kernel/linux.git/include/linux/sched/topology.h, branch v6.2.2

sched/fair: Introduce SIS_UTIL to search idle CPU based on sum of util_avg

2022-06-28T07:08:30+00:00

[Problem Statement] select_idle_cpu() might spend too much time searching for an idle CPU, when the system is overloaded. The following histogram is the time spent in select_idle_cpu(), when running 224 instances of netperf on a system with 112 CPUs per LLC domain: @usecs: [0] 533 | | [1] 5495 | | [2, 4) 12008 | | [4, 8) 239252 | | [8, 16) 4041924 |@@@@@@@@@@@@@@ | [16, 32) 12357398 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ | [32, 64) 14820255 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@| [64, 128) 13047682 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ | [128, 256) 8235013 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@ | [256, 512) 4507667 |@@@@@@@@@@@@@@@ | [512, 1K) 2600472 |@@@@@@@@@ | [1K, 2K) 927912 |@@@ | [2K, 4K) 218720 | | [4K, 8K) 98161 | | [8K, 16K) 37722 | | [16K, 32K) 6715 | | [32K, 64K) 477 | | [64K, 128K) 7 | | netperf latency usecs: ======= case load Lat_99th std% TCP_RR thread-224 257.39 ( 0.21) The time spent in select_idle_cpu() is visible to netperf and might have a negative impact. [Symptom analysis] The patch [1] from Mel Gorman has been applied to track the efficiency of select_idle_sibling. Copy the indicators here: SIS Search Efficiency(se_eff%): A ratio expressed as a percentage of runqueues scanned versus idle CPUs found. A 100% efficiency indicates that the target, prev or recent CPU of a task was idle at wakeup. The lower the efficiency, the more runqueues were scanned before an idle CPU was found. SIS Domain Search Efficiency(dom_eff%): Similar, except only for the slower SIS patch. SIS Fast Success Rate(fast_rate%): Percentage of SIS that used target, prev or recent CPUs. SIS Success rate(success_rate%): Percentage of scans that found an idle CPU. The test is based on Aubrey's schedtests tool, including netperf, hackbench, schbench and tbench. Test on vanilla kernel: schedstat_parse.py -f netperf_vanilla.log case load se_eff% dom_eff% fast_rate% success_rate% TCP_RR 28 threads 99.978 18.535 99.995 100.000 TCP_RR 56 threads 99.397 5.671 99.964 100.000 TCP_RR 84 threads 21.721 6.818 73.632 100.000 TCP_RR 112 threads 12.500 5.533 59.000 100.000 TCP_RR 140 threads 8.524 4.535 49.020 100.000 TCP_RR 168 threads 6.438 3.945 40.309 99.999 TCP_RR 196 threads 5.397 3.718 32.320 99.982 TCP_RR 224 threads 4.874 3.661 25.775 99.767 UDP_RR 28 threads 99.988 17.704 99.997 100.000 UDP_RR 56 threads 99.528 5.977 99.970 100.000 UDP_RR 84 threads 24.219 6.992 76.479 100.000 UDP_RR 112 threads 13.907 5.706 62.538 100.000 UDP_RR 140 threads 9.408 4.699 52.519 100.000 UDP_RR 168 threads 7.095 4.077 44.352 100.000 UDP_RR 196 threads 5.757 3.775 35.764 99.991 UDP_RR 224 threads 5.124 3.704 28.748 99.860 schedstat_parse.py -f schbench_vanilla.log (each group has 28 tasks) case load se_eff% dom_eff% fast_rate% success_rate% normal 1 mthread 99.152 6.400 99.941 100.000 normal 2 mthreads 97.844 4.003 99.908 100.000 normal 3 mthreads 96.395 2.118 99.917 99.998 normal 4 mthreads 55.288 1.451 98.615 99.804 normal 5 mthreads 7.004 1.870 45.597 61.036 normal 6 mthreads 3.354 1.346 20.777 34.230 normal 7 mthreads 2.183 1.028 11.257 21.055 normal 8 mthreads 1.653 0.825 7.849 15.549 schedstat_parse.py -f hackbench_vanilla.log (each group has 28 tasks) case load se_eff% dom_eff% fast_rate% success_rate% process-pipe 1 group 99.991 7.692 99.999 100.000 process-pipe 2 groups 99.934 4.615 99.997 100.000 process-pipe 3 groups 99.597 3.198 99.987 100.000 process-pipe 4 groups 98.378 2.464 99.958 100.000 process-pipe 5 groups 27.474 3.653 89.811 99.800 process-pipe 6 groups 20.201 4.098 82.763 99.570 process-pipe 7 groups 16.423 4.156 77.398 99.316 process-pipe 8 groups 13.165 3.920 72.232 98.828 