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Message-ID: <alpine.DEB.2.22.394.2112180654470.3139@hadrien>
Date:   Sat, 18 Dec 2021 07:12:45 +0100 (CET)
From:   Julia Lawall <julia.lawall@...ia.fr>
To:     Francisco Jerez <currojerez@...eup.net>
cc:     Julia Lawall <julia.lawall@...ia.fr>,
        "Rafael J. Wysocki" <rafael@...nel.org>,
        Srinivas Pandruvada <srinivas.pandruvada@...ux.intel.com>,
        Len Brown <lenb@...nel.org>,
        Viresh Kumar <viresh.kumar@...aro.org>,
        Linux PM <linux-pm@...r.kernel.org>,
        Linux Kernel Mailing List <linux-kernel@...r.kernel.org>,
        Ingo Molnar <mingo@...hat.com>,
        Peter Zijlstra <peterz@...radead.org>,
        Juri Lelli <juri.lelli@...hat.com>,
        Vincent Guittot <vincent.guittot@...aro.org>
Subject: Re: cpufreq: intel_pstate: map utilization into the pstate range

> As you can see in intel_pstate.c, min_pstate is initialized on core
> platforms from MSR_PLATFORM_INFO[47:40], which is "Maximum Efficiency
> Ratio (R/O)".  However that seems to deviate massively from the most
> efficient ratio on your system, which may indicate a firmware bug, some
> sort of clock gating problem, or an issue with the way that
> intel_pstate.c processes this information.

I'm not sure to understand the bug part.  min_pstate gives the frequency
that I find as the minimum frequency when I look for the specifications of
the CPU.  Should one expect that it should be something different?

> Yup, thanks for the traces, seems like the kind of workloads that
> greatly underutilize the CPU resources.  It's not surprising to see
> schedutil give a suboptimal response in these cases, since the limiting
> factor for such latency-bound workloads that spend most of their time
> waiting is how quickly the CPU can react to some event and complete a
> short non-parallelizable computation, rather than the total amount of
> computational resources available to it.
>
> Do you get any better results while using HWP as actual governor
> (i.e. when intel_pstate is in active mode) instead of relying on
> schedutil?  With schedutil you may be able to get better results in
> combination with the deadline scheduler, though that would also need
> userspace collaboration.

I have results for Linux 5.9.  At that time, schedutil made suggestions
and the hardware made the decisions, mostly ignoring the suggestions from
schedutil.  With avrora (mostly 6 concurrent threads, tiny gaps), only 7%
of the execution time is below the turbo frequencies.  With h2 (more
threads, larger gaps), 15% of the time is below turbo frequencies.  With
xalan (larger number of threads, middle sized gaps), only 0.2% of the time
is below the turbo frequencies.

