Patch "sched/fair: Introduce SIS_UTIL to search idle CPU based on sum of util_avg" has been added to the 5.19-stable tree

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This is a note to let you know that I've just added the patch titled

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

to the 5.19-stable tree which can be found at:
    http://www.kernel.org/git/?p=linux/kernel/git/stable/stable-queue.git;a=summary

The filename of the patch is:
     sched-fair-introduce-sis_util-to-search-idle-cpu-bas.patch
and it can be found in the queue-5.19 subdirectory.

If you, or anyone else, feels it should not be added to the stable tree,
please let <stable@xxxxxxxxxxxxxxx> know about it.



commit 566e5b79179f28c876eaf9cf2bd5d55788578bd8
Author: Chen Yu <yu.c.chen@xxxxxxxxx>
Date:   Mon Jun 13 00:34:28 2022 +0800

    sched/fair: Introduce SIS_UTIL to search idle CPU based on sum of util_avg
    
    [ Upstream commit 70fb5ccf2ebb09a0c8ebba775041567812d45f86 ]
    
    [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 <tim.c.chen@xxxxxxxxx>
    Suggested-by: Peter Zijlstra <peterz@xxxxxxxxxxxxx>
    Signed-off-by: Chen Yu <yu.c.chen@xxxxxxxxx>
    Signed-off-by: Peter Zijlstra (Intel) <peterz@xxxxxxxxxxxxx>
    Tested-by: Yicong Yang <yangyicong@xxxxxxxxxxxxx>
    Tested-by: Mohini Narkhede <mohini.narkhede@xxxxxxxxx>
    Tested-by: K Prateek Nayak <kprateek.nayak@xxxxxxx>
    Link: https://lore.kernel.org/r/20220612163428.849378-1-yu.c.chen@xxxxxxxxx
    Signed-off-by: Sasha Levin <sashal@xxxxxxxxxx>

diff --git a/include/linux/sched/topology.h b/include/linux/sched/topology.h
index 56cffe42abbc..816df6cc444e 100644
--- a/include/linux/sched/topology.h
+++ b/include/linux/sched/topology.h
@@ -81,6 +81,7 @@ struct sched_domain_shared {
 	atomic_t	ref;
 	atomic_t	nr_busy_cpus;
 	int		has_idle_cores;
+	int		nr_idle_scan;
 };
 
 struct sched_domain {
diff --git a/kernel/sched/fair.c b/kernel/sched/fair.c
index 77b2048a9326..3fb857a35b16 100644
--- a/kernel/sched/fair.c
+++ b/kernel/sched/fair.c
@@ -6336,6 +6336,7 @@ static int select_idle_cpu(struct task_struct *p, struct sched_domain *sd, bool
 {
 	struct cpumask *cpus = this_cpu_cpumask_var_ptr(select_idle_mask);
 	int i, cpu, idle_cpu = -1, nr = INT_MAX;
+	struct sched_domain_shared *sd_share;
 	struct rq *this_rq = this_rq();
 	int this = smp_processor_id();
 	struct sched_domain *this_sd;
@@ -6375,6 +6376,17 @@ static int select_idle_cpu(struct task_struct *p, struct sched_domain *sd, bool
 		time = cpu_clock(this);
 	}
 
+	if (sched_feat(SIS_UTIL)) {
+		sd_share = rcu_dereference(per_cpu(sd_llc_shared, target));
+		if (sd_share) {
+			/* because !--nr is the condition to stop scan */
+			nr = READ_ONCE(sd_share->nr_idle_scan) + 1;
+			/* overloaded LLC is unlikely to have idle cpu/core */
+			if (nr == 1)
+				return -1;
+		}
+	}
+
 	for_each_cpu_wrap(cpu, cpus, target + 1) {
 		if (has_idle_core) {
 			i = select_idle_core(p, cpu, cpus, &idle_cpu);
@@ -9222,6 +9234,77 @@ find_idlest_group(struct sched_domain *sd, struct task_struct *p, int this_cpu)
 	return idlest;
 }
 
