Hi all,
I noticed that some benchmark performance varies after tunning the sysctl_sched_migration_cost
through /sys/kernel/debug/sched/migration_cost_ns on arm64. The default value is 500000, and
I tried 10000, 100000, 1000000. Below are some results from mmtests, based on 5.14-release.
On Kunpeng920 (128cores, 4numa, 2socket):
pgbench (config-db-pgbench-timed-ro-medium)
mig-cost-500000 mig-cost-100000 mig-cost-10000 mig-cost-1000000
Hmean 1 9558.99 ( 0.00%) 9735.31 * 1.84%* 9410.84 * -1.55%* 9602.47 * 0.45%*
Hmean 8 17615.90 ( 0.00%) 17439.78 * -1.00%* 18056.44 * 2.50%* 19222.18 * 9.12%*
Hmean 12 25228.38 ( 0.00%) 25592.69 * 1.44%* 26739.06 * 5.99%* 27575.48 * 9.30%*
Hmean 24 46623.27 ( 0.00%) 48853.30 * 4.78%* 47386.02 * 1.64%* 48542.94 * 4.12%*
Hmean 32 60578.78 ( 0.00%) 62116.81 * 2.54%* 59961.36 * -1.02%* 58681.07 * -3.13%*
Hmean 48 68159.12 ( 0.00%) 67867.90 ( -0.43%) 65631.79 * -3.71%* 66487.16 * -2.45%*
Hmean 80 66894.87 ( 0.00%) 73440.92 * 9.79%* 68751.63 * 2.78%* 67326.70 ( 0.65%)
Hmean 112 68582.27 ( 0.00%) 65339.90 * -4.73%* 68454.99 ( -0.19%) 67211.66 * -2.00%*
Hmean 144 76290.98 ( 0.00%) 70455.65 * -7.65%* 64851.23 * -14.99%* 64940.61 * -14.88%*
Hmean 172 63245.68 ( 0.00%) 68790.24 * 8.77%* 66246.46 * 4.74%* 69536.96 * 9.95%*
Hmean 204 61793.47 ( 0.00%) 63711.62 * 3.10%* 66055.64 * 6.90%* 58023.20 * -6.10%*
Hmean 236 61486.75 ( 0.00%) 68404.44 * 11.25%* 70499.70 * 14.66%* 58285.67 * -5.21%*
Hmean 256 57476.13 ( 0.00%) 65645.83 * 14.21%* 69437.05 * 20.81%* 60518.05 * 5.29%*
tbench (config-network-tbench)
mig-cost-500000 mig-cost-100000 mig-cost-10000 mig-cost-1000000
Hmean 1 333.12 ( 0.00%) 332.93 ( -0.06%) 335.34 * 0.67%* 334.36 * 0.37%*
Hmean 2 665.88 ( 0.00%) 667.19 * 0.20%* 666.47 * 0.09%* 667.02 * 0.17%*
Hmean 4 1324.10 ( 0.00%) 1312.23 * -0.90%* 1313.07 * -0.83%* 1315.13 * -0.68%*
Hmean 8 2618.85 ( 0.00%) 2602.00 * -0.64%* 2577.49 * -1.58%* 2600.48 * -0.70%*
Hmean 16 5100.74 ( 0.00%) 5068.80 * -0.63%* 5041.34 * -1.16%* 5069.78 * -0.61%*
Hmean 32 8157.22 ( 0.00%) 8163.50 ( 0.08%) 7936.25 * -2.71%* 8329.18 * 2.11%*
Hmean 64 4824.56 ( 0.00%) 4890.81 * 1.37%* 5319.97 * 10.27%* 4830.68 * 0.13%*
Hmean 128 4635.17 ( 0.00%) 6810.90 * 46.94%* 5304.36 * 14.44%* 4516.06 * -2.57%*
Hmean 256 8816.62 ( 0.00%) 8851.28 * 0.39%* 8448.76 * -4.17%* 6840.12 * -22.42%*
Hmean 512 7825.56 ( 0.00%) 8538.04 * 9.10%* 8002.77 * 2.26%* 7946.54 * 1.55%*
Also on Raspberrypi 4B:
pgbench (config-db-pgbench-timed-ro-medium)
mig-cost-500000 mig-cost-100000
Hmean 1 1651.41 ( 0.00%) 3444.27 * 108.56%*
Hmean 4 4015.83 ( 0.00%) 6883.21 * 71.40%*
Hmean 7 4161.45 ( 0.00%) 6646.18 * 59.71%*
Hmean 8 4277.28 ( 0.00%) 6764.60 * 58.15%*
For tbench on Raspberrypi 4B and both pgbench and tbench on x86, tuning sysctl_sched_migration_cost
doesn't have such huge difference and will have some degradations (max -8% on x86 for pgbench) in some cases.
The sysctl_sched_migration_cost will affects the frequency of load balance. It will affect
directly in task_hot() and newidle_balance() to decide whether we can do a migration or load
balance. And affects other parameters like rq->avg_idle, rq->max_idle_balance_cost and
sd->max_newidle_lb_cost to indirectly affect the load balance process. These parameters record
the load_balance() cost and will be limited up to sysctl_sched_migration_cost, so I measure
the average cost of load_balance() on Kunpeng920 with bcc tools(./funclantency load_balance -d 10):
system status idle 50%load 100%load
avg cost 3160ns 4790ns 7563ns
The average cost of load balance seems quite smaller than the default sysctl_sched_migration_cost
which is 500000(500ms).
So I have some RFC questions:
1. how is the default 500000 (500ms) migration cost is measured or caculated?
The value has never changed in the past decade. I dig into the git commits and find it was introduced
in da84d9617672 ("sched: reintroduce cache-hot affinity"). But it didn't explain how did this value come.
2. The ABI now has been removed from sysctl and moved to debugfs. As tuning this can improve the performance
of some workloads on some platforms, maybe it's better to make it a formal sysctl again with docs?
I'll be appreciated for any comments and replies!
Thanks,
Yicong
Hi Yicong,
On Tue, 14 Sept 2021 at 09:27, Yicong Yang <[email protected]> wrote:
>
> Hi all,
>
> I noticed that some benchmark performance varies after tunning the sysctl_sched_migration_cost
> through /sys/kernel/debug/sched/migration_cost_ns on arm64. The default value is 500000, and
> I tried 10000, 100000, 1000000. Below are some results from mmtests, based on 5.14-release.
>
> On Kunpeng920 (128cores, 4numa, 2socket):
>
> pgbench (config-db-pgbench-timed-ro-medium)
> mig-cost-500000 mig-cost-100000 mig-cost-10000 mig-cost-1000000
> Hmean 1 9558.99 ( 0.00%) 9735.31 * 1.84%* 9410.84 * -1.55%* 9602.47 * 0.45%*
> Hmean 8 17615.90 ( 0.00%) 17439.78 * -1.00%* 18056.44 * 2.50%* 19222.18 * 9.12%*
> Hmean 12 25228.38 ( 0.00%) 25592.69 * 1.44%* 26739.06 * 5.99%* 27575.48 * 9.30%*
> Hmean 24 46623.27 ( 0.00%) 48853.30 * 4.78%* 47386.02 * 1.64%* 48542.94 * 4.12%*
> Hmean 32 60578.78 ( 0.00%) 62116.81 * 2.54%* 59961.36 * -1.02%* 58681.07 * -3.13%*
> Hmean 48 68159.12 ( 0.00%) 67867.90 ( -0.43%) 65631.79 * -3.71%* 66487.16 * -2.45%*
> Hmean 80 66894.87 ( 0.00%) 73440.92 * 9.79%* 68751.63 * 2.78%* 67326.70 ( 0.65%)
> Hmean 112 68582.27 ( 0.00%) 65339.90 * -4.73%* 68454.99 ( -0.19%) 67211.66 * -2.00%*
> Hmean 144 76290.98 ( 0.00%) 70455.65 * -7.65%* 64851.23 * -14.99%* 64940.61 * -14.88%*
> Hmean 172 63245.68 ( 0.00%) 68790.24 * 8.77%* 66246.46 * 4.74%* 69536.96 * 9.95%*
> Hmean 204 61793.47 ( 0.00%) 63711.62 * 3.10%* 66055.64 * 6.90%* 58023.20 * -6.10%*
> Hmean 236 61486.75 ( 0.00%) 68404.44 * 11.25%* 70499.70 * 14.66%* 58285.67 * -5.21%*
> Hmean 256 57476.13 ( 0.00%) 65645.83 * 14.21%* 69437.05 * 20.81%* 60518.05 * 5.29%*
>
> tbench (config-network-tbench)
> mig-cost-500000 mig-cost-100000 mig-cost-10000 mig-cost-1000000
> Hmean 1 333.12 ( 0.00%) 332.93 ( -0.06%) 335.34 * 0.67%* 334.36 * 0.37%*
> Hmean 2 665.88 ( 0.00%) 667.19 * 0.20%* 666.47 * 0.09%* 667.02 * 0.17%*
> Hmean 4 1324.10 ( 0.00%) 1312.23 * -0.90%* 1313.07 * -0.83%* 1315.13 * -0.68%*
> Hmean 8 2618.85 ( 0.00%) 2602.00 * -0.64%* 2577.49 * -1.58%* 2600.48 * -0.70%*
> Hmean 16 5100.74 ( 0.00%) 5068.80 * -0.63%* 5041.34 * -1.16%* 5069.78 * -0.61%*
> Hmean 32 8157.22 ( 0.00%) 8163.50 ( 0.08%) 7936.25 * -2.71%* 8329.18 * 2.11%*
> Hmean 64 4824.56 ( 0.00%) 4890.81 * 1.37%* 5319.97 * 10.27%* 4830.68 * 0.13%*
> Hmean 128 4635.17 ( 0.00%) 6810.90 * 46.94%* 5304.36 * 14.44%* 4516.06 * -2.57%*
> Hmean 256 8816.62 ( 0.00%) 8851.28 * 0.39%* 8448.76 * -4.17%* 6840.12 * -22.42%*
> Hmean 512 7825.56 ( 0.00%) 8538.04 * 9.10%* 8002.77 * 2.26%* 7946.54 * 1.55%*
>
> Also on Raspberrypi 4B:
>
> pgbench (config-db-pgbench-timed-ro-medium)
> mig-cost-500000 mig-cost-100000
> Hmean 1 1651.41 ( 0.00%) 3444.27 * 108.56%*
> Hmean 4 4015.83 ( 0.00%) 6883.21 * 71.40%*
> Hmean 7 4161.45 ( 0.00%) 6646.18 * 59.71%*
> Hmean 8 4277.28 ( 0.00%) 6764.60 * 58.15%*
>
> For tbench on Raspberrypi 4B and both pgbench and tbench on x86, tuning sysctl_sched_migration_cost
> doesn't have such huge difference and will have some degradations (max -8% on x86 for pgbench) in some cases.
