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  1. 18 11月, 2021 2 次提交
    • B
      sched: Add cluster scheduler level in core and related Kconfig for ARM64 · ac032ae3
      由 Barry Song 提交于 
      mainline inclusion
from tip/sched/core for v5.16
commit: 778c558f
category: feature
bugzilla: https://gitee.com/openeuler/kernel/issues/I4H33U
CVE: NA
Reference: https://lore.kernel.org/lkml/20210924085104.44806-1-21cnbao@gmail.com/

------------------------------------------------------------------------

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: NBarry Song <song.bao.hua@hisilicon.com>
Tested-by: NYicong Yang <yangyicong@hisilicon.com>
Signed-off-by: NPeter Zijlstra (Intel) <peterz@infradead.org>
Signed-off-by: NYicong Yang <yangyicong@hisilicon.com>
Reviewed-by: Ntao zeng <prime.zeng@hisilicon.com>
Signed-off-by: NZheng Zengkai <zhengzengkai@huawei.com>
      ac032ae3
    • J
      topology: Represent clusters of CPUs within a die · c84cd40a
      由 Jonathan Cameron 提交于 
      mainline inclusion
from tip/sched/core for v5.15-release
commit: c5e22fef
category: feature
bugzilla: https://gitee.com/openeuler/kernel/issues/I4GEZS
CVE: NA
Reference: https://lore.kernel.org/lkml/20210924085104.44806-1-21cnbao@gmail.com/

------------------------------------------------------------------------

Both ACPI and DT provide the ability to describe additional layers of
topology between that of individual cores and higher level constructs
such as the level at which the last level cache is shared.
In ACPI this can be represented in PPTT as a Processor Hierarchy
Node Structure [1] that is the parent of the CPU cores and in turn
has a parent Processor Hierarchy Nodes Structure representing
a higher level of topology.

For example Kunpeng 920 has 6 or 8 clusters in each NUMA node, and each
cluster has 4 cpus. All clusters share L3 cache data, but each cluster
has local L3 tag. On the other hand, each clusters will share some
internal system bus.

+-----------------------------------+                          +---------+
|  +------+    +------+             +--------------------------+         |
|  | CPU0 |    | cpu1 |             |    +-----------+         |         |
|  +------+    +------+             |    |           |         |         |
|                                   +----+    L3     |         |         |
|  +------+    +------+   cluster   |    |    tag    |         |         |
|  | CPU2 |    | CPU3 |             |    |           |         |         |
|  +------+    +------+             |    +-----------+         |         |
|                                   |                          |         |
+-----------------------------------+                          |         |
+-----------------------------------+                          |         |
|  +------+    +------+             +--------------------------+         |
|  |      |    |      |             |    +-----------+         |         |
|  +------+    +------+             |    |           |         |         |
|                                   |    |    L3     |         |         |
|  +------+    +------+             +----+    tag    |         |         |
|  |      |    |      |             |    |           |         |         |
|  +------+    +------+             |    +-----------+         |         |
|                                   |                          |         |
+-----------------------------------+                          |   L3    |
                                                               |   data  |
+-----------------------------------+                          |         |
|  +------+    +------+             |    +-----------+         |         |
|  |      |    |      |             |    |           |         |         |
|  +------+    +------+             +----+    L3     |         |         |
|                                   |    |    tag    |         |         |
|  +------+    +------+             |    |           |         |         |
|  |      |    |      |             |    +-----------+         |         |
|  +------+    +------+             +--------------------------+         |
+-----------------------------------|                          |         |
+-----------------------------------|                          |         |
|  +------+    +------+             +--------------------------+         |
|  |      |    |      |             |    +-----------+         |         |
|  +------+    +------+             |    |           |         |         |
|                                   +----+    L3     |         |         |
|  +------+    +------+             |    |    tag    |         |         |
|  |      |    |      |             |    |           |         |         |
|  +------+    +------+             |    +-----------+         |         |
|                                   |                          |         |
+-----------------------------------+                          |         |
+-----------------------------------+                          |         |
|  +------+    +------+             +--------------------------+         |
|  |      |    |      |             |   +-----------+          |         |
|  +------+    +------+             |   |           |          |         |
|                                   |   |    L3     |          |         |
|  +------+    +------+             +---+    tag    |          |         |
|  |      |    |      |             |   |           |          |         |
|  +------+    +------+             |   +-----------+          |         |
|                                   |                          |         |
+-----------------------------------+                          |         |
+-----------------------------------+                          |         |
|  +------+    +------+             +--------------------------+         |
|  |      |    |      |             |  +-----------+           |         |
|  +------+    +------+             |  |           |           |         |
|                                   |  |    L3     |           |         |
|  +------+    +------+             +--+    tag    |           |         |
|  |      |    |      |             |  |           |           |         |
|  +------+    +------+             |  +-----------+           |         |
|                                   |                          +---------+
+-----------------------------------+

That means spreading tasks among clusters will bring more bandwidth
while packing tasks within one cluster will lead to smaller cache
synchronization latency. So both kernel and userspace will have
a chance to leverage this topology to deploy tasks accordingly to
achieve either smaller cache latency within one cluster or an even
distribution of load among clusters for higher throughput.

This patch exposes cluster topology to both kernel and userspace.
Libraried like hwloc will know cluster by cluster_cpus and related
sysfs attributes. PoC of HWLOC support at [2].

Note this patch only handle the ACPI case.

Special consideration is needed for SMT processors, where it is
necessary to move 2 levels up the hierarchy from the leaf nodes
(thus skipping the processor core level).

Note that arm64 / ACPI does not provide any means of identifying
a die level in the topology but that may be unrelate to the cluster
level.

[1] ACPI Specification 6.3 - section 5.2.29.1 processor hierarchy node
    structure (Type 0)
[2] https://github.com/hisilicon/hwloc/tree/linux-clusterSigned-off-by: NJonathan Cameron <Jonathan.Cameron@huawei.com>
Signed-off-by: NTian Tao <tiantao6@hisilicon.com>
Signed-off-by: NBarry Song <song.bao.hua@hisilicon.com>
Signed-off-by: NPeter Zijlstra (Intel) <peterz@infradead.org>
Link: https://lore.kernel.org/r/20210924085104.44806-2-21cnbao@gmail.comSigned-off-by: NYicong Yang <yangyicong@hisilicon.com>
Reviewed-by: Ntao zeng <prime.zeng@hisilicon.com>
Signed-off-by: NZheng Zengkai <zhengzengkai@huawei.com>
      c84cd40a
  3. 15 11月, 2021 11 次提交
  5. 11 11月, 2021 3 次提交
  7. 30 10月, 2021 2 次提交
  9. 21 10月, 2021 22 次提交