julia


>
> >
> > thanks,
> > julia
> >
> >> As you've probably realized
> >> yourself, in such a scenario the optimality assumptions of the current
> >> schedutil heuristic break down, however it doesn't seem like
> >> intel_pstate has enough information to make up for that problem, if that
> >> requires introducing another heuristic which will itself cause us to
> >> further deviate from optimality in a different set of scenarios.
> >>
> >> > julia
> >> >
> >>
> >> Regards,
> >> Francisco
> >>
> >> >
> >> >>
> >> >> > This patch scales the utilization
> >> >> > (target_perf) between the min pstate and the cap pstate instead.
> >> >> >
> >> >> > On the DaCapo (Java) benchmarks and on a few exmples of kernel compilation
> >> >> > (based on make defconfig), on two-socket machines with the above CPUs, the
> >> >> > performance is always the same or better as Linux v5.15, and the CPU and
> >> >> > RAM energy consumption is likewise always the same or better (one
> >> >> > exception: zxing-eval on the 5128 uses a little more energy).
> >> >> >
> >> >> > 6130:
> >> >> >
> >> >> > Performance (sec):
> >> >> >                 v5.15           with this patch (improvement)
> >> >> > avrora          77.5773         56.4090 (1.38)
> >> >> > batik-eval      113.1173        112.4135 (1.01)
> >> >> > biojava-eval    196.6533        196.7943 (1.00)
> >> >> > cassandra-eval  62.6638         59.2800 (1.06)
> >> >> > eclipse-eval    218.5988        210.0139 (1.04)
> >> >> > fop             3.5537          3.4281 (1.04)
> >> >> > graphchi-evalN  13.8668         10.3411 (1.34)
> >> >> > h2              75.5018         62.2993 (1.21)
> >> >> > jme-eval        94.9531         89.5722 (1.06)
> >> >> > jython          23.5789         23.0603 (1.02)
> >> >> > kafka-eval      60.2784         59.2057 (1.02)
> >> >> > luindex         5.3537          5.1190 (1.05)
> >> >> > lusearch-fix    3.5956          3.3628 (1.07)
> >> >> > lusearch        3.5396          3.5204 (1.01)
> >> >> > pmd             13.3505         10.8795 (1.23)
> >> >> > sunflow         7.5932          7.4899 (1.01)
> >> >> > tomcat-eval     39.6568         31.4844 (1.26)
> >> >> > tradebeans      118.9918        99.3932 (1.20)
> >> >> > tradesoap-eval  56.9113         54.7567 (1.04)
> >> >> > tradesoap       50.7779         44.5169 (1.14)
> >> >> > xalan           5.0711          4.8879 (1.04)
> >> >> > zxing-eval      10.5532         10.2435 (1.03)
> >> >> >
> >> >> > make            45.5977         45.3454 (1.01)
> >> >> > make sched      3.4318          3.3450 (1.03)
> >> >> > make fair.o     2.9611          2.8464 (1.04)
> >> >> >
> >> >> > CPU energy consumption (J):
> >> >> >
> >> >> > avrora          4740.4813       3585.5843 (1.32)
> >> >> > batik-eval      13361.34        13278.74 (1.01)
> >> >> > biojava-eval    21608.70        21652.94 (1.00)
> >> >> > cassandra-eval  3037.6907       2891.8117 (1.05)
> >> >> > eclipse-eval    23528.15        23198.36 (1.01)
> >> >> > fop             455.7363        441.6443 (1.03)
> >> >> > graphchi-eval   999.9220        971.5633 (1.03)
> >> >> > h2              5451.3093       4929.8383 (1.11)
> >> >> > jme-eval        5343.7790       5143.8463 (1.04)
> >> >> > jython          2685.3790       2623.1950 (1.02)
> >> >> > kafka-eval      2715.6047       2548.7220 (1.07)
> >> >> > luindex         597.7587        571.0387 (1.05)
> >> >> > lusearch-fix    714.0340        692.4727 (1.03)
> >> >> > lusearch        718.4863        704.3650 (1.02)
> >> >> > pmd             1627.6377       1497.5437 (1.09)
> >> >> > sunflow         1563.5173       1514.6013 (1.03)
> >> >> > tomcat-eval     4740.1603       4539.1503 (1.04)
> >> >> > tradebeans      8331.2260       7482.3737 (1.11)
> >> >> > tradesoap-eval  6610.1040       6426.7077 (1.03)
> >> >> > tradesoap       5641.9300       5544.3517 (1.02)
> >> >> > xalan           1072.0363       1065.7957 (1.01)
> >> >> > zxing-eval      2200.1883       2174.1137 (1.01)
> >> >> >
> >> >> > make            9788.9290       9777.5823 (1.00)
> >> >> > make sched      501.0770        495.0600 (1.01)
> >> >> > make fair.o     363.4570        352.8670 (1.03)
> >> >> >
> >> >> > RAM energy consumption (J):
> >> >> >
