mm/mempolicy: implement the sysfs-based weighted_interleave interface
Patch series "mm/mempolicy: weighted interleave mempolicy and sysfs
extension", v5.
Weighted interleave is a new interleave policy intended to make use of
heterogeneous memory environments appearing with CXL.
The existing interleave mechanism does an even round-robin distribution of
memory across all nodes in a nodemask, while weighted interleave
distributes memory across nodes according to a provided weight. (Weight =
# of page allocations per round)
Weighted interleave is intended to reduce average latency when bandwidth
is pressured - therefore increasing total throughput.
In other words: It allows greater use of the total available bandwidth in
a heterogeneous hardware environment (different hardware provides
different bandwidth capacity).
As bandwidth is pressured, latency increases - first linearly and then
exponentially. By keeping bandwidth usage distributed according to
available bandwidth, we therefore can reduce the average latency of a
cacheline fetch.
A good explanation of the bandwidth vs latency response curve:
https://mahmoudhatem.wordpress.com/2017/11/07/memory-bandwidth-vs-latency-response-curve/
From the article:
```
Constant region:
The latency response is fairly constant for the first 40%
of the sustained bandwidth.
Linear region:
In between 40% to 80% of the sustained bandwidth, the
latency response increases almost linearly with the bandwidth
demand of the system due to contention overhead by numerous
memory requests.
Exponential region:
Between 80% to 100% of the sustained bandwidth, the memory
latency is dominated by the contention latency which can be
as much as twice the idle latency or more.
Maximum sustained bandwidth :
Is 65% to 75% of the theoretical maximum bandwidth.
```
As a general rule of thumb:
* If bandwidth usage is low, latency does not increase. It is
optimal to place data in the nearest (lowest latency) device.
* If bandwidth usage is high, latency increases. It is optimal
to place data such that bandwidth use is optimized per-device.
This is the top line goal: Provide a user a mechanism to target using the
"maximum sustained bandwidth" of each hardware component in a heterogenous
memory system.
For example, the stream benchmark demonstrates that 1:1 (default)
interleave is actively harmful, while weighted interleave can be
beneficial. Default interleave distributes data such that too much
pressure is placed on devices with lower available bandwidth.
Stream Benchmark (vs DRAM, 1 Socket + 1 CXL Device)
Default interleave : -78% (slower than DRAM)
Global weighting : -6% to +4% (workload dependant)
Targeted weights : +2.5% to +4% (consistently better than DRAM)
Global means the task-policy was set (set_mempolicy), while targeted means
VMA policies were set (mbind2). We see weighted interleave is not always
beneficial when applied globally, but is always beneficial when applied to
bandwidth-driving memory regions.
There are 4 patches in this set:
1) Implement system-global interleave weights as sysfs extension
in mm/mempolicy.c. These weights are RCU protected, and a
default weight set is provided (all weights are 1 by default).
In future work, we intend to expose an interface for HMAT/CDAT
code to set reasonable default values based on the memory
configuration of the system discovered at boot/hotplug.
2) A mild refactor of some interleave-logic for re-use in the
new weighted interleave logic.
3) MPOL_WEIGHTED_INTERLEAVE extension for set_mempolicy/mbind
4) Protect interleave logic (weighted and normal) with the
mems_allowed seq cookie. If the nodemask changes while
accessing it during a rebind, just retry the access.
Included below are some performance and LTP test information,
and a sample numactl branch which can be used for testing.
= Performance summary =
(tests may have different configurations, see extended info below)
1) MLC (W2) : +38% over DRAM. +264% over default interleave.
MLC (W5) : +40% over DRAM. +226% over default interleave.
2) Stream : -6% to +4% over DRAM, +430% over default interleave.
3) XSBench : +19% over DRAM. +47% over default interleave.
= LTP Testing Summary =
existing mempolicy & mbind tests: pass
mempolicy & mbind + weighted interleave (global weights): pass
= version history
v5:
- style fixes
- mems_allowed cookie protection to detect rebind issues,
prevents spurious allocation failures and/or mis-allocations
- sparse warning fixes related to __rcu on local variables
=====================================================================
Performance tests - MLC
From - Ravi Jonnalagadda <ravis.opensrc@micron.com>
Hardware: Single-socket, multiple CXL memory expanders.
