Date:	Mon, 1 Feb 2010 23:13:42 -0800
From:	Paul Turner <pjt@...gle.com>
To:	bharata@...ux.vnet.ibm.com
Cc:	Bharata B Rao <bharata.rao@...il.com>,
	linux-kernel@...r.kernel.org,
	Dhaval Giani <dhaval.giani@...il.com>,
	Balbir Singh <balbir@...ux.vnet.ibm.com>,
	Vaidyanathan Srinivasan <svaidy@...ux.vnet.ibm.com>,
	Gautham R Shenoy <ego@...ibm.com>,
	Srivatsa Vaddagiri <vatsa@...ibm.com>,
	Kamalesh Babulal <kamalesh@...ux.vnet.ibm.com>,
	Ingo Molnar <mingo@...e.hu>,
	Peter Zijlstra <a.p.zijlstra@...llo.nl>,
	Pavel Emelyanov <xemul@...nvz.org>,
	Herbert Poetzl <herbert@...hfloor.at>,
	Avi Kivity <avi@...hat.com>,
	Chris Friesen <cfriesen@...tel.com>,
	Paul Menage <menage@...gle.com>,
	Mike Waychison <mikew@...gle.com>
Subject: Re: [RFC v5 PATCH 0/8] CFS Hard limits - v5

On Mon, Feb 1, 2010 at 8:14 PM, Bharata B Rao
<bharata@...ux.vnet.ibm.com> wrote:
> On Mon, Feb 01, 2010 at 10:25:11AM -0800, Paul Turner wrote:
>> On Mon, Feb 1, 2010 at 3:04 AM, Paul Turner <pjt@...gle.com> wrote:
>> > On Mon, Feb 1, 2010 at 12:21 AM, Bharata B Rao
>> > <bharata@...ux.vnet.ibm.com> wrote:
>> >> On Thu, Jan 28, 2010 at 08:26:08PM -0800, Paul Turner wrote:
>> >>> On Thu, Jan 28, 2010 at 7:49 PM, Bharata B Rao <bharata.rao@...il.com> wrote:
>> >>> > On Sat, Jan 9, 2010 at 2:15 AM, Paul Turner <pjt@...gle.com> wrote:
>> >>> >>
>> >>> >> What are your thoughts on using a separate mechanism for the general case.  A
>> >>> >> draft proposal follows:
>> >>> >>
>> >>> >> - Maintain a global run-time pool for each tg.  The runtime specified by the
>> >>> >>  user represents the value that this pool will be refilled to each period.
>> >>> >> - We continue to maintain the local notion of runtime/period in each cfs_rq,
>> >>> >>  continue to accumulate locally here.
>> >>> >>
>> >>> >> Upon locally exceeding the period acquire new credit from the global pool
>> >>> >> (either under lock or more likely using atomic ops).  This can either be in
>> >>> >> fixed steppings (e.g. 10ms, could be tunable) or following some quasi-curve
>> >>> >> variant with historical demand.
>> >>> >>
>> >>> >> One caveat here is that there is some over-commit in the system, the local
>> >>> >> differences of runtime vs period represent additional over the global pool.
>> >>> >> However it should not be possible to consistently exceed limits since the rate
>> >>> >> of refill is gated by the runtime being input into the system via the per-tg
>> >>> >> pool.
>> >>> >>
>> >>> >
>> >>> > We borrow from what is actually available as spare (spare = unused or
>> >>> > remaining). With global pool, I see that would be difficult.
>> >>> > Inability/difficulty in keeping the global pool in sync with the
>> >>> > actual available spare time is the reason for over-commit ?
>> >>> >
>> >>>
>> >>> We maintain two pools, a global pool (new) and a per-cfs_rq pool
>> >>> (similar to existing rt_bw).
>> >>>
>> >>> When consuming time you charge vs your local bandwidth until it is
>> >>> expired, at this point you must either refill from the global pool, or
>> >>> throttle.
>> >>>
>> >>> The "slack" in the system is the sum of unconsumed time in local pools
>> >>> from the *previous* global pool refill.  This is bounded above by the
>> >>> size of time you refill a local pool at each expiry.  We call the size
>> >>> of refill a 'slice'.
>> >>>
>> >>> e.g.
>> >>>
>> >>> Task limit of 50ms, slice=10ms, 4cpus, period of 500ms
>> >>>
>> >>> Task A runs on cpus 0 and 1 for 5ms each, then blocks.
>> >>>
>> >>> When A first executes on each cpu we take slice=10ms from the global
>> >>> pool of 50ms and apply it to the local rq.  Execution then proceeds vs
>> >>> local pool.
>> >>>
>> >>> Current state is: 5 ms in local pools on {0,1}, 30ms remaining in global pool
>> >>>
>> >>> Upon period expiration we issue a global pool refill.  At this point we have:
>> >>> 5 ms in local pools on {0,1}, 50ms remaining in global pool.
>> >>>
>> >>> That 10ms of slack time is over-commit in the system.  However it
>> >>> should be clear that this can only be a local effect since over any
>> >>> period of time the rate of input into the system is limited by global
>> >>> pool refill rate.
>> >>
>> >> With the same setup as above consider 5 such tasks which block after
>> >> consuming 5ms each. So now we have 25ms slack time. In the next bandwidth
>> >> period if 5 cpu hogs start running and they would consume this 25ms and the
>> >> 50ms from this period. So we gave 50% extra to a group in a bandwidth period.
>> >> Just wondering how common such scenarious could be.
>> >>
>> >
>> > Yes within a single given period you may exceed your reservation due
>> > to slack.  However, of note is that across any 2 successive periods
>> > you are guaranteed to be within your reservation, i.e. 2*usage <=
>> > 2*period, as slack available means that you under-consumed your
>> > previous period.
>> >
>> > For those needing a hard guarantee (independent of amelioration
>> > strategies) halving the period provided would then provide this across
>> > their target period with the basic v1 implementation.
>> >
>>
>> Actually now that I think about it, this observation only holds when
>> the slack is consumed within the second of the two periods.  It should
>> be restated something like:
>>
>> for any n contiguous periods your maximum usage is n*runtime +
>> nr_cpus*slice, note the slack term is constant and is dominated for
>> any observation window involving several periods
>
> Ok. We are talking about 'hard limits' here and looks like there is
> a theoritical possibility of exceeding the limit often. Need to understand
> how good/bad this is in real life.
>

I'm really glad that we're having this discussion however it feels
like we are rat-holing a little on the handling of slack?  As an issue
it seems a non-starter since if necessary it can be scrubbed with the
same overhead as the original proposal for period refresh (i.e. remove
slack from each cpu).  There are also trivial faster ways to zero it
without this O(n) overhead.

I feel it would be more productive to focus discussion on other areas
of design such as load balancer interaction, distribution from global
to local pools, entity placement and fairness on wakeup, etc.

> Regards,
> Bharata.
>
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