process-sockets 1 group 99.977 5.882 99.999 100.000 process-sockets 2 groups 99.927 5.505 99.996 100.000 process-sockets 3 groups 99.397 3.250 99.980 100.000 process-sockets 4 groups 79.680 4.258 98.864 99.998 process-sockets 5 groups 7.673 2.503 63.659 92.115 process-sockets 6 groups 4.642 1.584 58.946 88.048 process-sockets 7 groups 3.493 1.379 49.816 81.164 process-sockets 8 groups 3.015 1.407 40.845 75.500 threads-pipe 1 group 99.997 0.000 100.000 100.000 threads-pipe 2 groups 99.894 2.932 99.997 100.000 threads-pipe 3 groups 99.611 4.117 99.983 100.000 threads-pipe 4 groups 97.703 2.624 99.937 100.000 threads-pipe 5 groups 22.919 3.623 87.150 99.764 threads-pipe 6 groups 18.016 4.038 80.491 99.557 threads-pipe 7 groups 14.663 3.991 75.239 99.247 threads-pipe 8 groups 12.242 3.808 70.651 98.644 threads-sockets 1 group 99.990 6.667 99.999 100.000 threads-sockets 2 groups 99.940 5.114 99.997 100.000 threads-sockets 3 groups 99.469 4.115 99.977 100.000 threads-sockets 4 groups 87.528 4.038 99.400 100.000 threads-sockets 5 groups 6.942 2.398 59.244 88.337 threads-sockets 6 groups 4.359 1.954 49.448 87.860 threads-sockets 7 groups 2.845 1.345 41.198 77.102 threads-sockets 8 groups 2.871 1.404 38.512 74.312 schedstat_parse.py -f tbench_vanilla.log case load se_eff% dom_eff% fast_rate% success_rate% loopback 28 threads 99.976 18.369 99.995 100.000 loopback 56 threads 99.222 7.799 99.934 100.000 loopback 84 threads 19.723 6.819 70.215 100.000 loopback 112 threads 11.283 5.371 55.371 99.999 loopback 140 threads 0.000 0.000 0.000 0.000 loopback 168 threads 0.000 0.000 0.000 0.000 loopback 196 threads 0.000 0.000 0.000 0.000 loopback 224 threads 0.000 0.000 0.000 0.000 According to the test above, if the system becomes busy, the SIS Search Efficiency(se_eff%) drops significantly. Although some benchmarks would finally find an idle CPU(success_rate% = 100%), it is doubtful whether it is worth it to search the whole LLC domain. [Proposal] It would be ideal to have a crystal ball to answer this question: How many CPUs must a wakeup path walk down, before it can find an idle CPU? Many potential metrics could be used to predict the number. One candidate is the sum of util_avg in this LLC domain. The benefit of choosing util_avg is that it is a metric of accumulated historic activity, which seems to be smoother than instantaneous metrics (such as rq->nr_running). Besides, choosing the sum of util_avg would help predict the load of the LLC domain more precisely, because SIS_PROP uses one CPU's idle time to estimate the total LLC domain idle time. In summary, the lower the util_avg is, the more select_idle_cpu() should scan for idle CPU, and vice versa. When the sum of util_avg in this LLC domain hits 85% or above, the scan stops. The reason to choose 85% as the threshold is that this is the imbalance_pct(117) when a LLC sched group is overloaded. Introduce the quadratic function: y = SCHED_CAPACITY_SCALE - p * x^2 and y'= y / SCHED_CAPACITY_SCALE x is the ratio of sum_util compared to the CPU capacity: x = sum_util / (llc_weight * SCHED_CAPACITY_SCALE) y' is the ratio of CPUs to be scanned in the LLC domain, and the number of CPUs to scan is calculated by: nr_scan = llc_weight * y' Choosing quadratic function is because: [1] Compared to the linear function, it scans more aggressively when the sum_util is low. [2] Compared to the exponential function, it is easier to calculate. [3] It seems that there is no accurate mapping between the sum of util_avg and the number of CPUs to be scanned. Use heuristic scan for now. For a platform with 112 CPUs per LLC, the number of CPUs to scan is: sum_util% 0 5 15 25 35 45 55 65 75 85 86 ... scan_nr 112 111 108 102 93 81 65 47 25 1 0 ... For a platform with 16 CPUs per LLC, the number of CPUs to scan is: sum_util% 0 5 15 25 35 45 55 65 75 85 86 ... scan_nr 16 15 15 14 