Workload: W2
Data Signature: 2:1 read:write
DRAM only bandwidth (GBps): 298.8
DRAM + CXL (default interleave) (GBps): 113.04
DRAM + CXL (weighted interleave)(GBps): 412.5
Gain over DRAM only: 1.38x
Gain over default interleave: 2.64x
Workload: W5
Data Signature: 1:1 read:write
DRAM only bandwidth (GBps): 273.2
DRAM + CXL (default interleave) (GBps): 117.23
DRAM + CXL (weighted interleave)(GBps): 382.7
Gain over DRAM only: 1.4x
Gain over default interleave: 2.26x
=====================================================================
Performance test - Stream
From - Gregory Price <gregory.price@memverge.com>
Hardware: Single socket, single CXL expander
numactl extension: https://github.com/gmprice/numactl/tree/weighted_interleave_master
Summary: 64 threads, ~18GB workload, 3GB per array, executed 100 times
Default interleave : -78% (slower than DRAM)
Global weighting : -6% to +4% (workload dependant)
mbind2 weights : +2.5% to +4% (consistently better than DRAM)
dram only:
numactl --cpunodebind=1 --membind=1 ./stream_c.exe --ntimes 100 --array-size 400M --malloc
Function Direction BestRateMBs AvgTime MinTime MaxTime
Copy: 0->0 200923.2 0.032662 0.031853 0.033301
Scale: 0->0 202123.0 0.032526 0.031664 0.032970
Add: 0->0 208873.2 0.047322 0.045961 0.047884
Triad: 0->0 208523.8 0.047262 0.046038 0.048414
CXL-only:
numactl --cpunodebind=1 -w --membind=2 ./stream_c.exe --ntimes 100 --array-size 400M --malloc
Copy: 0->0 22209.7 0.288661 0.288162 0.289342
Scale: 0->0 22288.2 0.287549 0.287147 0.288291
Add: 0->0 24419.1 0.393372 0.393135 0.393735
Triad: 0->0 24484.6 0.392337 0.392083 0.394331
Based on the above, the optimal weights are ~9:1
echo 9 > /sys/kernel/mm/mempolicy/weighted_interleave/node1
echo 1 > /sys/kernel/mm/mempolicy/weighted_interleave/node2
default interleave:
numactl --cpunodebind=1 --interleave=1,2 ./stream_c.exe --ntimes 100 --array-size 400M --malloc
Copy: 0->0 44666.2 0.143671 0.143285 0.144174
Scale: 0->0 44781.6 0.143256 0.142916 0.143713
Add: 0->0 48600.7 0.197719 0.197528 0.197858
Triad: 0->0 48727.5 0.197204 0.197014 0.197439
global weighted interleave:
numactl --cpunodebind=1 -w --interleave=1,2 ./stream_c.exe --ntimes 100 --array-size 400M --malloc
Copy: 0->0 190085.9 0.034289 0.033669 0.034645
Scale: 0->0 207677.4 0.031909 0.030817 0.033061
Add: 0->0 202036.8 0.048737 0.047516 0.053409
Triad: 0->0 217671.5 0.045819 0.044103 0.046755
targted regions w/ global weights (modified stream to mbind2 malloc'd regions))
numactl --cpunodebind=1 --membind=1 ./stream_c.exe -b --ntimes 100 --array-size 400M --malloc
Copy: 0->0 205827.0 0.031445 0.031094 0.031984
Scale: 0->0 208171.8 0.031320 0.030744 0.032505
Add: 0->0 217352.0 0.045087 0.044168 0.046515
Triad: 0->0 216884.8 0.045062 0.044263 0.046982
=====================================================================
Performance tests - XSBench
From - Hyeongtak Ji <hyeongtak.ji@sk.com>
Hardware: Single socket, Single CXL memory Expander
NUMA node 0: 56 logical cores, 128 GB memory
NUMA node 2: 96 GB CXL memory
Threads: 56
Lookups: 170,000,000
Summary: +19% over DRAM. +47% over default interleave.