>
> The sysctl_sched_migration_cost will affects the frequency of load balance. It will affect
So it doesn't affect the periodic load but only the newly idle load balance
> directly in task_hot() and newidle_balance() to decide whether we can do a migration or load
> balance. And affects other parameters like rq->avg_idle, rq->max_idle_balance_cost and
> sd->max_newidle_lb_cost to indirectly affect the load balance process. These parameters record
> the load_balance() cost and will be limited up to sysctl_sched_migration_cost, so I measure
> the average cost of load_balance() on Kunpeng920 with bcc tools(./funclantency load_balance -d 10):
>
> system status idle 50%load 100%load
> avg cost 3160ns 4790ns 7563ns
What is the setup of your test ? has this been measured during the
benchmarks above ?
Also, do you have more details about the topology and the number of
sched domain ?
Are you using cgroup hierarchy ?
>
> The average cost of load balance seems quite smaller than the default sysctl_sched_migration_cost
> which is 500000(500ms).
AFAICT, it is 500us not 500ms
>
> So I have some RFC questions:
> 1. how is the default 500000 (500ms) migration cost is measured or caculated?
500us not ms
I would say that it's a heuristic value that works for most of system
but it should probably be tuned per platform. But also note that it's
quite difficult to get a correct value
> The value has never changed in the past decade. I dig into the git commits and find it was introduced
> in da84d9617672 ("sched: reintroduce cache-hot affinity"). But it didn't explain how did this value come.
> 2. The ABI now has been removed from sysctl and moved to debugfs. As tuning this can improve the performance
> of some workloads on some platforms, maybe it's better to make it a formal sysctl again with docs?
>
> I'll be appreciated for any comments and replies!
>
> Thanks,
> Yicong
>
>
On Tue, Sep 14, 2021 at 03:27:09PM +0800, Yicong Yang wrote:
> 2. The ABI now has been removed from sysctl and moved to debugfs. As tuning this can improve the performance
> of some workloads on some platforms, maybe it's better to make it a formal sysctl again with docs?
It never was an ABI, there is nothing to restore. It has always been
CONFIG_SCHED_DEBUG.
I'm open to topology based improvements to the code, but I don't think
user tunables are a good way.
On Tue, Sep 14, 2021 at 11:04:03AM +0200, Vincent Guittot wrote:
>
> I would say that it's a heuristic value that works for most of system
> but it should probably be tuned per platform. But also note that it's
> quite difficult to get a correct value
>
Right; so back before CFS there was some boot time benchmarks that
measured something for each sched domain.
Conceptually that makes sense, the larger the domain, the larger the
cost, also, you get per platform etc..
In practise it had boot to boot variance and virt fail written all over
it, which is why Ingo ripped it out. I think someone once tried to bring
some of it back, but that was a long time ago.
I'm also not convinced boot time benchmarks are the best idea, because
the above reasons, but perhaps we can do something topology based, and
maybe using a few platform inputs.
And as with anything, some benchmarks will like it, others will not like
it. It's only worth the complexity if we can get an improvement across
the board.
Hi Vincent,
thanks for the reply!
On 2021/9/14 17:04, Vincent Guittot wrote:
> Hi Yicong,
>
> On Tue, 14 Sept 2021 at 09:27, Yicong Yang <[email protected]> wrote:
>>
>> Hi all,
>>
>> I noticed that some benchmark performance varies after tunning the sysctl_sched_migration_cost
>> through /sys/kernel/debug/sched/migration_cost_ns on arm64. The default value is 500000, and
>> I tried 10000, 100000, 1000000. Below are some results from mmtests, based on 5.14-release.
>>
>> On Kunpeng920 (128cores, 4numa, 2socket):
>>
>> pgbench (config-db-pgbench-timed-ro-medium)
>> mig-cost-500000 mig-cost-100000 mig-cost-10000 mig-cost-1000000
>> Hmean 1 9558.99 ( 0.00%) 9735.31 * 1.84%* 9410.84 * -1.55%* 9602.47 * 0.45%*
>> Hmean 8 17615.90 ( 0.00%) 17439.78 * -1.00%* 18056.44 * 2.50%* 19222.18 * 9.12%*
>> Hmean 12 25228.38 ( 0.00%) 25592.69 * 1.44%* 26739.06 * 5.99%* 27575.48 * 9.30%*
>> Hmean 24 46623.27 ( 0.00%) 48853.30 * 4.78%* 47386.02 * 1.64%* 48542.94 * 4.12%*
>> Hmean 32 60578.78 ( 0.00%) 62116.81 * 2.54%* 59961.36 * -1.02%* 58681.07 * -3.13%*
>> Hmean 48 68159.12 ( 0.00%) 67867.90 ( -0.43%) 65631.79 * -3.71%* 66487.16 * -2.45%*
>> Hmean 80 66894.87 ( 0.00%) 73440.92 * 9.79%* 68751.63 * 2.78%* 67326.70 ( 0.65%)
>> Hmean 112 68582.27 ( 0.00%) 65339.90 * -4.73%* 68454.99 ( -0.19%) 67211.66 * -2.00%*
>> Hmean 144 76290.98 ( 0.00%) 70455.65 * -7.65%* 64851.23 * -14.99%* 64940.61 * -14.88%*
>> Hmean 172 63245.68 ( 0.00%) 68790.24 * 8.77%* 66246.46 * 4.74%* 69536.96 * 9.95%*
>> Hmean 204 61793.47 ( 0.00%) 63711.62 * 3.10%* 66055.64 * 6.90%* 58023.20 * -6.10%*
>> Hmean 236 61486.75 ( 0.00%) 68404.44 * 11.25%* 70499.70 * 14.66%* 58285.67 * -5.21%*
>> Hmean 256 57476.13 ( 0.00%) 65645.83 * 14.21%* 69437.05 * 20.81%* 60518.05 * 5.29%*
>>
>> tbench (config-network-tbench)
>> mig-cost-500000 mig-cost-100000 mig-cost-10000 mig-cost-1000000
>> Hmean 1 333.12 ( 0.00%) 332.93 ( -0.06%) 335.34 * 0.67%* 334.36 * 0.37%*
>> Hmean 2 665.88 ( 0.00%) 667.19 * 0.20%* 666.47 * 0.09%* 667.02 * 0.17%*
>> Hmean 4 1324.10 ( 0.00%) 1312.23 * -0.90%* 1313.07 * -0.83%* 1315.13 * -0.68%*
>> Hmean 8 2618.85 ( 0.00%) 2602.00 * -0.64%* 2577.49 * -1.58%* 2600.48 * -0.70%*
>> Hmean 16 5100.74 ( 0.00%) 5068.80 * -0.63%* 5041.34 * -1.16%* 5069.78 * -0.61%*
>> Hmean 32 8157.22 ( 0.00%) 8163.50 ( 0.08%) 7936.25 * -2.71%* 8329.18 * 2.11%*
>> Hmean 64 4824.56 ( 0.00%) 4890.81 * 1.37%* 5319.97 * 10.27%* 4830.68 * 0.13%*
>> Hmean 128 4635.17 ( 0.00%) 6810.90 * 46.94%* 5304.36 * 14.44%* 4516.06 * -2.57%*
>> Hmean 256 8816.62 ( 0.00%) 8851.28 * 0.39%* 8448.76 * -4.17%* 6840.12 * -22.42%*
>> Hmean 512 7825.56 ( 0.00%) 8538.04 * 9.10%* 8002.77 * 2.26%* 7946.54 * 1.55%*
>>
>> Also on Raspberrypi 4B:
>>
>> pgbench (config-db-pgbench-timed-ro-medium)
>> mig-cost-500000 mig-cost-100000
>> Hmean 1 1651.41 ( 0.00%) 3444.27 * 108.56%*
>> Hmean 4 4015.83 ( 0.00%) 6883.21 * 71.40%*
>> Hmean 7 4161.45 ( 0.00%) 6646.18 * 59.71%*
>> Hmean 8 4277.28 ( 0.00%) 6764.60 * 58.15%*
>>
>> For tbench on Raspberrypi 4B and both pgbench and tbench on x86, tuning sysctl_sched_migration_cost
>> doesn't have such huge difference and will have some degradations (max -8% on x86 for pgbench) in some cases.