13 11 9 6 3 0 0 ... Furthermore, to minimize the overhead of calculating the metrics in select_idle_cpu(), borrow the statistics from periodic load balance. As mentioned by Abel, on a platform with 112 CPUs per LLC, the sum_util calculated by periodic load balance after 112 ms would decay to about 0.5 * 0.5 * 0.5 * 0.7 = 8.75%, thus bringing a delay in reflecting the latest utilization. But it is a trade-off. Checking the util_avg in newidle load balance would be more frequent, but it brings overhead - multiple CPUs write/read the per-LLC shared variable and introduces cache contention. Tim also mentioned that, it is allowed to be non-optimal in terms of scheduling for the short-term variations, but if there is a long-term trend in the load behavior, the scheduler can adjust for that. When SIS_UTIL is enabled, the select_idle_cpu() uses the nr_scan calculated by SIS_UTIL instead of the one from SIS_PROP. As Peter and Mel suggested, SIS_UTIL should be enabled by default. This patch is based on the util_avg, which is very sensitive to the CPU frequency invariance. There is an issue that, when the max frequency has been clamp, the util_avg would decay insanely fast when the CPU is idle. Commit addca285120b ("cpufreq: intel_pstate: Handle no_turbo in frequency invariance") could be used to mitigate this symptom, by adjusting the arch_max_freq_ratio when turbo is disabled. But this issue is still not thoroughly fixed, because the current code is unaware of the user-specified max CPU frequency. [Test result] netperf and tbench were launched with 25% 50% 75% 100% 125% 150% 175% 200% of CPU number respectively. Hackbench and schbench were launched by 1, 2 ,4, 8 groups. Each test lasts for 100 seconds and repeats 3 times. The following is the benchmark result comparison between baseline:vanilla v5.19-rc1 and compare:patched kernel. Positive compare% indicates better performance. Each netperf test is a: netperf -4 -H 127.0.1 -t TCP/UDP_RR -c -C -l 100 netperf.throughput ======= case load baseline(std%) compare%( std%) TCP_RR 28 threads 1.00 ( 0.34) -0.16 ( 0.40) TCP_RR 56 threads 1.00 ( 0.19) -0.02 ( 0.20) TCP_RR 84 threads 1.00 ( 0.39) -0.47 ( 0.40) TCP_RR 112 threads 1.00 ( 0.21) -0.66 ( 0.22) TCP_RR 140 threads 1.00 ( 0.19) -0.69 ( 0.19) TCP_RR 168 threads 1.00 ( 0.18) -0.48 ( 0.18) TCP_RR 196 threads 1.00 ( 0.16) +194.70 ( 16.43) TCP_RR 224 threads 1.00 ( 0.16) +197.30 ( 7.85) UDP_RR 28 threads 1.00 ( 0.37) +0.35 ( 0.33) UDP_RR 56 threads 1.00 ( 11.18) -0.32 ( 0.21) UDP_RR 84 threads 1.00 ( 1.46) -0.98 ( 0.32) UDP_RR 112 threads 1.00 ( 28.85) -2.48 ( 19.61) UDP_RR 140 threads 1.00 ( 0.70) -0.71 ( 14.04) UDP_RR 168 threads 1.00 ( 14.33) -0.26 ( 11.16) UDP_RR 196 threads 1.00 ( 12.92) +186.92 ( 20.93) UDP_RR 224 threads 1.00 ( 11.74) +196.79 ( 18.62) Take the 224 threads as an example, the SIS search metrics changes are illustrated below: vanilla patched 4544492 +237.5% 15338634 sched_debug.cpu.sis_domain_search.avg 38539 +39686.8% 15333634 sched_debug.cpu.sis_failed.avg 128300000 -87.9% 15551326 sched_debug.cpu.sis_scanned.avg 5842896 +162.7% 15347978 sched_debug.cpu.sis_search.avg There is -87.9% less CPU scans after patched, which indicates lower overhead. Besides, with this patch applied, there is -13% less rq lock contention in perf-profile.calltrace.cycles-pp._raw_spin_lock.raw_spin_rq_lock_nested .try_to_wake_up.default_wake_function.woken_wake_function. This might help explain the performance improvement - Because this patch allows the waking task to remain on the previous CPU, rather than grabbing other CPUs' lock. Each hackbench test is a: hackbench -g $job --process/threads --pipe/sockets -l 1000000 -s 100 hackbench.throughput ========= case load baseline(std%) compare%( std%) process-pipe 1 group 1.00 ( 1.29) +0.57 ( 0.47) process-pipe 2 groups 1.00 ( 0.27) +0.77 ( 0.81) process-pipe 