From: Peter Zijlstra <peterz@infradead.org>
To: Aaron Lu <aaron.lu@intel.com>
Cc: Ingo Molnar <mingo@redhat.com>,
Juri Lelli <juri.lelli@redhat.com>,
Vincent Guittot <vincent.guittot@linaro.org>,
Dietmar Eggemann <dietmar.eggemann@arm.com>,
Steven Rostedt <rostedt@goodmis.org>,
Ben Segall <bsegall@google.com>, Mel Gorman <mgorman@suse.de>,
Daniel Bristot de Oliveira <bristot@redhat.com>,
Valentin Schneider <vschneid@redhat.com>,
Tim Chen <tim.c.chen@intel.com>,
Nitin Tekchandani <nitin.tekchandani@intel.com>,
Waiman Long <longman@redhat.com>, Yu Chen <yu.c.chen@intel.com>,
linux-kernel@vger.kernel.org
Subject: Re: [RFC PATCH] sched/fair: Make tg->load_avg per node
Date: Wed, 12 Apr 2023 13:59:36 +0200 [thread overview]
Message-ID: <20230412115936.GC628377@hirez.programming.kicks-ass.net> (raw)
In-Reply-To: <20230327053955.GA570404@ziqianlu-desk2>
On Mon, Mar 27, 2023 at 01:39:55PM +0800, Aaron Lu wrote:
> When using sysbench to benchmark Postgres in a single docker instance
> with sysbench's nr_threads set to nr_cpu, it is observed there are times
> update_cfs_group() and update_load_avg() shows noticeable overhead on
> cpus of one node of a 2sockets/112core/224cpu Intel Sapphire Rapids:
>
> 10.01% 9.86% [kernel.vmlinux] [k] update_cfs_group
> 7.84% 7.43% [kernel.vmlinux] [k] update_load_avg
>
> While cpus of the other node normally sees a lower cycle percent:
>
> 4.46% 4.36% [kernel.vmlinux] [k] update_cfs_group
> 4.02% 3.40% [kernel.vmlinux] [k] update_load_avg
>
> Annotate shows the cycles are mostly spent on accessing tg->load_avg
> with update_load_avg() being the write side and update_cfs_group() being
> the read side.
>
> The reason why only cpus of one node has bigger overhead is: task_group
> is allocated on demand from a slab and whichever cpu happens to do the
> allocation, the allocated tg will be located on that node and accessing
> to tg->load_avg will have a lower cost for cpus on the same node and
> a higer cost for cpus of the remote node.
>
> Tim Chen told me that PeterZ once mentioned a way to solve a similar
> problem by making a counter per node so do the same for tg->load_avg.
Yeah, I send him a very similar patch (except horrible) some 5 years ago
for testing.
> After this change, the worst number I saw during a 5 minutes run from
> both nodes are:
>
> 2.77% 2.11% [kernel.vmlinux] [k] update_load_avg
> 2.72% 2.59% [kernel.vmlinux] [k] update_cfs_group
Nice!
> Another observation of this workload is: it has a lot of wakeup time
> task migrations and that is the reason why update_load_avg() and
> update_cfs_group() shows noticeable cost. Running this workload in N
> instances setup where N >= 2 with sysbench's nr_threads set to 1/N nr_cpu,
> task migrations on wake up time are greatly reduced and the overhead from
> the two above mentioned functions also dropped a lot. It's not clear to
> me why running in multiple instances can reduce task migrations on
> wakeup path yet.
If there is *any* idle time, we're rather agressive at moving tasks to
idle CPUs in an attempt to avoid said idle time. If you're running at
about the number of CPUs there will be a fair amount of idle time and
hence significant migrations.
When you overload, there will no longer be idle time and hence no more
migrations.
> Reported-by: Nitin Tekchandani <nitin.tekchandani@intel.com>
> Signed-off-by: Aaron Lu <aaron.lu@intel.com>
If you want to make things more complicated you can check
num_possible_nodes()==1 on boot and then avoid the indirection, but
next prev parent reply other threads:[~2023-04-12 12:02 UTC|newest]
Thread overview: 33+ messages / expand[flat|nested] mbox.gz Atom feed top
2023-03-27 5:39 Aaron Lu
2023-03-27 14:45 ` Chen Yu
2023-03-28 6:42 ` Aaron Lu
2023-03-28 12:09 ` Dietmar Eggemann
2023-03-28 12:56 ` Aaron Lu
2023-03-29 12:36 ` Dietmar Eggemann
2023-03-29 13:54 ` Aaron Lu
2023-03-30 17:45 ` Daniel Jordan
2023-03-30 19:51 ` Daniel Jordan
2023-03-31 4:06 ` Aaron Lu
2023-03-31 15:48 ` Dietmar Eggemann
2023-04-03 7:53 ` Aaron Lu
2023-04-05 21:04 ` Daniel Jordan
2023-04-12 12:07 ` Peter Zijlstra
2023-04-20 20:52 ` Daniel Jordan
2023-04-21 15:05 ` Aaron Lu
2023-05-03 19:41 ` Daniel Jordan
2023-05-04 10:27 ` Aaron Lu
2023-05-16 7:50 ` Aaron Lu
2023-05-16 8:57 ` Chen Yu
2023-05-16 11:32 ` Aaron Lu
2023-03-29 14:55 ` Chen Yu
2023-04-04 8:25 ` Chen Yu
2023-04-04 13:33 ` Aaron Lu
2023-04-04 15:15 ` Aaron Lu
2023-04-04 15:37 ` Chen Yu
2023-04-05 21:31 ` Daniel Jordan
2023-04-12 11:59 ` Peter Zijlstra [this message]
2023-04-12 13:58 ` Peter Zijlstra
2023-04-12 14:11 ` Aaron Lu
2023-04-12 14:01 ` Aaron Lu
2023-04-22 4:01 ` Chen Yu
2023-04-22 6:04 ` Aaron Lu
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