> >> >> > avrora          2508.5553       1844.5977 (1.36)
> >> >> > batik-eval      5627.3327       5603.1820 (1.00)
> >> >> > biojava-eval    9371.1417       9351.1543 (1.00)
> >> >> > cassandra-eval  1398.0567       1289.8317 (1.08)
> >> >> > eclipse-eval    10193.28        9952.3543 (1.02)
> >> >> > fop             189.1927        184.0620 (1.03)
> >> >> > graphchi-eval   539.3947        447.4557 (1.21)
> >> >> > h2              2771.0573       2432.2587 (1.14)
> >> >> > jme-eval        2702.4030       2504.0783 (1.08)
> >> >> > jython          1135.7317       1114.5190 (1.02)
> >> >> > kafka-eval      1320.6840       1220.6867 (1.08)
> >> >> > luindex         246.6597        237.1593 (1.04)
> >> >> > lusearch-fix    294.4317        282.2193 (1.04)
> >> >> > lusearch        295.5400        284.3890 (1.04)
> >> >> > pmd             721.7020        643.1280 (1.12)
> >> >> > sunflow         568.6710        549.3780 (1.04)
> >> >> > tomcat-eval     2305.8857       1995.8843 (1.16)
> >> >> > tradebeans      4323.5243       3749.7033 (1.15)
> >> >> > tradesoap-eval  2862.8047       2783.5733 (1.03)
> >> >> > tradesoap       2717.3900       2519.9567 (1.08)
> >> >> > xalan           430.6100        418.5797 (1.03)
> >> >> > zxing-eval      732.2507        710.9423 (1.03)
> >> >> >
> >> >> > make            3362.8837       3356.2587 (1.00)
> >> >> > make sched      191.7917        188.8863 (1.02)
> >> >> > make fair.o     149.6850        145.8273 (1.03)
> >> >> >
> >> >> > 5128:
> >> >> >
> >> >> > Performance (sec):
> >> >> >
> >> >> > avrora          62.0511         43.9240 (1.41)
> >> >> > batik-eval      111.6393        110.1999 (1.01)
> >> >> > biojava-eval    241.4400        238.7388 (1.01)
> >> >> > cassandra-eval  62.0185         58.9052 (1.05)
> >> >> > eclipse-eval    240.9488        232.8944 (1.03)
> >> >> > fop             3.8318          3.6408 (1.05)
> >> >> > graphchi-eval   13.3911         10.4670 (1.28)
> >> >> > h2              75.3658         62.8218 (1.20)
> >> >> > jme-eval        95.0131         89.5635 (1.06)
> >> >> > jython          28.1397         27.6802 (1.02)
> >> >> > kafka-eval      60.4817         59.4780 (1.02)
> >> >> > luindex         5.1994          4.9587 (1.05)
> >> >> > lusearch-fix    3.8448          3.6519 (1.05)
> >> >> > lusearch        3.8928          3.7068 (1.05)
> >> >> > pmd             13.0990         10.8008 (1.21)
> >> >> > sunflow         7.7983          7.8569 (0.99)
> >> >> > tomcat-eval     39.2064         31.7629 (1.23)
> >> >> > tradebeans      120.8676        100.9113 (1.20)
> >> >> > tradesoap-eval  65.5552         63.3493 (1.03)
> >> >> > xalan           5.4463          5.3576 (1.02)
> >> >> > zxing-eval      9.8611          9.9692 (0.99)
> >> >> >
> >> >> > make            43.1852         43.1285 (1.00)
> >> >> > make sched      3.2181          3.1706 (1.01)
> >> >> > make fair.o     2.7584          2.6615 (1.04)
> >> >> >
> >> >> > CPU energy consumption (J):
> >> >> >
> >> >> > avrora          3979.5297       3049.3347 (1.31)
> >> >> > batik-eval      12339.59        12413.41 (0.99)
> >> >> > biojava-eval    23935.18        23931.61 (1.00)
> >> >> > cassandra-eval  3552.2753       3380.4860 (1.05)
> >> >> > eclipse-eval    24186.38        24076.57 (1.00)
> >> >> > fop             441.0607        442.9647 (1.00)
> >> >> > graphchi-eval   1021.1323       964.4800 (1.06)
> >> >> > h2              5484.9667       4901.9067 (1.12)
> >> >> > jme-eval        6167.5287       5909.5767 (1.04)
> >> >> > jython          2956.7150       2986.3680 (0.99)
> >> >> > kafka-eval      3229.9333       3197.7743 (1.01)
> >> >> > luindex         537.0007        533.9980 (1.01)
> >> >> > lusearch-fix    720.1830        699.2343 (1.03)
> >> >> > lusearch        708.8190        700.7023 (1.01)
> >> >> > pmd             1539.7463       1398.1850 (1.10)
> >> >> > sunflow         1533.3367       1497.2863 (1.02)
> >> >> > tomcat-eval     4551.9333       4289.2553 (1.06)
> >> >> > tradebeans      8527.2623       7570.2933 (1.13)
> >> >> > tradesoap-eval  6849.3213       6750.9687 (1.01)
> >> >> > xalan           1013.2747       1019.1217 (0.99)
> >> >> > zxing-eval      1852.9077       1943.1753 (0.95)