4 groups 1.00 ( 0.26) +1.17 ( 0.02) process-pipe 8 groups 1.00 ( 0.15) -4.79 ( 0.02) process-sockets 1 group 1.00 ( 0.63) -0.92 ( 0.13) process-sockets 2 groups 1.00 ( 0.03) -0.83 ( 0.14) process-sockets 4 groups 1.00 ( 0.40) +5.20 ( 0.26) process-sockets 8 groups 1.00 ( 0.04) +3.52 ( 0.03) threads-pipe 1 group 1.00 ( 1.28) +0.07 ( 0.14) threads-pipe 2 groups 1.00 ( 0.22) -0.49 ( 0.74) threads-pipe 4 groups 1.00 ( 0.05) +1.88 ( 0.13) threads-pipe 8 groups 1.00 ( 0.09) -4.90 ( 0.06) threads-sockets 1 group 1.00 ( 0.25) -0.70 ( 0.53) threads-sockets 2 groups 1.00 ( 0.10) -0.63 ( 0.26) threads-sockets 4 groups 1.00 ( 0.19) +11.92 ( 0.24) threads-sockets 8 groups 1.00 ( 0.08) +4.31 ( 0.11) Each tbench test is a: tbench -t 100 $job 127.0.0.1 tbench.throughput ====== case load baseline(std%) compare%( std%) loopback 28 threads 1.00 ( 0.06) -0.14 ( 0.09) loopback 56 threads 1.00 ( 0.03) -0.04 ( 0.17) loopback 84 threads 1.00 ( 0.05) +0.36 ( 0.13) loopback 112 threads 1.00 ( 0.03) +0.51 ( 0.03) loopback 140 threads 1.00 ( 0.02) -1.67 ( 0.19) loopback 168 threads 1.00 ( 0.38) +1.27 ( 0.27) loopback 196 threads 1.00 ( 0.11) +1.34 ( 0.17) loopback 224 threads 1.00 ( 0.11) +1.67 ( 0.22) Each schbench test is a: schbench -m $job -t 28 -r 100 -s 30000 -c 30000 schbench.latency_90%_us ======== case load baseline(std%) compare%( std%) normal 1 mthread 1.00 ( 31.22) -7.36 ( 20.25)* normal 2 mthreads 1.00 ( 2.45) -0.48 ( 1.79) normal 4 mthreads 1.00 ( 1.69) +0.45 ( 0.64) normal 8 mthreads 1.00 ( 5.47) +9.81 ( 14.28) *Consider the Standard Deviation, this -7.36% regression might not be valid. Also, a OLTP workload with a commercial RDBMS has been tested, and there is no significant change. There were concerns that unbalanced tasks among CPUs would cause problems. For example, suppose the LLC domain is composed of 8 CPUs, and 7 tasks are bound to CPU0~CPU6, while CPU7 is idle: CPU0 CPU1 CPU2 CPU3 CPU4 CPU5 CPU6 CPU7 util_avg 1024 1024 1024 1024 1024 1024 1024 0 Since the util_avg ratio is 87.5%( = 7/8 ), which is higher than 85%, select_idle_cpu() will not scan, thus CPU7 is undetected during scan. But according to Mel, it is unlikely the CPU7 will be idle all the time because CPU7 could pull some tasks via CPU_NEWLY_IDLE. lkp(kernel test robot) has reported a regression on stress-ng.sock on a very busy system. According to the sched_debug statistics, it might be caused by SIS_UTIL terminates the scan and chooses a previous CPU earlier, and this might introduce more context switch, especially involuntary preemption, which impacts a busy stress-ng. This regression has shown that, not all benchmarks in every scenario benefit from idle CPU scan limit, and it needs further investigation. Besides, there is slight regression in hackbench's 16 groups case when the LLC domain has 16 CPUs. Prateek mentioned that we should scan aggressively in an LLC domain with 16 CPUs. Because the cost to search for an idle one among 16 CPUs is negligible. The current patch aims to propose a generic solution and only considers the util_avg. Something like the below could be applied on top of the current patch to fulfill the requirement: if (llc_weight <= 16) nr_scan = nr_scan * 32 / llc_weight; For LLC domain with 16 CPUs, the nr_scan will be expanded to 2 times large. The smaller the CPU number this LLC domain has, the larger nr_scan will be expanded. This needs further investigation. There is also ongoing work[2] from Abel to filter out the busy CPUs during wakeup, to further speed up the idle CPU scan. And it could be a following-up optimization on top of this change. Suggested-by: Tim Chen Suggested-by: Peter Zijlstra Signed-off-by: Chen Yu Signed-off-by: Peter Zijlstra (Intel) Tested-by: Yicong Yang Tested-by: Mohini Narkhede Tested-by: K Prateek Nayak Link: https://lore.kernel.org/r/20220612163428.849378-1-yu.c.chen@intel.com

