
sched: Shard per-LLC shared runqueues
include/linux/sched.h | 2 +
kernel/sched/core.c | 52 ++----
kernel/sched/debug.c | 18 ++-
kernel/sched/fair.c | 340 +++++++++++++++++++++++++++++++++++++++-
kernel/sched/features.h | 1 +
kernel/sched/sched.h | 56 ++++++-
kernel/sched/topology.c | 4 +-
7 files changed, 420 insertions(+), 53 deletions(-)
--
2.41.0