>>
>> The sysctl_sched_migration_cost will affects the frequency of load balance. It will affect
>
> So it doesn't affect the periodic load but only the newly idle load balance
>
In load_balance(), it's used to judge whether a task is hot in task_hot(). so I think it
participates in the periodic load balance.
>> directly in task_hot() and newidle_balance() to decide whether we can do a migration or load
>> balance. And affects other parameters like rq->avg_idle, rq->max_idle_balance_cost and
>> sd->max_newidle_lb_cost to indirectly affect the load balance process. These parameters record
>> the load_balance() cost and will be limited up to sysctl_sched_migration_cost, so I measure
>> the average cost of load_balance() on Kunpeng920 with bcc tools(./funclantency load_balance -d 10):
>>
>> system status idle 50%load 100%load
>> avg cost 3160ns 4790ns 7563ns
>
> What is the setup of your test ? has this been measured during the
> benchmarks above ?
>
I use stress-ng to generate the load. Since it's a 128core server, `stress-ng -c 64` for
50% load, and `stress-ng -c 128` for 100% load. This is not measured during the benchmarks'
process.
> Also, do you have more details about the topology and the number of
> sched domain ?
>
sure. for `numactl -H`:
available: 4 nodes (0-3)
node 0 cpus: 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
node 0 size: 257149 MB
node 0 free: 253518 MB
node 1 cpus: 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63
node 1 size: 193531 MB
node 1 free: 192916 MB
node 2 cpus: 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95
node 2 size: 96763 MB
node 2 free: 92654 MB
node 3 cpus: 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127
node 3 size: 127668 MB
node 3 free: 125846 MB
node distances:
node 0 1 2 3
0: 10 12 20 22
1: 12 10 22 24
2: 20 22 10 12
3: 22 24 12 10
Kunpeng 920 is non-smt. There're 4 level domains and below is part of the /proc/schedstat:
[...]
cpu0
domain0 00000000,00000000,00000000,ffffffff
domain1 00000000,00000000,ffffffff,ffffffff
domain2 00000000,ffffffff,ffffffff,ffffffff
domain3 ffffffff,ffffffff,ffffffff,ffffffff
[...]
cpu32
domain0 00000000,00000000,ffffffff,00000000
domain1 00000000,00000000,ffffffff,ffffffff
domain2 00000000,ffffffff,ffffffff,ffffffff
domain3 ffffffff,ffffffff,ffffffff,ffffffff
[...]
cpu64
domain0 00000000,ffffffff,00000000,00000000
domain1 ffffffff,ffffffff,00000000,00000000
domain2 ffffffff,ffffffff,00000000,ffffffff
domain3 ffffffff,ffffffff,ffffffff,ffffffff
[...]
cpu96
domain0 ffffffff,00000000,00000000,00000000
domain1 ffffffff,ffffffff,00000000,00000000
domain2 ffffffff,ffffffff,00000000,ffffffff
domain3 ffffffff,ffffffff,ffffffff,ffffffff
[...]
> Are you using cgroup hierarchy ?
>
No cgroup hierarchy during the test.
>>
>> The average cost of load balance seems quite smaller than the default sysctl_sched_migration_cost
>> which is 500000(500ms).
>
> AFAICT, it is 500us not 500ms
>
yes it's 500us. sorry for the wrong unit.
>>
>> So I have some RFC questions:
>> 1. how is the default 500000 (500ms) migration cost is measured or caculated?
>
> 500us not ms
>
> I would say that it's a heuristic value that works for most of system
> but it should probably be tuned per platform. But also note that it's
> quite difficult to get a correct value
>
thanks for the explanation. I agree that it should be tuned per platform, and maybe also
per workload. Current default value seems to have be well tuned on x86 but not on the some
arm64 platforms.
Thanks.
>> The value has never changed in the past decade. I dig into the git commits and find it was introduced
>> in da84d9617672 ("sched: reintroduce cache-hot affinity"). But it didn't explain how did this value come.
>> 2. The ABI now has been removed from sysctl and moved to debugfs. As tuning this can improve the performance
>> of some workloads on some platforms, maybe it's better to make it a formal sysctl again with docs?
>>
>> I'll be appreciated for any comments and replies!
>>
>> Thanks,
>> Yicong
>>
>>
>
> .
>
On 2021/9/14 19:30, Peter Zijlstra wrote:
> On Tue, Sep 14, 2021 at 03:27:09PM +0800, Yicong Yang wrote:
>> 2. The ABI now has been removed from sysctl and moved to debugfs. As tuning this can improve the performance
>> of some workloads on some platforms, maybe it's better to make it a formal sysctl again with docs?
>
> It never was an ABI, there is nothing to restore. It has always been
> CONFIG_SCHED_DEBUG.
>
It's right that CONIG_SCHED_DEBUG is on for most releases and it's same to tune
it through debugfs. So I'm not with a strong heart to restore it but just curious
about this magic value since it does have some influence when tuning this on my platform.
> I'm open to topology based improvements to the code, but I don't think
> user tunables are a good way.
>
sure, it's better to make the scheduler topology adapted rather than manually tuned, but
certainly it's not that easy to achieve. Maybe I can investigate the whole story
first, seems we didn't use a constant migration_cost_ns at very beginning, to see if there's
any inspiration.
Thanks.
> .
>
On Tue, 14 Sept 2021 at 14:08, Yicong Yang <[email protected]> wrote:
>
> Hi Vincent,
>
> thanks for the reply!
>
> On 2021/9/14 17:04, Vincent Guittot wrote:
> > Hi Yicong,
> >
> > On Tue, 14 Sept 2021 at 09:27, Yicong Yang <[email protected]> wrote:
> >>
> >> Hi all,
> >>
> >> I noticed that some benchmark performance varies after tunning the sysctl_sched_migration_cost
> >> through /sys/kernel/debug/sched/migration_cost_ns on arm64. The default value is 500000, and
> >> I tried 10000, 100000, 1000000. Below are some results from mmtests, based on 5.14-release.