sched/fair: Adjust the allowed NUMA imbalance when SD_NUMA spans multiple LLCs

2022-02-11T22:30:08+00:00

Commit 7d2b5dd0bcc4 ("sched/numa: Allow a floating imbalance between NUMA nodes") allowed an imbalance between NUMA nodes such that communicating tasks would not be pulled apart by the load balancer. This works fine when there is a 1:1 relationship between LLC and node but can be suboptimal for multiple LLCs if independent tasks prematurely use CPUs sharing cache. Zen* has multiple LLCs per node with local memory channels and due to the allowed imbalance, it's far harder to tune some workloads to run optimally than it is on hardware that has 1 LLC per node. This patch allows an imbalance to exist up to the point where LLCs should be balanced between nodes. On a Zen3 machine running STREAM parallelised with OMP to have on instance per LLC the results and without binding, the results are 5.17.0-rc0 5.17.0-rc0 vanilla sched-numaimb-v6 MB/sec copy-16 162596.94 ( 0.00%) 580559.74 ( 257.05%) MB/sec scale-16 136901.28 ( 0.00%) 374450.52 ( 173.52%) MB/sec add-16 157300.70 ( 0.00%) 564113.76 ( 258.62%) MB/sec triad-16 151446.88 ( 0.00%) 564304.24 ( 272.61%) STREAM can use directives to force the spread if the OpenMP is new enough but that doesn't help if an application uses threads and it's not known in advance how many threads will be created. Coremark is a CPU and cache intensive benchmark parallelised with threads. When running with 1 thread per core, the vanilla kernel allows threads to contend on cache. With the patch; 5.17.0-rc0 5.17.0-rc0 vanilla sched-numaimb-v5 Min Score-16 368239.36 ( 0.00%) 389816.06 ( 5.86%) Hmean Score-16 388607.33 ( 0.00%) 427877.08 * 10.11%* Max Score-16 408945.69 ( 0.00%) 481022.17 ( 17.62%) Stddev Score-16 15247.04 ( 0.00%) 24966.82 ( -63.75%) CoeffVar Score-16 3.92 ( 0.00%) 5.82 ( -48.48%) It can also make a big difference for semi-realistic workloads like specjbb which can execute arbitrary numbers of threads without advance knowledge of how they should be placed. Even in cases where the average performance is neutral, the results are more stable. 5.17.0-rc0 5.17.0-rc0 vanilla sched-numaimb-v6 Hmean tput-1 71631.55 ( 0.00%) 73065.57 ( 2.00%) Hmean tput-8 582758.78 ( 0.00%) 556777.23 ( -4.46%) Hmean tput-16 1020372.75 ( 0.00%) 1009995.26 ( -1.02%) Hmean tput-24 1416430.67 ( 0.00%) 1398700.11 ( -1.25%) Hmean tput-32 1687702.72 ( 0.00%) 1671357.04 ( -0.97%) Hmean tput-40 1798094.90 ( 0.00%) 2015616.46 * 12.10%* Hmean tput-48 1972731.77 ( 0.00%) 2333233.72 ( 18.27%) Hmean tput-56 2386872.38 ( 0.00%) 2759483.38 ( 15.61%) Hmean tput-64 2909475.33 ( 0.00%) 2925074.69 ( 0.54%) Hmean tput-72 2585071.36 ( 0.00%) 2962443.97 ( 14.60%) Hmean tput-80 2994387.24 ( 0.00%) 3015980.59 ( 0.72%) Hmean tput-88 3061408.57 ( 0.00%) 3010296.16 ( -1.67%) Hmean tput-96 3052394.82 ( 0.00%) 2784743.41 ( -8.77%) Hmean tput-104 2997814.76 ( 0.00%) 2758184.50 ( -7.99%) Hmean tput-112 2955353.29 ( 0.00%) 2859705.09 ( -3.24%) Hmean tput-120 2889770.71 ( 0.00%) 2764478.46 ( -4.34%) Hmean tput-128 2871713.84 ( 0.00%) 2750136.73 ( -4.23%) Stddev tput-1 5325.93 ( 0.00%) 2002.53 ( 62.40%) Stddev tput-8 6630.54 ( 0.00%) 10905.00 ( -64.47%) Stddev tput-16 25608.58 ( 0.00%) 6851.16 ( 73.25%) Stddev tput-24 12117.69 ( 0.00%) 4227.79 ( 65.11%) Stddev tput-32 27577.16 ( 0.00%) 8761.05 ( 68.23%) Stddev tput-40 59505.86 ( 0.00%) 2048.49 ( 96.56%) Stddev tput-48 168330.30 ( 0.00%) 93058.08 ( 44.72%) Stddev tput-56 219540.39 ( 0.00%) 30687.02 ( 86.02%) Stddev tput-64 121750.35 ( 0.00%) 9617.36 ( 92.10%) Stddev tput-72 223387.05 ( 0.00%) 34081.13 ( 84.74%) Stddev tput-80 128198.46 ( 0.00%) 22565.19 ( 82.40%) Stddev tput-88 136665.36 ( 0.00%) 27905.97 ( 79.58%) Stddev tput-96 111925.81 ( 0.00%) 99615.79 ( 11.00%) Stddev tput-104 146455.96 ( 0.00%) 28861.98 ( 80.29%) Stddev tput-112 88740.49 ( 0.00%) 58288.23 ( 34.32%) Stddev tput-120 186384.86 ( 0.00%) 45812.03 ( 75.42%) Stddev tput-128 78761.09 ( 0.00%) 57418.48 ( 27.10%) Similarly, for embarassingly parallel problems like NPB-ep, there are improvements due to better spreading across LLC when the machine is not fully utilised. vanilla sched-numaimb-v6 Min ep.D 31.79 ( 0.00%) 26.11 ( 17.87%) Amean ep.D 31.86 ( 0.00%) 26.17 * 17.86%* Stddev ep.D 0.07 ( 0.00%) 0.05 ( 24.41%) CoeffVar ep.D 0.22 ( 0.00%) 0.20 ( 7.97%) Max ep.D 31.93 ( 0.00%) 26.21 ( 17.91%) Signed-off-by: Mel Gorman Signed-off-by: Peter Zijlstra (Intel) Reviewed-by: Gautham R. Shenoy Tested-by: K Prateek Nayak Link: https://lore.kernel.org/r/20220208094334.16379-3-mgorman@techsingularity.net