Performance tests - XSBench
1. dram only
$ numactl -m 0 ./XSBench -s XL –p 5000000
Runtime: 36.235 seconds
Lookups/s: 4,691,618
2. default interleave
$ numactl –i 0,2 ./XSBench –s XL –p 5000000
Runtime: 55.243 seconds
Lookups/s: 3,077,293
3. weighted interleave
numactl –w –i 0,2 ./XSBench –s XL –p 5000000
Runtime: 29.262 seconds
Lookups/s: 5,809,513
=====================================================================
LTP Tests: https://github.com/gmprice/ltp/tree/mempolicy2
= Existing tests
set_mempolicy, get_mempolicy, mbind
MPOL_WEIGHTED_INTERLEAVE added manually to test basic functionality but
did not adjust tests for weighting. Basically the weights were set to 1,
which is the default, and it should behave the same as MPOL_INTERLEAVE if
logic is correct.
== set_mempolicy01 : passed 18, failed 0
== set_mempolicy02 : passed 10, failed 0
== set_mempolicy03 : passed 64, failed 0
== set_mempolicy04 : passed 32, failed 0
== set_mempolicy05 - n/a on non-x86
== set_mempolicy06 : passed 10, failed 0
this is set_mempolicy02 + MPOL_WEIGHTED_INTERLEAVE
== set_mempolicy07 : passed 32, failed 0
set_mempolicy04 + MPOL_WEIGHTED_INTERLEAVE
== get_mempolicy01 : passed 12, failed 0
change: added MPOL_WEIGHTED_INTERLEAVE
== get_mempolicy02 : passed 2, failed 0
== mbind01 : passed 15, failed 0
added MPOL_WEIGHTED_INTERLEAVE
== mbind02 : passed 4, failed 0
added MPOL_WEIGHTED_INTERLEAVE
== mbind03 : passed 16, failed 0
added MPOL_WEIGHTED_INTERLEAVE
== mbind04 : passed 48, failed 0
added MPOL_WEIGHTED_INTERLEAVE
=====================================================================
numactl (set_mempolicy) w/ global weighting test
numactl fork: https://github.com/gmprice/numactl/tree/weighted_interleave_master
command: numactl -w --interleave=0,1 ./eatmem
result (weights 1:1):
0176a000 weighted interleave:0-1 heap anon=65793 dirty=65793 active=0 N0=32897 N1=32896 kernelpagesize_kB=4
7fceeb9ff000 weighted interleave:0-1 anon=65537 dirty=65537 active=0 N0=32768 N1=32769 kernelpagesize_kB=4
50% distribution is correct
result (weights 5:1):
01b14000 weighted interleave:0-1 heap anon=65793 dirty=65793 active=0 N0=54828 N1=10965 kernelpagesize_kB=4
7f47a1dff000 weighted interleave:0-1 anon=65537 dirty=65537 active=0 N0=54614 N1=10923 kernelpagesize_kB=4
16.666% distribution is correct
result (weights 1:5):
01f07000 weighted interleave:0-1 heap anon=65793 dirty=65793 active=0 N0=10966 N1=54827 kernelpagesize_kB=4
7f17b1dff000 weighted interleave:0-1 anon=65537 dirty=65537 active=0 N0=10923 N1=54614 kernelpagesize_kB=4
16.666% distribution is correct
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
int main (void)
{
char* mem = malloc(1024*1024*256);
memset(mem, 1, 1024*1024*256);
for (int i = 0; i < ((1024*1024*256)/4096); i++)
{
mem = malloc(4096);
mem[0] = 1;
}
printf("done\n");
getchar();
return 0;
}
This patch (of 4):
This patch provides a way to set interleave weight information under sysfs
at /sys/kernel/mm/mempolicy/weighted_interleave/nodeN
The sysfs structure is designed as follows.
$ tree /sys/kernel/mm/mempolicy/
/sys/kernel/mm/mempolicy/ [1]
└── weighted_interleave [2]
├── node0 [3]
└── node1
Each file above can be explained as follows.