> >>
> >> On Kunpeng920 (128cores, 4numa, 2socket):
> >>
> >> pgbench (config-db-pgbench-timed-ro-medium)
> >> mig-cost-500000 mig-cost-100000 mig-cost-10000 mig-cost-1000000
> >> Hmean 1 9558.99 ( 0.00%) 9735.31 * 1.84%* 9410.84 * -1.55%* 9602.47 * 0.45%*
> >> Hmean 8 17615.90 ( 0.00%) 17439.78 * -1.00%* 18056.44 * 2.50%* 19222.18 * 9.12%*
> >> Hmean 12 25228.38 ( 0.00%) 25592.69 * 1.44%* 26739.06 * 5.99%* 27575.48 * 9.30%*
> >> Hmean 24 46623.27 ( 0.00%) 48853.30 * 4.78%* 47386.02 * 1.64%* 48542.94 * 4.12%*
> >> Hmean 32 60578.78 ( 0.00%) 62116.81 * 2.54%* 59961.36 * -1.02%* 58681.07 * -3.13%*
> >> Hmean 48 68159.12 ( 0.00%) 67867.90 ( -0.43%) 65631.79 * -3.71%* 66487.16 * -2.45%*
> >> Hmean 80 66894.87 ( 0.00%) 73440.92 * 9.79%* 68751.63 * 2.78%* 67326.70 ( 0.65%)
> >> Hmean 112 68582.27 ( 0.00%) 65339.90 * -4.73%* 68454.99 ( -0.19%) 67211.66 * -2.00%*
> >> Hmean 144 76290.98 ( 0.00%) 70455.65 * -7.65%* 64851.23 * -14.99%* 64940.61 * -14.88%*
> >> Hmean 172 63245.68 ( 0.00%) 68790.24 * 8.77%* 66246.46 * 4.74%* 69536.96 * 9.95%*
> >> Hmean 204 61793.47 ( 0.00%) 63711.62 * 3.10%* 66055.64 * 6.90%* 58023.20 * -6.10%*
> >> Hmean 236 61486.75 ( 0.00%) 68404.44 * 11.25%* 70499.70 * 14.66%* 58285.67 * -5.21%*
> >> Hmean 256 57476.13 ( 0.00%) 65645.83 * 14.21%* 69437.05 * 20.81%* 60518.05 * 5.29%*
> >>
> >> tbench (config-network-tbench)
> >> mig-cost-500000 mig-cost-100000 mig-cost-10000 mig-cost-1000000
> >> Hmean 1 333.12 ( 0.00%) 332.93 ( -0.06%) 335.34 * 0.67%* 334.36 * 0.37%*
> >> Hmean 2 665.88 ( 0.00%) 667.19 * 0.20%* 666.47 * 0.09%* 667.02 * 0.17%*
> >> Hmean 4 1324.10 ( 0.00%) 1312.23 * -0.90%* 1313.07 * -0.83%* 1315.13 * -0.68%*
> >> Hmean 8 2618.85 ( 0.00%) 2602.00 * -0.64%* 2577.49 * -1.58%* 2600.48 * -0.70%*
> >> Hmean 16 5100.74 ( 0.00%) 5068.80 * -0.63%* 5041.34 * -1.16%* 5069.78 * -0.61%*
> >> Hmean 32 8157.22 ( 0.00%) 8163.50 ( 0.08%) 7936.25 * -2.71%* 8329.18 * 2.11%*
> >> Hmean 64 4824.56 ( 0.00%) 4890.81 * 1.37%* 5319.97 * 10.27%* 4830.68 * 0.13%*
> >> Hmean 128 4635.17 ( 0.00%) 6810.90 * 46.94%* 5304.36 * 14.44%* 4516.06 * -2.57%*
> >> Hmean 256 8816.62 ( 0.00%) 8851.28 * 0.39%* 8448.76 * -4.17%* 6840.12 * -22.42%*
> >> Hmean 512 7825.56 ( 0.00%) 8538.04 * 9.10%* 8002.77 * 2.26%* 7946.54 * 1.55%*
> >>
> >> Also on Raspberrypi 4B:
> >>
> >> pgbench (config-db-pgbench-timed-ro-medium)
> >> mig-cost-500000 mig-cost-100000
> >> Hmean 1 1651.41 ( 0.00%) 3444.27 * 108.56%*
> >> Hmean 4 4015.83 ( 0.00%) 6883.21 * 71.40%*
> >> Hmean 7 4161.45 ( 0.00%) 6646.18 * 59.71%*
> >> Hmean 8 4277.28 ( 0.00%) 6764.60 * 58.15%*
> >>
> >> For tbench on Raspberrypi 4B and both pgbench and tbench on x86, tuning sysctl_sched_migration_cost
> >> doesn't have such huge difference and will have some degradations (max -8% on x86 for pgbench) in some cases.
> >>
> >> The sysctl_sched_migration_cost will affects the frequency of load balance. It will affect
> >
> > So it doesn't affect the periodic load but only the newly idle load balance
> >
>
> In load_balance(), it's used to judge whether a task is hot in task_hot(). so I think it
> participates in the periodic load balance.
Not really. The periodic load balance always happens but task_hot is
used to skip task that have recently run on the cpu and select older
tasks instead
At the contrary, sysctl_sched_migration_cost is used to decide if we
should abort newly_idle_load_balance
As a side point, would be good to know if the improvement and
regression seen in your tests are more linked to the task hotness or
for skipping/aborting newly idle load balance
>
> >> directly in task_hot() and newidle_balance() to decide whether we can do a migration or load
> >> balance. And affects other parameters like rq->avg_idle, rq->max_idle_balance_cost and
> >> sd->max_newidle_lb_cost to indirectly affect the load balance process. These parameters record
> >> the load_balance() cost and will be limited up to sysctl_sched_migration_cost, so I measure
> >> the average cost of load_balance() on Kunpeng920 with bcc tools(./funclantency load_balance -d 10):
> >>
> >> system status idle 50%load 100%load
> >> avg cost 3160ns 4790ns 7563ns
> >
> > What is the setup of your test ? has this been measured during the
> > benchmarks above ?
> >
>
> I use stress-ng to generate the load. Since it's a 128core server, `stress-ng -c 64` for
> 50% load, and `stress-ng -c 128` for 100% load. This is not measured during the benchmarks'
> process.
I don't think this is the best benchmark to evaluate the real cost of
load_balance because it create always running task and you measure
only the periodic load balance and not the newly load balance which is
the one really impacted by sysctl_sched_migration_cost
>
> > Also, do you have more details about the topology and the number of
> > sched domain ?
> >
>
> sure. for `numactl -H`:
>
> available: 4 nodes (0-3)
> node 0 cpus: 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
> node 0 size: 257149 MB
> node 0 free: 253518 MB
> node 1 cpus: 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63
> node 1 size: 193531 MB
> node 1 free: 192916 MB
> node 2 cpus: 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95
> node 2 size: 96763 MB
> node 2 free: 92654 MB
> node 3 cpus: 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127
> node 3 size: 127668 MB
> node 3 free: 125846 MB
> node distances:
> node 0 1 2 3
> 0: 10 12 20 22
> 1: 12 10 22 24
> 2: 20 22 10 12
> 3: 22 24 12 10
>
> Kunpeng 920 is non-smt. There're 4 level domains and below is part of the /proc/schedstat:
> [...]
> cpu0
> domain0 00000000,00000000,00000000,ffffffff
> domain1 00000000,00000000,ffffffff,ffffffff
> domain2 00000000,ffffffff,ffffffff,ffffffff
> domain3 ffffffff,ffffffff,ffffffff,ffffffff
Because of the large difference between the number of cpus at 1st and
last level, an average duration of load_balance() is not really
meaningful and we can expect a factor of 4 between smallest and larger
one
> [...]
> cpu32
> domain0 00000000,00000000,ffffffff,00000000
> domain1 00000000,00000000,ffffffff,ffffffff
> domain2 00000000,ffffffff,ffffffff,ffffffff
> domain3 ffffffff,ffffffff,ffffffff,ffffffff
> [...]
> cpu64
> domain0 00000000,ffffffff,00000000,00000000
> domain1 ffffffff,ffffffff,00000000,00000000
> domain2 ffffffff,ffffffff,00000000,ffffffff
> domain3 ffffffff,ffffffff,ffffffff,ffffffff
> [...]
> cpu96
> domain0 ffffffff,00000000,00000000,00000000
> domain1 ffffffff,ffffffff,00000000,00000000
> domain2 ffffffff,ffffffff,00000000,ffffffff
> domain3 ffffffff,ffffffff,ffffffff,ffffffff
> [...]
>
> > Are you using cgroup hierarchy ?
> >
>
> No cgroup hierarchy during the test.
This can slow down a bit the load_balance so might be good to take
that into account
>
> >>
> >> The average cost of load balance seems quite smaller than the default sysctl_sched_migration_cost
> >> which is 500000(500ms).
> >
> > AFAICT, it is 500us not 500ms
> >
>
> yes it's 500us. sorry for the wrong unit.
>
> >>
> >> So I have some RFC questions:
> >> 1. how is the default 500000 (500ms) migration cost is measured or caculated?
> >
> > 500us not ms
> >
> > I would say that it's a heuristic value that works for most of system
> > but it should probably be tuned per platform. But also note that it's
> > quite difficult to get a correct value
> >
>
> thanks for the explanation. I agree that it should be tuned per platform, and maybe also
> per workload. Current default value seems to have be well tuned on x86 but not on the some
> arm64 platforms.
Adjusting the value based on the platform seems reasonable although
i'm not sure which input should be used (arch type / interconnect
bandwidth / cache size / number of cpu per cache level ...)
>
> Thanks.
>
> >> The value has never changed in the past decade. I dig into the git commits and find it was introduced
> >> in da84d9617672 ("sched: reintroduce cache-hot affinity"). But it didn't explain how did this value come.
> >> 2. The ABI now has been removed from sysctl and moved to debugfs. As tuning this can improve the performance
> >> of some workloads on some platforms, maybe it's better to make it a formal sysctl again with docs?
> >>
> >> I'll be appreciated for any comments and replies!
> >>
> >> Thanks,
> >> Yicong
> >>
> >>
> >
> > .
> >
>
On 2021/9/14 20:55, Vincent Guittot wrote:
> On Tue, 14 Sept 2021 at 14:08, Yicong Yang <[email protected]> wrote:
>>
>> Hi Vincent,
>>
>> thanks for the reply!
>>
>> On 2021/9/14 17:04, Vincent Guittot wrote:
>>> Hi Yicong,
>>>
>>> On Tue, 14 Sept 2021 at 09:27, Yicong Yang <[email protected]> wrote:
>>>>
>>>> Hi all,
>>>>
>>>> I noticed that some benchmark performance varies after tunning the sysctl_sched_migration_cost
>>>> through /sys/kernel/debug/sched/migration_cost_ns on arm64. The default value is 500000, and
>>>> I tried 10000, 100000, 1000000. Below are some results from mmtests, based on 5.14-release.
