[lkml]   [2018]   [Apr]   [17]   [last100]   RSS Feed
Views: [wrap][no wrap]   [headers]  [forward] 
Messages in this thread
SubjectRe: [RFC PATCH v2 0/6] Energy Aware Scheduling
Hi Leo,

On 04/17/2018 02:50 PM, Leo Yan wrote:
> Hi Dietmar,
> On Fri, Apr 06, 2018 at 04:36:01PM +0100, Dietmar Eggemann wrote:


>> 1.1 Energy Model
>> A CPU with asymmetric core capacities features cores with significantly
>> different energy and performance characteristics. As the configurations
>> can vary greatly from one SoC to another, designing an energy-efficient
>> scheduling heuristic that performs well on a broad spectrum of platforms
>> appears to be particularly hard.
>> This proposal attempts to solve this issue by providing the scheduler
>> with an energy model of the platform which enables energy impact
>> estimation of scheduling decisions in a generic way. The energy model is
>> kept very simple as it represents only the active power of CPUs at all
>> available P-states and relies on existing data in the kernel (only used
>> by the thermal subsystem so far).
>> This proposal does not include the power consumption of C-states and
>> cluster-level resources which were originally introduced in [1] since
>> firstly, their impact on task placement decisions appears to be
>> neglectable on modern asymmetric platforms and secondly, they require
>> additional infrastructure and data (e.g new DT entries).
> Seems to me, if we move forward a bit for the energy model, we can use
> more simple method by generate power consumption:
> Power(@Freq) = Power(cpu_util=100%@Freq) - Power(cpu_util=%0@Freq)
> From upper formula, the power data includes CPU and cluster level
> power (and includes dynamic power and static leakage) but this is
> quite straightforward for measurement.
> I read a bit for Quentin's slides for simplized power modeling
> experiments [1], IIUC the simplized power modeling still bases on the
> distinguished CPU and cluster c-state and p-state power data, and just
> select CPU p-state power data for scheduler. I wander if we can
> simplize the power measurement, so the power data can be generated in
> single one testing and the power data without any post processing.
> This might need more detailed experiment to support this idea, just
> want to know how about you guys think for this?
> This is a side topic for this patch series, so whatever the conclusion
> for it, I think this will not impact anything of this patch series
> implementation and upstreaming.
> [1]

The simplified Energy Model in this patch-set only contains the per-cpu
p-state power data. This allows us to only rely on the knowledge of
which OPP's (opp frequency/max frequency) we have for the individual
frequency domains and the CPU dt property 'dynamic-power-coefficient'.
This is even encapsulated in the new PM_OPP library function

Please note that this has to be redesigned since neither Rafael nor
Peter like the idea of using PM_OPP library here. But we will continue
to only use per-cpu p-state power data.


>> 30 iterations of perf bench sched messaging --pipe --thread --group G
>> --loop L with G=[1 2 4 8] and L=50000 (Hikey960)/16000 (Juno r0).
> What's the reason to select different loop number for Hikey960 and
> Juno? Based on the testing time?

The Juno r0 board has only ~0.3 of the performance of the Hikey960. We
wanted to have roughly comparable test execution time numbers. We're
only interested in the difference between running w/ and w/o this code
per platform.

 \ /
  Last update: 2018-04-17 19:22    [W:0.356 / U:6.940 seconds]
©2003-2020 Jasper Spaans|hosted at Digital Ocean and TransIP|Read the blog|Advertise on this site