arch_topology: Remove unused topology_set_thermal_pressure() and related

2021-11-23T09:40:26+00:00

There is no need of this function (and related) since code has been converted to use the new arch_update_thermal_pressure() API. The old code can be removed. Signed-off-by: Lukasz Luba Signed-off-by: Viresh Kumar

arch_topology: Introduce thermal pressure update function

2021-11-23T09:40:26+00:00

The thermal pressure is a mechanism which is used for providing information about reduced CPU performance to the scheduler. Usually code has to convert the value from frequency units into capacity units, which are understandable by the scheduler. Create a common conversion code which can be just used via a handy API. Internally, the topology_update_thermal_pressure() operates on frequency in MHz and max CPU frequency is taken from 'freq_factor' (per-cpu). Signed-off-by: Lukasz Luba Reviewed-by: Thara Gopinath Signed-off-by: Viresh Kumar

sched/fair: Wait before decaying max_newidle_lb_cost

2021-10-31T10:11:38+00:00

Decay max_newidle_lb_cost only when it has not been updated for a while and ensure to not decay a recently changed value. Signed-off-by: Vincent Guittot Signed-off-by: Peter Zijlstra (Intel) Reviewed-by: Dietmar Eggemann Acked-by: Mel Gorman Link: https://lore.kernel.org/r/20211019123537.17146-4-vincent.guittot@linaro.org