>>>>
>>>> On Kunpeng920 (128cores, 4numa, 2socket):
>>>>
>>>> pgbench (config-db-pgbench-timed-ro-medium)
>>>> mig-cost-500000 mig-cost-100000 mig-cost-10000 mig-cost-1000000
>>>> Hmean 1 9558.99 ( 0.00%) 9735.31 * 1.84%* 9410.84 * -1.55%* 9602.47 * 0.45%*
>>>> Hmean 8 17615.90 ( 0.00%) 17439.78 * -1.00%* 18056.44 * 2.50%* 19222.18 * 9.12%*
>>>> Hmean 12 25228.38 ( 0.00%) 25592.69 * 1.44%* 26739.06 * 5.99%* 27575.48 * 9.30%*
>>>> Hmean 24 46623.27 ( 0.00%) 48853.30 * 4.78%* 47386.02 * 1.64%* 48542.94 * 4.12%*
>>>> Hmean 32 60578.78 ( 0.00%) 62116.81 * 2.54%* 59961.36 * -1.02%* 58681.07 * -3.13%*
>>>> Hmean 48 68159.12 ( 0.00%) 67867.90 ( -0.43%) 65631.79 * -3.71%* 66487.16 * -2.45%*
>>>> Hmean 80 66894.87 ( 0.00%) 73440.92 * 9.79%* 68751.63 * 2.78%* 67326.70 ( 0.65%)
>>>> Hmean 112 68582.27 ( 0.00%) 65339.90 * -4.73%* 68454.99 ( -0.19%) 67211.66 * -2.00%*
>>>> Hmean 144 76290.98 ( 0.00%) 70455.65 * -7.65%* 64851.23 * -14.99%* 64940.61 * -14.88%*
>>>> Hmean 172 63245.68 ( 0.00%) 68790.24 * 8.77%* 66246.46 * 4.74%* 69536.96 * 9.95%*
>>>> Hmean 204 61793.47 ( 0.00%) 63711.62 * 3.10%* 66055.64 * 6.90%* 58023.20 * -6.10%*
>>>> Hmean 236 61486.75 ( 0.00%) 68404.44 * 11.25%* 70499.70 * 14.66%* 58285.67 * -5.21%*
>>>> Hmean 256 57476.13 ( 0.00%) 65645.83 * 14.21%* 69437.05 * 20.81%* 60518.05 * 5.29%*
>>>>
>>>> tbench (config-network-tbench)
>>>> mig-cost-500000 mig-cost-100000 mig-cost-10000 mig-cost-1000000
>>>> Hmean 1 333.12 ( 0.00%) 332.93 ( -0.06%) 335.34 * 0.67%* 334.36 * 0.37%*
>>>> Hmean 2 665.88 ( 0.00%) 667.19 * 0.20%* 666.47 * 0.09%* 667.02 * 0.17%*
>>>> Hmean 4 1324.10 ( 0.00%) 1312.23 * -0.90%* 1313.07 * -0.83%* 1315.13 * -0.68%*
>>>> Hmean 8 2618.85 ( 0.00%) 2602.00 * -0.64%* 2577.49 * -1.58%* 2600.48 * -0.70%*
>>>> Hmean 16 5100.74 ( 0.00%) 5068.80 * -0.63%* 5041.34 * -1.16%* 5069.78 * -0.61%*
>>>> Hmean 32 8157.22 ( 0.00%) 8163.50 ( 0.08%) 7936.25 * -2.71%* 8329.18 * 2.11%*
>>>> Hmean 64 4824.56 ( 0.00%) 4890.81 * 1.37%* 5319.97 * 10.27%* 4830.68 * 0.13%*
>>>> Hmean 128 4635.17 ( 0.00%) 6810.90 * 46.94%* 5304.36 * 14.44%* 4516.06 * -2.57%*
>>>> Hmean 256 8816.62 ( 0.00%) 8851.28 * 0.39%* 8448.76 * -4.17%* 6840.12 * -22.42%*
>>>> Hmean 512 7825.56 ( 0.00%) 8538.04 * 9.10%* 8002.77 * 2.26%* 7946.54 * 1.55%*
>>>>
>>>> Also on Raspberrypi 4B:
>>>>
>>>> pgbench (config-db-pgbench-timed-ro-medium)
>>>> mig-cost-500000 mig-cost-100000
>>>> Hmean 1 1651.41 ( 0.00%) 3444.27 * 108.56%*
>>>> Hmean 4 4015.83 ( 0.00%) 6883.21 * 71.40%*
>>>> Hmean 7 4161.45 ( 0.00%) 6646.18 * 59.71%*
>>>> Hmean 8 4277.28 ( 0.00%) 6764.60 * 58.15%*
>>>>
>>>> For tbench on Raspberrypi 4B and both pgbench and tbench on x86, tuning sysctl_sched_migration_cost
>>>> doesn't have such huge difference and will have some degradations (max -8% on x86 for pgbench) in some cases.
>>>>
>>>> The sysctl_sched_migration_cost will affects the frequency of load balance. It will affect
>>>
>>> So it doesn't affect the periodic load but only the newly idle load balance
>>>
>>
>> In load_balance(), it's used to judge whether a task is hot in task_hot(). so I think it
>> participates in the periodic load balance.
>
> Not really. The periodic load balance always happens but task_hot is
> used to skip task that have recently run on the cpu and select older
> tasks instead
> At the contrary, sysctl_sched_migration_cost is used to decide if we
> should abort newly_idle_load_balance
>
well. I think I get it. In periodic load balance sysctl_sched_migration_cost will affect
which task we choose to migrate but won't abort the process like what it does
in new idle balance.
> As a side point, would be good to know if the improvement and
> regression seen in your tests are more linked to the task hotness or
> for skipping/aborting newly idle load balance
>
sure. I think I can get some hints by comparing the scheduler statistics
after tuning sysctl_sched_migration_cost.
>>
>>>> directly in task_hot() and newidle_balance() to decide whether we can do a migration or load
>>>> balance. And affects other parameters like rq->avg_idle, rq->max_idle_balance_cost and
>>>> sd->max_newidle_lb_cost to indirectly affect the load balance process. These parameters record
>>>> the load_balance() cost and will be limited up to sysctl_sched_migration_cost, so I measure
>>>> the average cost of load_balance() on Kunpeng920 with bcc tools(./funclantency load_balance -d 10):
>>>>
>>>> system status idle 50%load 100%load
>>>> avg cost 3160ns 4790ns 7563ns
>>>
>>> What is the setup of your test ? has this been measured during the
>>> benchmarks above ?
>>>
>>
>> I use stress-ng to generate the load. Since it's a 128core server, `stress-ng -c 64` for
>> 50% load, and `stress-ng -c 128` for 100% load. This is not measured during the benchmarks'
>> process.
>
> I don't think this is the best benchmark to evaluate the real cost of
> load_balance because it create always running task and you measure
> only the periodic load balance and not the newly load balance which is
> the one really impacted by sysctl_sched_migration_cost
>
it's right. It doesn't cover the newidle balance case and bcc is based on kprobe which
may have large latency on arm64 [1]. My original purpose is not to measure it accurately
but to see whehter the cost is comparable to the sysctl_sched_migration_cost.
[1] https://lore.kernel.org/lkml/[email protected]/
>>
>>> Also, do you have more details about the topology and the number of
>>> sched domain ?
>>>
>>
>> sure. for `numactl -H`:
>>
>> available: 4 nodes (0-3)
>> node 0 cpus: 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
>> node 0 size: 257149 MB
>> node 0 free: 253518 MB
>> node 1 cpus: 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63
>> node 1 size: 193531 MB
>> node 1 free: 192916 MB
>> node 2 cpus: 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95
>> node 2 size: 96763 MB
>> node 2 free: 92654 MB
>> node 3 cpus: 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127
>> node 3 size: 127668 MB
>> node 3 free: 125846 MB
>> node distances:
>> node 0 1 2 3
>> 0: 10 12 20 22
>> 1: 12 10 22 24
>> 2: 20 22 10 12
>> 3: 22 24 12 10
>>
>> Kunpeng 920 is non-smt. There're 4 level domains and below is part of the /proc/schedstat:
>> [...]
>> cpu0
>> domain0 00000000,00000000,00000000,ffffffff
>> domain1 00000000,00000000,ffffffff,ffffffff
>> domain2 00000000,ffffffff,ffffffff,ffffffff
>> domain3 ffffffff,ffffffff,ffffffff,ffffffff
>
> Because of the large difference between the number of cpus at 1st and
> last level, an average duration of load_balance() is not really
> meaningful and we can expect a factor of 4 between smallest and larger
> one
>
yes, the larger domain may have larger cost. I only show the average value
here while I got a histgram of the cost distribution as well.
the min range means where the minimal values fall in while the max range
means where the maximum values fall in. Counts means how many times
load_balance() is measured.
min range(counts) max range(counts) total counts
idle 256-511(456) 16384-32767(16) 14047
50% load 256-511(4018) 16382-32767(140) 57908
100%load 1024-2047(64) 32768-65535(8) 2582
Load balance is more frequent on a half loaded system while it takes more time
when it's well loaded.
funclatency tools: https://github.com/iovisor/bcc/blob/master/tools/funclatency.py
>> [...]
>> cpu32
>> domain0 00000000,00000000,ffffffff,00000000
>> domain1 00000000,00000000,ffffffff,ffffffff
>> domain2 00000000,ffffffff,ffffffff,ffffffff
>> domain3 ffffffff,ffffffff,ffffffff,ffffffff
>> [...]
