Message-ID: <50E3B61A.3040808@linux.vnet.ibm.com>
Date:	Wed, 02 Jan 2013 09:52:50 +0530
From:	Preeti U Murthy <preeti@...ux.vnet.ibm.com>
To:	LKML <linux-kernel@...r.kernel.org>,
	"svaidy@...ux.vnet.ibm.com" <svaidy@...ux.vnet.ibm.com>,
	"Paul E. McKenney" <paulmck@...ux.vnet.ibm.com>,
	Vincent Guittot <vincent.guittot@...aro.org>,
	Peter Zijlstra <a.p.zijlstra@...llo.nl>,
	Viresh Kumar <viresh.kumar@...aro.org>,
	Amit Kucheria <amit.kucheria@...aro.org>,
	Morten Rasmussen <Morten.Rasmussen@....com>,
	Paul McKenney <paul.mckenney@...aro.org>,
	Andrew Morton <akpm@...ux-foundation.org>,
	Arjan van de Ven <arjan@...ux.intel.com>,
	Ingo Molnar <mingo@...nel.org>, Paul Turner <pjt@...gle.com>,
	Venki Pallipadi <venki@...gle.com>,
	Robin Randhawa <robin.randhawa@....com>,
	Lists linaro-dev <linaro-dev@...ts.linaro.org>,
	Matthew Garrett <mjg59@...f.ucam.org>
Subject: sched: Consequences of integrating the Per Entity Load Tracking Metric
 into the Load Balancer

Hi everyone,
I have been looking at how different workloads react when the per entity
load tracking metric is integrated into the load balancer and what are
the possible reasons for it.

I had posted the integration patch earlier:
https://lkml.org/lkml/2012/11/15/391

Essentially what I am doing is:
1.I have disabled CONFIG_FAIR_GROUP_SCHED to make the analysis simple
2.I have replaced cfs_rq->load.weight in weighted_cpuload() with
cfs.runnable_load_avg,the active load tracking metric.
3.I have replaced se.load.weight in task_h_load() with
se.load.avg.contrib,the per entity load tracking metric.
4.The load balancer will end up using these metrics.

After conducting experiments on several workloads I found out that the
performance of the workloads with the above integration would neither
improve nor deteriorate.And this observation was consistent.

Ideally the performance should have improved considering,that the metric
does better tracking of load.

Let me explain with a simple example as to why we should see a
performance improvement ideally:Consider 2 80% tasks and 1 40% task.

With integration:
----------------

       40%
80%    40%
cpu1  cpu2

The above will be the scenario when the tasks fork initially.And this is
a perfectly balanced system,hence no more load balancing.And proper
distribution of loads on the cpu.

Without integration
-------------------

40%                               40%
80%    40%                 80%    40%
cpu1   cpu2        OR     cpu1   cpu2

Because the  view is that all the tasks as having the same load.The load
balancer could ping pong tasks between these two situations.

When I performed this experiment,I did not see an improvement in the
performance though in the former case.On further observation I found
that the following was actually happening.

With integration
----------------

Initially         40% task sleeps      40% task wakes up
                                       and select_idle_sibling()
                                       decides to wake it up on cpu1

       40%   ->                   ->   40%
80%    40%        80%    40%           80%      40%
cpu1  cpu2        cpu1   cpu2          cpu1     cpu2


This makes load balance trigger movement of 40% from cpu1 back to
cpu2.Hence the stability that the load balancer was trying to achieve is
gone.Hence the culprit boils down to select_idle_sibling.How is it the
culprit and how is it hindering performance of the workloads?

*What is the way ahead with the per entity load tracking metric in the
load balancer then?*

In replies to a post by Paul in https://lkml.org/lkml/2012/12/6/105,
he mentions the following:

"It is my intuition that the greatest carnage here is actually caused
by wake-up load-balancing getting in the way of periodic in
establishing a steady state. I suspect more mileage would result from
reducing the interference wake-up load-balancing has with steady
state."

"The whole point of using blocked load is so that you can converge on a
steady state where you don't NEED to move tasks.  What disrupts this is
we naturally prefer idle cpus on wake-up balance to reduce wake-up
latency. I think the better answer is making these two processes load
balancing() and select_idle_sibling() more co-operative."

I had not realised how this would happen until I saw it happening in the
above experiment.

Based on what Paul explained above let us use the runnable load + the
blocked load for calculating the load on a cfs runqueue rather than just
the runnable load(which is what i am doing now) and see its consequence.

Initially:       40% task sleeps

       40%
80%    40%   ->  80%  40%
cpu1   cpu2     cpu1  cpu2

So initially the load on cpu1 is say 80 and on cpu2 also it is
80.Balanced.Now when 40% task sleeps,the total load on cpu2=runnable
load+blocked load.which is still 80.

As a consequence,firstly,during periodic load balancing the load is not
moved from cpu1 to cpu2 when the 40% task sleeps.(It sees the load on
cpu2 as 80 and not as 40).
Hence the above scenario remains the same.On wake up,what happens?

Here comes the point of making both load balancing and wake up
balance(select_idle_sibling) co operative. How about we always schedule
the woken up task on the prev_cpu? This seems more sensible considering
load balancing considers blocked load as being a part of the load of cpu2.

If we do that,we end up scheduling the 40% task back on cpu2.Back to the
scenario which load balancing intended.Hence a steady state is
maintained no matter what unless other tasks show up.

Note that considering prev_cpu as the default cpu to run the woken up
task on is possible only because we use blocked load for load balancing
purposes.

The above steps of using blocked load and selecting the prev_cpu as the
target for the woken up task seems to me to be the next step.This could
allow the load balance with the per entity load tracking metric to
behave as it is supposed to without anything else disrupting it.And here
i expect a performance improvement.

Please do let me know your suggestions.This will greatly help take the
right steps here on, in achieving the correct integration.

Thank you

Regards
Preeti U Murthy

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