sched: Add cluster scheduler level in core and related Kconfig for ARM64

2021-10-15T09:25:16+00:00

This patch adds scheduler level for clusters and automatically enables the load balance among clusters. It will directly benefit a lot of workload which loves more resources such as memory bandwidth, caches. Testing has widely been done in two different hardware configurations of Kunpeng920: 24 cores in one NUMA(6 clusters in each NUMA node); 32 cores in one NUMA(8 clusters in each NUMA node) Workload is running on either one NUMA node or four NUMA nodes, thus, this can estimate the effect of cluster spreading w/ and w/o NUMA load balance. * Stream benchmark: 4threads stream (on 1NUMA * 24cores = 24cores) stream stream w/o patch w/ patch MB/sec copy 29929.64 ( 0.00%) 32932.68 ( 10.03%) MB/sec scale 29861.10 ( 0.00%) 32710.58 ( 9.54%) MB/sec add 27034.42 ( 0.00%) 32400.68 ( 19.85%) MB/sec triad 27225.26 ( 0.00%) 31965.36 ( 17.41%) 6threads stream (on 1NUMA * 24cores = 24cores) stream stream w/o patch w/ patch MB/sec copy 40330.24 ( 0.00%) 42377.68 ( 5.08%) MB/sec scale 40196.42 ( 0.00%) 42197.90 ( 4.98%) MB/sec add 37427.00 ( 0.00%) 41960.78 ( 12.11%) MB/sec triad 37841.36 ( 0.00%) 42513.64 ( 12.35%) 12threads stream (on 1NUMA * 24cores = 24cores) stream stream w/o patch w/ patch MB/sec copy 52639.82 ( 0.00%) 53818.04 ( 2.24%) MB/sec scale 52350.30 ( 0.00%) 53253.38 ( 1.73%) MB/sec add 53607.68 ( 0.00%) 55198.82 ( 2.97%) MB/sec triad 54776.66 ( 0.00%) 56360.40 ( 2.89%) Thus, it could help memory-bound workload especially under medium load. Similar improvement is also seen in lkp-pbzip2: * lkp-pbzip2 benchmark 2-96 threads (on 4NUMA * 24cores = 96cores) lkp-pbzip2 lkp-pbzip2 w/o patch w/ patch Hmean tput-2 11062841.57 ( 0.00%) 11341817.51 * 2.52%* Hmean tput-5 26815503.70 ( 0.00%) 27412872.65 * 2.23%* Hmean tput-8 41873782.21 ( 0.00%) 43326212.92 * 3.47%* Hmean tput-12 61875980.48 ( 0.00%) 64578337.51 * 4.37%* Hmean tput-21 105814963.07 ( 0.00%) 111381851.01 * 5.26%* Hmean tput-30 150349470.98 ( 0.00%) 156507070.73 * 4.10%* Hmean tput-48 237195937.69 ( 0.00%) 242353597.17 * 2.17%* Hmean tput-79 360252509.37 ( 0.00%) 362635169.23 * 0.66%* Hmean tput-96 394571737.90 ( 0.00%) 400952978.48 * 1.62%* 2-24 threads (on 1NUMA * 24cores = 24cores) lkp-pbzip2 lkp-pbzip2 w/o patch w/ patch Hmean tput-2 11071705.49 ( 0.00%) 11296869.10 * 2.03%* Hmean tput-4 20782165.19 ( 0.00%) 21949232.15 * 5.62%* Hmean tput-6 30489565.14 ( 0.00%) 33023026.96 * 8.31%* Hmean tput-8 40376495.80 ( 0.00%) 42779286.27 * 5.95%* Hmean tput-12 61264033.85 ( 0.00%) 62995632.78 * 2.83%* Hmean tput-18 86697139.39 ( 0.00%) 86461545.74 ( -0.27%) Hmean tput-24 104854637.04 ( 0.00%) 104522649.46 * -0.32%* In the case of 6 threads and 8 threads, we see the greatest performance improvement. Similar improvement can be seen on lkp-pixz though the improvement is smaller: * lkp-pixz benchmark 2-24 threads lkp-pixz (on 1NUMA * 24cores = 24cores) lkp-pixz lkp-pixz w/o patch w/ patch Hmean tput-2 6486981.16 ( 0.00%) 6561515.98 * 1.15%* Hmean tput-4 11645766.38 ( 0.00%) 11614628.43 ( -0.27%) Hmean tput-6 15429943.96 ( 0.00%) 15957350.76 * 3.42%* Hmean tput-8 19974087.63 ( 0.00%) 20413746.98 * 2.20%* Hmean tput-12 28172068.18 ( 0.00%) 28751997.06 * 2.06%* Hmean tput-18 39413409.54 ( 0.00%) 39896830.55 * 1.23%* Hmean tput-24 49101815.85 ( 0.00%) 49418141.47 * 0.64%* * SPECrate benchmark 4,8,16 copies mcf_r(on 1NUMA * 32cores = 32cores) Base Base Run Time Rate ------- --------- 4 Copies w/o 580 (w/ 570) w/o 11.1 (w/ 11.3) 8 Copies w/o 647 (w/ 605) w/o 20.0 (w/ 21.4, +7%) 16 Copies w/o 844 (w/ 844) w/o 30.6 (w/ 30.6) 32 Copies(on 4NUMA * 32 cores = 128cores) [w/o patch] Base Base Base Benchmarks Copies Run Time Rate --------------- ------- --------- --------- 500.perlbench_r 32 584 87.2 * 502.gcc_r 32 503 90.2 * 505.mcf_r 32 745 69.4 * 520.omnetpp_r 32 1031 40.7 * 523.xalancbmk_r 32 597 56.6 * 525.x264_r 1 -- CE 531.deepsjeng_r 32 336 109 * 541.leela_r 32 556 95.4 * 548.exchange2_r 32 513 163 * 557.xz_r 32 530 65.2 * Est. SPECrate2017_int_base 80.3 [w/ patch] Base Base Base Benchmarks Copies Run Time Rate --------------- ------- --------- --------- 500.perlbench_r 32 580 87.8 (+0.688%) * 502.gcc_r 32 477 95.1 (+5.432%) * 505.mcf_r 32 644 80.3 (+13.574%) * 520.omnetpp_r 32 942 44.6 (+9.58%) * 523.xalancbmk_r 32 560 60.4 (+6.714%%) * 525.x264_r 1 -- CE 531.deepsjeng_r 32 337 109 (+0.000%) * 541.leela_r 32 554 95.6 (+0.210%) * 548.exchange2_r 32 515 163 (+0.000%) * 557.xz_r 32 524 66.0 (+1.227%) * Est. SPECrate2017_int_base 83.7 (+4.062%) On the other hand, it is slightly helpful to CPU-bound tasks like kernbench: * 24-96 threads kernbench (on 4NUMA * 24cores = 96cores) kernbench kernbench w/o cluster w/ cluster Min user-24 12054.67 ( 0.00%) 12024.19 ( 0.25%) Min syst-24 1751.51 ( 0.00%) 1731.68 ( 1.13%) Min elsp-24 600.46 ( 0.00%) 598.64 ( 0.30%) Min user-48 12361.93 ( 0.00%) 12315.32 ( 0.38%) Min syst-48 1917.66 ( 0.00%) 1892.73 ( 1.30%) Min elsp-48 333.96 ( 0.00%) 332.57 ( 0.42%) Min user-96 12922.40 ( 0.00%) 12921.17 ( 0.01%) Min syst-96 2143.94 ( 0.00%) 2110.39 ( 1.56%) Min elsp-96 211.22 ( 0.00%) 210.47 ( 0.36%) Amean user-24 12063.99 ( 0.00%) 12030.78 * 0.28%* Amean syst-24 1755.20 ( 0.00%) 1735.53 * 1.12%* Amean elsp-24 601.60 ( 0.00%) 600.19 ( 0.23%) Amean user-48 12362.62 ( 0.00%) 12315.56 * 0.38%* Amean syst-48 1921.59 ( 0.00%) 1894.95 * 1.39%* Amean elsp-48 334.10 ( 0.00%) 332.82 * 0.38%* Amean user-96 12925.27 ( 0.00%) 12922.63 ( 0.02%) Amean syst-96 2146.66 ( 0.00%) 2122.20 * 1.14%* Amean elsp-96 211.96 ( 0.00%) 211.79 ( 0.08%) Note this patch isn't an universal win, it might hurt those workload which can benefit from packing. Though tasks which want to take advantages of lower communication latency of one cluster won't necessarily been packed in one cluster while kernel is not aware of clusters, they have some chance to be randomly packed. But this patch will make them more likely spread. Signed-off-by: Barry Song Tested-by: Yicong Yang Signed-off-by: Peter Zijlstra (Intel)