>> cpu64
>> domain0 00000000,ffffffff,00000000,00000000
>> domain1 ffffffff,ffffffff,00000000,00000000
>> domain2 ffffffff,ffffffff,00000000,ffffffff
>> domain3 ffffffff,ffffffff,ffffffff,ffffffff
>> [...]
>> cpu96
>> domain0 ffffffff,00000000,00000000,00000000
>> domain1 ffffffff,ffffffff,00000000,00000000
>> domain2 ffffffff,ffffffff,00000000,ffffffff
>> domain3 ffffffff,ffffffff,ffffffff,ffffffff
>> [...]
>>
>>> Are you using cgroup hierarchy ?
>>>
>>
>> No cgroup hierarchy during the test.
>
> This can slow down a bit the load_balance so might be good to take
> that into account
>
If I run the test in a cgroup, the load balance will only be performed
on the cpuset rather than the whole system and the scan will be faster as
the range narrowed. Is that the reason here?
Thanks.
>>
>>>>
>>>> The average cost of load balance seems quite smaller than the default sysctl_sched_migration_cost
>>>> which is 500000(500ms).
>>>
>>> AFAICT, it is 500us not 500ms
>>>
>>
>> yes it's 500us. sorry for the wrong unit.
>>
>>>>
>>>> So I have some RFC questions:
>>>> 1. how is the default 500000 (500ms) migration cost is measured or caculated?
>>>
>>> 500us not ms
>>>
>>> I would say that it's a heuristic value that works for most of system
>>> but it should probably be tuned per platform. But also note that it's
>>> quite difficult to get a correct value
>>>
>>
>> thanks for the explanation. I agree that it should be tuned per platform, and maybe also
>> per workload. Current default value seems to have be well tuned on x86 but not on the some
>> arm64 platforms.
>
> Adjusting the value based on the platform seems reasonable although
> i'm not sure which input should be used (arch type / interconnect
> bandwidth / cache size / number of cpu per cache level ...)
>
>>
>> Thanks.
>>
>>>> The value has never changed in the past decade. I dig into the git commits and find it was introduced
>>>> in da84d9617672 ("sched: reintroduce cache-hot affinity"). But it didn't explain how did this value come.
>>>> 2. The ABI now has been removed from sysctl and moved to debugfs. As tuning this can improve the performance
>>>> of some workloads on some platforms, maybe it's better to make it a formal sysctl again with docs?
>>>>
>>>> I'll be appreciated for any comments and replies!
>>>>
>>>> Thanks,
>>>> Yicong
>>>>
>>>>
>>>
>>> .
>>>
>>
>
> .
>
On Wed, 15 Sept 2021 at 10:34, Yicong Yang <[email protected]> wrote:
>
> On 2021/9/14 20:55, Vincent Guittot wrote:
> > On Tue, 14 Sept 2021 at 14:08, Yicong Yang <[email protected]> wrote:
> >>
> >> Hi Vincent,
> >>
> >> thanks for the reply!
> >>
> >> On 2021/9/14 17:04, Vincent Guittot wrote:
> >>> Hi Yicong,
> >>>
> >>> On Tue, 14 Sept 2021 at 09:27, Yicong Yang <[email protected]> wrote:
> >>>>
> >>>> Hi all,
> >>>>
> >>>> I noticed that some benchmark performance varies after tunning the sysctl_sched_migration_cost
> >>>> through /sys/kernel/debug/sched/migration_cost_ns on arm64. The default value is 500000, and
> >>>> I tried 10000, 100000, 1000000. Below are some results from mmtests, based on 5.14-release.
> >>>>
> >>>> On Kunpeng920 (128cores, 4numa, 2socket):
> >>>>
> >>>> pgbench (config-db-pgbench-timed-ro-medium)
> >>>> mig-cost-500000 mig-cost-100000 mig-cost-10000 mig-cost-1000000
> >>>> Hmean 1 9558.99 ( 0.00%) 9735.31 * 1.84%* 9410.84 * -1.55%* 9602.47 * 0.45%*
> >>>> Hmean 8 17615.90 ( 0.00%) 17439.78 * -1.00%* 18056.44 * 2.50%* 19222.18 * 9.12%*
> >>>> Hmean 12 25228.38 ( 0.00%) 25592.69 * 1.44%* 26739.06 * 5.99%* 27575.48 * 9.30%*
> >>>> Hmean 24 46623.27 ( 0.00%) 48853.30 * 4.78%* 47386.02 * 1.64%* 48542.94 * 4.12%*
> >>>> Hmean 32 60578.78 ( 0.00%) 62116.81 * 2.54%* 59961.36 * -1.02%* 58681.07 * -3.13%*
> >>>> Hmean 48 68159.12 ( 0.00%) 67867.90 ( -0.43%) 65631.79 * -3.71%* 66487.16 * -2.45%*
> >>>> Hmean 80 66894.87 ( 0.00%) 73440.92 * 9.79%* 68751.63 * 2.78%* 67326.70 ( 0.65%)
> >>>> Hmean 112 68582.27 ( 0.00%) 65339.90 * -4.73%* 68454.99 ( -0.19%) 67211.66 * -2.00%*
> >>>> Hmean 144 76290.98 ( 0.00%) 70455.65 * -7.65%* 64851.23 * -14.99%* 64940.61 * -14.88%*
> >>>> Hmean 172 63245.68 ( 0.00%) 68790.24 * 8.77%* 66246.46 * 4.74%* 69536.96 * 9.95%*
> >>>> Hmean 204 61793.47 ( 0.00%) 63711.62 * 3.10%* 66055.64 * 6.90%* 58023.20 * -6.10%*
> >>>> Hmean 236 61486.75 ( 0.00%) 68404.44 * 11.25%* 70499.70 * 14.66%* 58285.67 * -5.21%*
> >>>> Hmean 256 57476.13 ( 0.00%) 65645.83 * 14.21%* 69437.05 * 20.81%* 60518.05 * 5.29%*
> >>>>
> >>>> tbench (config-network-tbench)
> >>>> mig-cost-500000 mig-cost-100000 mig-cost-10000 mig-cost-1000000
> >>>> Hmean 1 333.12 ( 0.00%) 332.93 ( -0.06%) 335.34 * 0.67%* 334.36 * 0.37%*
> >>>> Hmean 2 665.88 ( 0.00%) 667.19 * 0.20%* 666.47 * 0.09%* 667.02 * 0.17%*
> >>>> Hmean 4 1324.10 ( 0.00%) 1312.23 * -0.90%* 1313.07 * -0.83%* 1315.13 * -0.68%*
> >>>> Hmean 8 2618.85 ( 0.00%) 2602.00 * -0.64%* 2577.49 * -1.58%* 2600.48 * -0.70%*
> >>>> Hmean 16 5100.74 ( 0.00%) 5068.80 * -0.63%* 5041.34 * -1.16%* 5069.78 * -0.61%*
> >>>> Hmean 32 8157.22 ( 0.00%) 8163.50 ( 0.08%) 7936.25 * -2.71%* 8329.18 * 2.11%*
> >>>> Hmean 64 4824.56 ( 0.00%) 4890.81 * 1.37%* 5319.97 * 10.27%* 4830.68 * 0.13%*
> >>>> Hmean 128 4635.17 ( 0.00%) 6810.90 * 46.94%* 5304.36 * 14.44%* 4516.06 * -2.57%*
> >>>> Hmean 256 8816.62 ( 0.00%) 8851.28 * 0.39%* 8448.76 * -4.17%* 6840.12 * -22.42%*
> >>>> Hmean 512 7825.56 ( 0.00%) 8538.04 * 9.10%* 8002.77 * 2.26%* 7946.54 * 1.55%*
> >>>>
> >>>> Also on Raspberrypi 4B:
> >>>>
> >>>> pgbench (config-db-pgbench-timed-ro-medium)
> >>>> mig-cost-500000 mig-cost-100000
> >>>> Hmean 1 1651.41 ( 0.00%) 3444.27 * 108.56%*
> >>>> Hmean 4 4015.83 ( 0.00%) 6883.21 * 71.40%*
> >>>> Hmean 7 4161.45 ( 0.00%) 6646.18 * 59.71%*
> >>>> Hmean 8 4277.28 ( 0.00%) 6764.60 * 58.15%*
> >>>>
> >>>> For tbench on Raspberrypi 4B and both pgbench and tbench on x86, tuning sysctl_sched_migration_cost
> >>>> doesn't have such huge difference and will have some degradations (max -8% on x86 for pgbench) in some cases.
> >>>>
> >>>> The sysctl_sched_migration_cost will affects the frequency of load balance. It will affect
> >>>
> >>> So it doesn't affect the periodic load but only the newly idle load balance
> >>>
> >>
> >> In load_balance(), it's used to judge whether a task is hot in task_hot(). so I think it
> >> participates in the periodic load balance.
> >
> > Not really. The periodic load balance always happens but task_hot is
> > used to skip task that have recently run on the cpu and select older
> > tasks instead
> > At the contrary, sysctl_sched_migration_cost is used to decide if we
> > should abort newly_idle_load_balance
> >
>
> well. I think I get it. In periodic load balance sysctl_sched_migration_cost will affect
> which task we choose to migrate but won't abort the process like what it does
> in new idle balance.