> >> >> >
> >> >> > make            9257.5547       9262.5993 (1.00)
> >> >> > make sched      438.7123        435.9133 (1.01)
> >> >> > make fair.o     315.6550        312.2280 (1.01)
> >> >> >
> >> >> > RAM energy consumption (J):
> >> >> >
> >> >> > avrora          16309.86        11458.08 (1.42)
> >> >> > batik-eval      30107.11        29891.58 (1.01)
> >> >> > biojava-eval    64290.01        63941.71 (1.01)
> >> >> > cassandra-eval  13240.04        12403.19 (1.07)
> >> >> > eclipse-eval    64188.41        62008.35 (1.04)
> >> >> > fop             1052.2457       996.0907 (1.06)
> >> >> > graphchi-eval   3622.5130       2856.1983 (1.27)
> >> >> > h2              19965.58        16624.08 (1.20)
> >> >> > jme-eval        21777.02        20211.06 (1.08)
> >> >> > jython          7515.3843       7396.6437 (1.02)
> >> >> > kafka-eval      12868.39        12577.32 (1.02)
> >> >> > luindex         1387.7263       1328.8073 (1.04)
> >> >> > lusearch-fix    1313.1220       1238.8813 (1.06)
> >> >> > lusearch        1303.5597       1245.4130 (1.05)
> >> >> > pmd             3650.6697       3049.8567 (1.20)
> >> >> > sunflow         2460.8907       2380.3773 (1.03)
> >> >> > tomcat-eval     11199.61        9232.8367 (1.21)
> >> >> > tradebeans      32385.99        26901.40 (1.20)
> >> >> > tradesoap-eval  17691.01        17006.95 (1.04)
> >> >> > xalan           1783.7290       1735.1937 (1.03)
> >> >> > zxing-eval      2812.9710       2952.2933 (0.95)
> >> >> >
> >> >> > make            13247.47        13258.64 (1.00)
> >> >> > make sched      885.7790        877.1667 (1.01)
> >> >> > make fair.o     741.2473        723.6313 (1.02)
> >> >>
> >> >> So the number look better after the change, because it makes the
> >> >> driver ask the hardware for slightly more performance than it is asked
> >> >> for by the governor.
> >> >>
> >> >> >
> >> >> > Signed-off-by: Julia Lawall <julia.lawall@...ia.fr>
> >> >> >
> >> >> > ---
> >> >> >
> >> >> > min_pstate is defined in terms of cpu->pstate.min_pstate and
> >> >> > cpu->min_perf_ratio.  Maybe one of these values should be used instead.
> >> >> > Likewise, perhaps cap_pstate should be max_pstate?
> >> >>
> >> >> I'm not sure if I understand this remark.  cap_pstate is the max
> >> >> performance level of the CPU and max_pstate is the current limit
> >> >> imposed by the framework.  They are different things.
> >> >>
> >> >> >
> >> >> > diff --git a/drivers/cpufreq/intel_pstate.c b/drivers/cpufreq/intel_pstate.c
> >> >> > index 8c176b7dae41..ba6a48959754 100644
> >> >> > --- a/drivers/cpufreq/intel_pstate.c
> >> >> > +++ b/drivers/cpufreq/intel_pstate.c
> >> >> > @@ -2789,10 +2789,6 @@ static void intel_cpufreq_adjust_perf(unsigned int cpunum,
> >> >> >
> >> >> >         /* Optimization: Avoid unnecessary divisions. */
> >> >> >
> >> >> > -       target_pstate = cap_pstate;
> >> >> > -       if (target_perf < capacity)
> >> >> > -               target_pstate = DIV_ROUND_UP(cap_pstate * target_perf, capacity);
> >> >> > -
> >> >> >         min_pstate = cap_pstate;
> >> >> >         if (min_perf < capacity)
> >> >> >                 min_pstate = DIV_ROUND_UP(cap_pstate * min_perf, capacity);
> >> >> > @@ -2807,6 +2803,10 @@ static void intel_cpufreq_adjust_perf(unsigned int cpunum,
> >> >> >         if (max_pstate < min_pstate)
> >> >> >                 max_pstate = min_pstate;
> >> >> >
> >> >> > +       target_pstate = cap_pstate;
> >> >> > +       if (target_perf < capacity)
> >> >> > +               target_pstate = DIV_ROUND_UP((cap_pstate - min_pstate) * target_perf, capacity) + min_pstate;
> >> >>
> >> >> So the driver is asked by the governor to deliver the fraction of the
> >> >> max performance (cap_pstate) given by the target_perf / capacity ratio
> >> >> with the floor given by min_perf / capacity.  It cannot turn around
> >> >> and do something else, because it thinks it knows better.
> >> >>
> >> >> > +
> >> >> >         target_pstate = clamp_t(int, target_pstate, min_pstate, max_pstate);
> >> >> >
> >> >> >         intel_cpufreq_hwp_update(cpu, min_pstate, max_pstate, target_pstate, true);
> >> >>
> >>
>

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