sched/topology,schedutil: Wrap sched domains rebuild

2020-11-19T10:25:47+00:00

Add the rebuild_sched_domains_energy() function to wrap the functionality that rebuilds the scheduling domains if any of the Energy Aware Scheduling (EAS) initialisation conditions change. This functionality is used when schedutil is added or removed or when EAS is enabled or disabled through the sched_energy_aware sysctl. Therefore, create a single function that is used in both these cases and that can be later reused. Signed-off-by: Ionela Voinescu Signed-off-by: Peter Zijlstra (Intel) Acked-by: Quentin Perret Acked-by: Rafael J. Wysocki Link: https://lkml.kernel.org/r/20201027180713.7642-2-ionela.voinescu@arm.com

sched/topology: Move SD_DEGENERATE_GROUPS_MASK out of linux/sched/topology.h

2020-08-26T10:41:59+00:00

SD_DEGENERATE_GROUPS_MASK is only useful for sched/topology.c, but still gets defined for anyone who imports topology.h, leading to a flurry of unused variable warnings. Move it out of the header and place it next to the SD degeneration functions in sched/topology.c. Fixes: 4ee4ea443a5d ("sched/topology: Introduce SD metaflag for flags needing > 1 groups") Reported-by: Andy Shevchenko Signed-off-by: Valentin Schneider Signed-off-by: Peter Zijlstra (Intel) Link: https://lkml.kernel.org/r/20200825133216.9163-2-valentin.schneider@arm.com

sched/topology: Move sd_flag_debug out of linux/sched/topology.h

2020-08-26T10:41:59+00:00

Defining an array in a header imported all over the place clearly is a daft idea, that still didn't stop me from doing it. Leave a declaration of sd_flag_debug in topology.h and move its definition to sched/debug.c. Fixes: b6e862f38672 ("sched/topology: Define and assign sched_domain flag metadata") Reported-by: Andy Shevchenko Signed-off-by: Valentin Schneider Signed-off-by: Peter Zijlstra (Intel) Link: https://lkml.kernel.org/r/20200825133216.9163-1-valentin.schneider@arm.com

sched/topology: Introduce SD metaflag for flags needing > 1 groups

2020-08-19T08:49:48+00:00

In preparation of cleaning up the sd_degenerate*() functions, mark flags used in sd_degenerate() with the new SDF_NEEDS_GROUPS flag. With this, build a compile-time mask of those SD flags. Note that sd_parent_degenerate() uses an extra flag in its mask, SD_PREFER_SIBLING, which remains singled out for now. Suggested-by: Peter Zijlstra Signed-off-by: Valentin Schneider Signed-off-by: Ingo Molnar Reviewed-by: Dietmar Eggemann Acked-by: Peter Zijlstra Link: https://lore.kernel.org/r/20200817113003.20802-8-valentin.schneider@arm.com