Re: [Patch v4 0/6] Introduce Thermal Pressure

Daniel Lezcano
2019-10-29T15:34:19Z

Hi Thara,

On 22/10/2019 22:34, Thara Gopinath wrote:
> Thermal governors can respond to an overheat event of a cpu by
> capping the cpu's maximum possible frequency. This in turn
> means that the maximum available compute capacity of the
> cpu is restricted. But today in the kernel, task scheduler is
> not notified of capping of maximum frequency of a cpu.
> In other words, scheduler is unware of maximum capacity
> restrictions placed on a cpu due to thermal activity.
> This patch series attempts to address this issue.
> The benefits identified are better task placement among available
> cpus in event of overheating which in turn leads to better
> performance numbers.
>
> The reduction in the maximum possible capacity of a cpu due to a
> thermal event can be considered as thermal pressure. Instantaneous
> thermal pressure is hard to record and can sometime be erroneous
> as there can be mismatch between the actual capping of capacity
> and scheduler recording it. Thus solution is to have a weighted
> average per cpu value for thermal pressure over time.
> The weight reflects the amount of time the cpu has spent at a
> capped maximum frequency. Since thermal pressure is recorded as
> an average, it must be decayed periodically. Exisiting algorithm
> in the kernel scheduler pelt framework is re-used to calculate
> the weighted average. This patch series also defines a sysctl
> inerface to allow for a configurable decay period.
>
> Regarding testing, basic build, boot and sanity testing have been
> performed on db845c platform with debian file system.
> Further, dhrystone and hackbench tests have been
> run with the thermal pressure algorithm. During testing, due to
> constraints of step wise governor in dealing with big little systems,
> trip point 0 temperature was made assymetric between cpus in little
> cluster and big cluster; the idea being that
> big core will heat up and cpu cooling device will throttle the
> frequency of the big cores faster, there by limiting the maximum available
> capacity and the scheduler will spread out tasks to little cores as well.
>
> Test Results
>
> Hackbench: 1 group , 30000 loops, 10 runs
> Result SD
> (Secs) (% of mean)
> No Thermal Pressure 14.03 2.69%
> Thermal Pressure PELT Algo. Decay : 32 ms 13.29 0.56%
> Thermal Pressure PELT Algo. Decay : 64 ms 12.57 1.56%
> Thermal Pressure PELT Algo. Decay : 128 ms 12.71 1.04%
> Thermal Pressure PELT Algo. Decay : 256 ms 12.29 1.42%
> Thermal Pressure PELT Algo. Decay : 512 ms 12.42 1.15%
>
> Dhrystone Run Time : 20 threads, 3000 MLOOPS
> Result SD
> (Secs) (% of mean)
> No Thermal Pressure 9.452 4.49%
> Thermal Pressure PELT Algo. Decay : 32 ms 8.793 5.30%
> Thermal Pressure PELT Algo. Decay : 64 ms 8.981 5.29%
> Thermal Pressure PELT Algo. Decay : 128 ms 8.647 6.62%
> Thermal Pressure PELT Algo. Decay : 256 ms 8.774 6.45%
> Thermal Pressure PELT Algo. Decay : 512 ms 8.603 5.41%

I took the opportunity to try glmark2 on the db845c platform with the
default decay and got the following glmark2 scores:

Without thermal pressure:

# NumSamples = 9; Min = 790.00; Max = 805.00
# Mean = 794.888889; Variance = 19.209877; SD = 4.382907; Median 794.000000
# each ∎ represents a count of 1
790.0000 - 791.5000 [ 2]: ∎∎
791.5000 - 793.0000 [ 2]: ∎∎
793.0000 - 794.5000 [ 2]: ∎∎
794.5000 - 796.0000 [ 1]: ∎
796.0000 - 797.5000 [ 0]:
797.5000 - 799.0000 [ 1]: ∎
799.0000 - 800.5000 [ 0]:
800.5000 - 802.0000 [ 0]:
802.0000 - 803.5000 [ 0]:
803.5000 - 805.0000 [ 1]: ∎

With thermal pressure:

# NumSamples = 9; Min = 933.00; Max = 960.00
# Mean = 940.777778; Variance = 64.172840; SD = 8.010795; Median 937.000000
# each ∎ represents a count of 1
933.0000 - 935.7000 [ 3]: ∎∎∎
935.7000 - 938.4000 [ 2]: ∎∎
938.4000 - 941.1000 [ 2]: ∎∎
941.1000 - 943.8000 [ 0]:
943.8000 - 946.5000 [ 0]:
946.5000 - 949.2000 [ 1]: ∎
949.2000 - 951.9000 [ 0]:
951.9000 - 954.6000 [ 0]:
954.6000 - 957.3000 [ 0]:
957.3000 - 960.0000 [ 1]: ∎

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