>
> > As a side point, would be good to know if the improvement and
> > regression seen in your tests are more linked to the task hotness or
> > for skipping/aborting newly idle load balance
> >
>
> sure. I think I can get some hints by comparing the scheduler statistics
> after tuning sysctl_sched_migration_cost.
>
> >>
> >>>> directly in task_hot() and newidle_balance() to decide whether we can do a migration or load
> >>>> balance. And affects other parameters like rq->avg_idle, rq->max_idle_balance_cost and
> >>>> sd->max_newidle_lb_cost to indirectly affect the load balance process. These parameters record
> >>>> the load_balance() cost and will be limited up to sysctl_sched_migration_cost, so I measure
> >>>> the average cost of load_balance() on Kunpeng920 with bcc tools(./funclantency load_balance -d 10):
> >>>>
> >>>> system status idle 50%load 100%load
> >>>> avg cost 3160ns 4790ns 7563ns
> >>>
> >>> What is the setup of your test ? has this been measured during the
> >>> benchmarks above ?
> >>>
> >>
> >> I use stress-ng to generate the load. Since it's a 128core server, `stress-ng -c 64` for
> >> 50% load, and `stress-ng -c 128` for 100% load. This is not measured during the benchmarks'
> >> process.
> >
> > I don't think this is the best benchmark to evaluate the real cost of
> > load_balance because it create always running task and you measure
> > only the periodic load balance and not the newly load balance which is
> > the one really impacted by sysctl_sched_migration_cost
> >
>
> it's right. It doesn't cover the newidle balance case and bcc is based on kprobe which
> may have large latency on arm64 [1]. My original purpose is not to measure it accurately
> but to see whehter the cost is comparable to the sysctl_sched_migration_cost.
>
> [1] https://lore.kernel.org/lkml/[email protected]/
>
> >>
> >>> Also, do you have more details about the topology and the number of
> >>> sched domain ?
> >>>
> >>
> >> sure. for `numactl -H`:
> >>
> >> available: 4 nodes (0-3)
> >> node 0 cpus: 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
> >> node 0 size: 257149 MB
> >> node 0 free: 253518 MB
> >> node 1 cpus: 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63
> >> node 1 size: 193531 MB
> >> node 1 free: 192916 MB
> >> node 2 cpus: 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95
> >> node 2 size: 96763 MB
> >> node 2 free: 92654 MB
> >> node 3 cpus: 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127
> >> node 3 size: 127668 MB
> >> node 3 free: 125846 MB
> >> node distances:
> >> node 0 1 2 3
> >> 0: 10 12 20 22
> >> 1: 12 10 22 24
> >> 2: 20 22 10 12
> >> 3: 22 24 12 10
> >>
> >> Kunpeng 920 is non-smt. There're 4 level domains and below is part of the /proc/schedstat:
> >> [...]
> >> cpu0
> >> domain0 00000000,00000000,00000000,ffffffff
> >> domain1 00000000,00000000,ffffffff,ffffffff
> >> domain2 00000000,ffffffff,ffffffff,ffffffff
> >> domain3 ffffffff,ffffffff,ffffffff,ffffffff
> >
> > Because of the large difference between the number of cpus at 1st and
> > last level, an average duration of load_balance() is not really
> > meaningful and we can expect a factor of 4 between smallest and larger
> > one
> >
>
> yes, the larger domain may have larger cost. I only show the average value
> here while I got a histgram of the cost distribution as well.
> the min range means where the minimal values fall in while the max range
> means where the maximum values fall in. Counts means how many times
> load_balance() is measured.
>
> min range(counts) max range(counts) total counts
> idle 256-511(456) 16384-32767(16) 14047
> 50% load 256-511(4018) 16382-32767(140) 57908
> 100%load 1024-2047(64) 32768-65535(8) 2582
>
> Load balance is more frequent on a half loaded system while it takes more time
> when it's well loaded.
>
> funclatency tools: https://github.com/iovisor/bcc/blob/master/tools/funclatency.py
>
> >> [...]
> >> cpu32
> >> domain0 00000000,00000000,ffffffff,00000000
> >> domain1 00000000,00000000,ffffffff,ffffffff
> >> domain2 00000000,ffffffff,ffffffff,ffffffff
> >> domain3 ffffffff,ffffffff,ffffffff,ffffffff
> >> [...]
> >> cpu64
> >> domain0 00000000,ffffffff,00000000,00000000
> >> domain1 ffffffff,ffffffff,00000000,00000000
> >> domain2 ffffffff,ffffffff,00000000,ffffffff
> >> domain3 ffffffff,ffffffff,ffffffff,ffffffff
> >> [...]
> >> cpu96
> >> domain0 ffffffff,00000000,00000000,00000000
> >> domain1 ffffffff,ffffffff,00000000,00000000
> >> domain2 ffffffff,ffffffff,00000000,ffffffff
> >> domain3 ffffffff,ffffffff,ffffffff,ffffffff
> >> [...]
> >>
> >>> Are you using cgroup hierarchy ?
> >>>
> >>
> >> No cgroup hierarchy during the test.
> >
> > This can slow down a bit the load_balance so might be good to take
> > that into account
> >
>
> If I run the test in a cgroup, the load balance will only be performed
> on the cpuset rather than the whole system and the scan will be faster as
> the range narrowed. Is that the reason here?
I didn't have cgroup cpuset in mind but the fair group scheduling
which scans all cpus and adds more cfs level and impacts the
update_blocked_averages(). But the latter is not accounted for in the
cost of newidle_balance so it will not impact your tests.
That being said, we should account for this duration which can be
significant in some cases. I'm going to prepare a patch to add the
cost of update_blocked_averages() which can be significant in some
cases
>
> Thanks.
>
> >>
> >>>>
> >>>> The average cost of load balance seems quite smaller than the default sysctl_sched_migration_cost
> >>>> which is 500000(500ms).
> >>>
> >>> AFAICT, it is 500us not 500ms
> >>>
> >>
> >> yes it's 500us. sorry for the wrong unit.
> >>
> >>>>
> >>>> So I have some RFC questions:
> >>>> 1. how is the default 500000 (500ms) migration cost is measured or caculated?
> >>>
> >>> 500us not ms
> >>>
> >>> I would say that it's a heuristic value that works for most of system
> >>> but it should probably be tuned per platform. But also note that it's
> >>> quite difficult to get a correct value
> >>>
> >>
> >> thanks for the explanation. I agree that it should be tuned per platform, and maybe also
> >> per workload. Current default value seems to have be well tuned on x86 but not on the some
> >> arm64 platforms.
> >
> > Adjusting the value based on the platform seems reasonable although
> > i'm not sure which input should be used (arch type / interconnect
> > bandwidth / cache size / number of cpu per cache level ...)
> >
> >>
> >> Thanks.
> >>
> >>>> The value has never changed in the past decade. I dig into the git commits and find it was introduced
> >>>> in da84d9617672 ("sched: reintroduce cache-hot affinity"). But it didn't explain how did this value come.
> >>>> 2. The ABI now has been removed from sysctl and moved to debugfs. As tuning this can improve the performance
> >>>> of some workloads on some platforms, maybe it's better to make it a formal sysctl again with docs?
> >>>>
> >>>> I'll be appreciated for any comments and replies!
> >>>>
> >>>> Thanks,
> >>>> Yicong
> >>>>
> >>>>
> >>>
> >>> .
> >>>
> >>
> >
> > .
> >
>
On Wed, Sep 15, 2021 at 12:55 AM Vincent Guittot
<[email protected]> wrote:
>
> On Tue, 14 Sept 2021 at 14:08, Yicong Yang <[email protected]> wrote:
> >
> > Hi Vincent,
> >
> > thanks for the reply!
> >
> > On 2021/9/14 17:04, Vincent Guittot wrote:
> > > Hi Yicong,
> > >
> > > On Tue, 14 Sept 2021 at 09:27, Yicong Yang <[email protected]> wrote:
> > >>
> > >> Hi all,
> > >>
> > >> I noticed that some benchmark performance varies after tunning the sysctl_sched_migration_cost
> > >> through /sys/kernel/debug/sched/migration_cost_ns on arm64. The default value is 500000, and
> > >> I tried 10000, 100000, 1000000. Below are some results from mmtests, based on 5.14-release.