+static void update_idle_cpu_scan(struct lb_env *env,
+				 unsigned long sum_util)
+{
+	struct sched_domain_shared *sd_share;
+	int llc_weight, pct;
+	u64 x, y, tmp;
+	/*
+	 * Update the number of CPUs to scan in LLC domain, which could
+	 * be used as a hint in select_idle_cpu(). The update of sd_share
+	 * could be expensive because it is within a shared cache line.
+	 * So the write of this hint only occurs during periodic load
+	 * balancing, rather than CPU_NEWLY_IDLE, because the latter
+	 * can fire way more frequently than the former.
+	 */
+	if (!sched_feat(SIS_UTIL) || env->idle == CPU_NEWLY_IDLE)
+		return;
+
+	llc_weight = per_cpu(sd_llc_size, env->dst_cpu);
+	if (env->sd->span_weight != llc_weight)
+		return;
+
+	sd_share = rcu_dereference(per_cpu(sd_llc_shared, env->dst_cpu));
+	if (!sd_share)
+		return;
+
+	/*
+	 * The number of CPUs to search drops as sum_util increases, when
+	 * sum_util hits 85% or above, the scan stops.
+	 * The reason to choose 85% as the threshold is because this is the
+	 * imbalance_pct(117) when a LLC sched group is overloaded.
+	 *
+	 * let y = SCHED_CAPACITY_SCALE - p * x^2                       [1]
+	 * 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'                                    [2]
+	 *
+	 * When x hits the threshold of overloaded, AKA, when
+	 * x = 100 / pct, y drops to 0. According to [1],
+	 * p should be SCHED_CAPACITY_SCALE * pct^2 / 10000
+	 *
+	 * Scale x by SCHED_CAPACITY_SCALE:
+	 * x' = sum_util / llc_weight;                                  [3]
+	 *
+	 * and finally [1] becomes:
+	 * y = SCHED_CAPACITY_SCALE -
+	 *     x'^2 * pct^2 / (10000 * SCHED_CAPACITY_SCALE)            [4]
+	 *
+	 */
+	/* equation [3] */
+	x = sum_util;
+	do_div(x, llc_weight);
+
+	/* equation [4] */
+	pct = env->sd->imbalance_pct;
+	tmp = x * x * pct * pct;
+	do_div(tmp, 10000 * SCHED_CAPACITY_SCALE);
+	tmp = min_t(long, tmp, SCHED_CAPACITY_SCALE);
+	y = SCHED_CAPACITY_SCALE - tmp;
+
+	/* equation [2] */
+	y *= llc_weight;
+	do_div(y, SCHED_CAPACITY_SCALE);
+	if ((int)y != sd_share->nr_idle_scan)
+		WRITE_ONCE(sd_share->nr_idle_scan, (int)y);
+}
+
 /**
  * update_sd_lb_stats - Update sched_domain's statistics for load balancing.
  * @env: The load balancing environment.
@@ -9234,6 +9317,7 @@ static inline void update_sd_lb_stats(struct lb_env *env, struct sd_lb_stats *sd
 	struct sched_group *sg = env->sd->groups;
 	struct sg_lb_stats *local = &sds->local_stat;
 	struct sg_lb_stats tmp_sgs;
+	unsigned long sum_util = 0;
 	int sg_status = 0;
 
 	do {
@@ -9266,6 +9350,7 @@ static inline void update_sd_lb_stats(struct lb_env *env, struct sd_lb_stats *sd
 		sds->total_load += sgs->group_load;
 		sds->total_capacity += sgs->group_capacity;
 
+		sum_util += sgs->group_util;
 		sg = sg->next;
 	} while (sg != env->sd->groups);
 
@@ -9291,6 +9376,8 @@ static inline void update_sd_lb_stats(struct lb_env *env, struct sd_lb_stats *sd
 		WRITE_ONCE(rd->overutilized, SG_OVERUTILIZED);
 		trace_sched_overutilized_tp(rd, SG_OVERUTILIZED);
 	}
+
+	update_idle_cpu_scan(env, sum_util);
 }
 
 #define NUMA_IMBALANCE_MIN 2
diff --git a/kernel/sched/features.h b/kernel/sched/features.h
index 1cf435bbcd9c..ee7f23c76bd3 100644
--- a/kernel/sched/features.h
+++ b/kernel/sched/features.h
@@ -60,7 +60,8 @@ SCHED_FEAT(TTWU_QUEUE, true)
 /*
  * When doing wakeups, attempt to limit superfluous scans of the LLC domain.
  */
-SCHED_FEAT(SIS_PROP, true)
+SCHED_FEAT(SIS_PROP, false)
+SCHED_FEAT(SIS_UTIL, true)
 
 /*
  * Issue a WARN when we do multiple update_rq_clock() calls



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