> > >>
> > >> On Kunpeng920 (128cores, 4numa, 2socket):
> > >>
> > >> pgbench (config-db-pgbench-timed-ro-medium)
> > >> mig-cost-500000 mig-cost-100000 mig-cost-10000 mig-cost-1000000
> > >> Hmean 1 9558.99 ( 0.00%) 9735.31 * 1.84%* 9410.84 * -1.55%* 9602.47 * 0.45%*
> > >> Hmean 8 17615.90 ( 0.00%) 17439.78 * -1.00%* 18056.44 * 2.50%* 19222.18 * 9.12%*
> > >> Hmean 12 25228.38 ( 0.00%) 25592.69 * 1.44%* 26739.06 * 5.99%* 27575.48 * 9.30%*
> > >> Hmean 24 46623.27 ( 0.00%) 48853.30 * 4.78%* 47386.02 * 1.64%* 48542.94 * 4.12%*
> > >> Hmean 32 60578.78 ( 0.00%) 62116.81 * 2.54%* 59961.36 * -1.02%* 58681.07 * -3.13%*
> > >> Hmean 48 68159.12 ( 0.00%) 67867.90 ( -0.43%) 65631.79 * -3.71%* 66487.16 * -2.45%*
> > >> Hmean 80 66894.87 ( 0.00%) 73440.92 * 9.79%* 68751.63 * 2.78%* 67326.70 ( 0.65%)
> > >> Hmean 112 68582.27 ( 0.00%) 65339.90 * -4.73%* 68454.99 ( -0.19%) 67211.66 * -2.00%*
> > >> Hmean 144 76290.98 ( 0.00%) 70455.65 * -7.65%* 64851.23 * -14.99%* 64940.61 * -14.88%*
> > >> Hmean 172 63245.68 ( 0.00%) 68790.24 * 8.77%* 66246.46 * 4.74%* 69536.96 * 9.95%*
> > >> Hmean 204 61793.47 ( 0.00%) 63711.62 * 3.10%* 66055.64 * 6.90%* 58023.20 * -6.10%*
> > >> Hmean 236 61486.75 ( 0.00%) 68404.44 * 11.25%* 70499.70 * 14.66%* 58285.67 * -5.21%*
> > >> Hmean 256 57476.13 ( 0.00%) 65645.83 * 14.21%* 69437.05 * 20.81%* 60518.05 * 5.29%*
> > >>
> > >> tbench (config-network-tbench)
> > >> mig-cost-500000 mig-cost-100000 mig-cost-10000 mig-cost-1000000
> > >> Hmean 1 333.12 ( 0.00%) 332.93 ( -0.06%) 335.34 * 0.67%* 334.36 * 0.37%*
> > >> Hmean 2 665.88 ( 0.00%) 667.19 * 0.20%* 666.47 * 0.09%* 667.02 * 0.17%*
> > >> Hmean 4 1324.10 ( 0.00%) 1312.23 * -0.90%* 1313.07 * -0.83%* 1315.13 * -0.68%*
> > >> Hmean 8 2618.85 ( 0.00%) 2602.00 * -0.64%* 2577.49 * -1.58%* 2600.48 * -0.70%*
> > >> Hmean 16 5100.74 ( 0.00%) 5068.80 * -0.63%* 5041.34 * -1.16%* 5069.78 * -0.61%*
> > >> Hmean 32 8157.22 ( 0.00%) 8163.50 ( 0.08%) 7936.25 * -2.71%* 8329.18 * 2.11%*
> > >> Hmean 64 4824.56 ( 0.00%) 4890.81 * 1.37%* 5319.97 * 10.27%* 4830.68 * 0.13%*
> > >> Hmean 128 4635.17 ( 0.00%) 6810.90 * 46.94%* 5304.36 * 14.44%* 4516.06 * -2.57%*
> > >> Hmean 256 8816.62 ( 0.00%) 8851.28 * 0.39%* 8448.76 * -4.17%* 6840.12 * -22.42%*
> > >> Hmean 512 7825.56 ( 0.00%) 8538.04 * 9.10%* 8002.77 * 2.26%* 7946.54 * 1.55%*
> > >>
> > >> Also on Raspberrypi 4B:
> > >>
> > >> pgbench (config-db-pgbench-timed-ro-medium)
> > >> mig-cost-500000 mig-cost-100000
> > >> Hmean 1 1651.41 ( 0.00%) 3444.27 * 108.56%*
> > >> Hmean 4 4015.83 ( 0.00%) 6883.21 * 71.40%*
> > >> Hmean 7 4161.45 ( 0.00%) 6646.18 * 59.71%*
> > >> Hmean 8 4277.28 ( 0.00%) 6764.60 * 58.15%*
> > >>
> > >> For tbench on Raspberrypi 4B and both pgbench and tbench on x86, tuning sysctl_sched_migration_cost
> > >> doesn't have such huge difference and will have some degradations (max -8% on x86 for pgbench) in some cases.
> > >>
> > >> The sysctl_sched_migration_cost will affects the frequency of load balance. It will affect
> > >
> > > So it doesn't affect the periodic load but only the newly idle load balance
> > >
> >
> > In load_balance(), it's used to judge whether a task is hot in task_hot(). so I think it
> > participates in the periodic load balance.
>
> Not really. The periodic load balance always happens but task_hot is
> used to skip task that have recently run on the cpu and select older
> tasks instead
> At the contrary, sysctl_sched_migration_cost is used to decide if we
> should abort newly_idle_load_balance
>
> As a side point, would be good to know if the improvement and
> regression seen in your tests are more linked to the task hotness or
> for skipping/aborting newly idle load balance
>
> >
> > >> directly in task_hot() and newidle_balance() to decide whether we can do a migration or load
> > >> balance. And affects other parameters like rq->avg_idle, rq->max_idle_balance_cost and
> > >> sd->max_newidle_lb_cost to indirectly affect the load balance process. These parameters record
> > >> the load_balance() cost and will be limited up to sysctl_sched_migration_cost, so I measure
> > >> the average cost of load_balance() on Kunpeng920 with bcc tools(./funclantency load_balance -d 10):
> > >>
> > >> system status idle 50%load 100%load
> > >> avg cost 3160ns 4790ns 7563ns
> > >
> > > What is the setup of your test ? has this been measured during the
> > > benchmarks above ?
> > >
> >
> > I use stress-ng to generate the load. Since it's a 128core server, `stress-ng -c 64` for
> > 50% load, and `stress-ng -c 128` for 100% load. This is not measured during the benchmarks'
> > process.
>
> I don't think this is the best benchmark to evaluate the real cost of
> load_balance because it create always running task and you measure
> only the periodic load balance and not the newly load balance which is
> the one really impacted by sysctl_sched_migration_cost
>
> >
> > > Also, do you have more details about the topology and the number of
> > > sched domain ?
> > >
> >
> > sure. for `numactl -H`:
> >
> > available: 4 nodes (0-3)
> > node 0 cpus: 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
> > node 0 size: 257149 MB
> > node 0 free: 253518 MB
> > node 1 cpus: 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63
> > node 1 size: 193531 MB
> > node 1 free: 192916 MB
> > node 2 cpus: 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95
> > node 2 size: 96763 MB
> > node 2 free: 92654 MB
> > node 3 cpus: 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127
> > node 3 size: 127668 MB
> > node 3 free: 125846 MB
> > node distances:
> > node 0 1 2 3
> > 0: 10 12 20 22
> > 1: 12 10 22 24
> > 2: 20 22 10 12
> > 3: 22 24 12 10
> >
> > Kunpeng 920 is non-smt. There're 4 level domains and below is part of the /proc/schedstat:
> > [...]
> > cpu0
> > domain0 00000000,00000000,00000000,ffffffff
> > domain1 00000000,00000000,ffffffff,ffffffff
> > domain2 00000000,ffffffff,ffffffff,ffffffff
> > domain3 ffffffff,ffffffff,ffffffff,ffffffff
>
> Because of the large difference between the number of cpus at 1st and
> last level, an average duration of load_balance() is not really
> meaningful and we can expect a factor of 4 between smallest and larger
> one
I also think measuring the funclatency of load_balance() might not be the
proper way to estimate the cost of migration considering it might iterate
over several levels of domains:
for_each_domain(this_cpu, sd) {
int continue_balancing = 1;
u64 t0, domain_cost;
if (this_rq->avg_idle < curr_cost + sd->max_newidle_lb_cost) {
update_next_balance(sd, &next_balance);
break;
}
if (sd->flags & SD_BALANCE_NEWIDLE) {
t0 = sched_clock_cpu(this_cpu);
pulled_task = load_balance(this_cpu, this_rq,
sd, CPU_NEWLY_IDLE,
&continue_balancing);
domain_cost = sched_clock_cpu(this_cpu) - t0;
if (domain_cost > sd->max_newidle_lb_cost)
sd->max_newidle_lb_cost = domain_cost;
curr_cost += domain_cost;
}
update_next_balance(sd, &next_balance);
/*
* Stop searching for tasks to pull if there are
* now runnable tasks on this rq.
*/
if (pulled_task || this_rq->nr_running > 0 ||
this_rq->ttwu_pending)
break;
}
maybe worth adding some tracepoints at the start and the end of the
whole balance
procedure.
But even if we can get the avg, min and max figures afterwards, is it
really reasonable
to set the migration_cost according to the figure? migration cost
isn't only moving a
task, pulling a task from remote numa might mean huge cache coherence overhead.
I feel a couple of factors will determine the best sched_migration_cost:
1. hardware topology - how many sched levels, how many numas, how far
numa nodes are
2. cache coherence overhead between cpus in different topology
3. how fast each cpu is
4. if tasks are pinning numa, this might scale down/up the range LB
needs to be done
5. relax_domain_level bootargs
...
Thanks
barry