[1] mm/mempolicy: configuration interface for mempolicy subsystem
[2] weighted_interleave/: config interface for weighted interleave policy
[3] weighted_interleave/nodeN: weight for nodeN
If a node value is set to `0`, the system-default value will be used.
As of this patch, the system-default for all nodes is always 1.
Link: https://lkml.kernel.org/r/20240202170238.90004-1-gregory.price@memverge.com
Link: https://lkml.kernel.org/r/20240202170238.90004-2-gregory.price@memverge.com
Suggested-by: "Huang, Ying" <ying.huang@intel.com>
Signed-off-by: Rakie Kim <rakie.kim@sk.com>
Signed-off-by: Honggyu Kim <honggyu.kim@sk.com>
Co-developed-by: Gregory Price <gregory.price@memverge.com>
Signed-off-by: Gregory Price <gregory.price@memverge.com>
Co-developed-by: Hyeongtak Ji <hyeongtak.ji@sk.com>
Signed-off-by: Hyeongtak Ji <hyeongtak.ji@sk.com>
Reviewed-by: "Huang, Ying" <ying.huang@intel.com>
Cc: Dan Williams <dan.j.williams@intel.com>
Cc: Gregory Price <gourry.memverge@gmail.com>
Cc: Hasan Al Maruf <Hasan.Maruf@amd.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Jonathan Corbet <corbet@lwn.net>
Cc: Michal Hocko <mhocko@kernel.org>
Cc: Srinivasulu Thanneeru <sthanneeru.opensrc@micron.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
2024-02-02 12:02:35 -05:00
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What: /sys/kernel/mm/mempolicy/weighted_interleave/
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Date: January 2024
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Contact: Linux memory management mailing list <linux-mm@kvack.org>
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Description: Configuration Interface for the Weighted Interleave policy
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What: /sys/kernel/mm/mempolicy/weighted_interleave/nodeN
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Date: January 2024
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Contact: Linux memory management mailing list <linux-mm@kvack.org>
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Description: Weight configuration interface for nodeN
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The interleave weight for a memory node (N). These weights are
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utilized by tasks which have set their mempolicy to
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MPOL_WEIGHTED_INTERLEAVE.
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These weights only affect new allocations, and changes at runtime
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will not cause migrations on already allocated pages.
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The minimum weight for a node is always 1.
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Minimum weight: 1
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Maximum weight: 255
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mm/mempolicy: Weighted Interleave Auto-tuning
On machines with multiple memory nodes, interleaving page allocations
across nodes allows for better utilization of each node's bandwidth.
Previous work by Gregory Price [1] introduced weighted interleave, which
allowed for pages to be allocated across nodes according to user-set
ratios.
Ideally, these weights should be proportional to their bandwidth, so that
under bandwidth pressure, each node uses its maximal efficient bandwidth
and prevents latency from increasing exponentially.
Previously, weighted interleave's default weights were just 1s -- which
would be equivalent to the (unweighted) interleave mempolicy, which goes
through the nodes in a round-robin fashion, ignoring bandwidth
information.
This patch has two main goals: First, it makes weighted interleave easier
to use for users who wish to relieve bandwidth pressure when using nodes
with varying bandwidth (CXL). By providing a set of "real" default
weights that just work out of the box, users who might not have the
capability (or wish to) perform experimentation to find the most optimal
weights for their system can still take advantage of bandwidth-informed
weighted interleave.
Second, it allows for weighted interleave to dynamically adjust to
hotplugged memory with new bandwidth information. Instead of manually
updating node weights every time new bandwidth information is reported or
taken off, weighted interleave adjusts and provides a new set of default
weights for weighted interleave to use when there is a change in bandwidth
information.
To meet these goals, this patch introduces an auto-configuration mode for
the interleave weights that provides a reasonable set of default weights,
calculated using bandwidth data reported by the system. In auto mode,
weights are dynamically adjusted based on whatever the current bandwidth
information reports (and responds to hotplug events).
This patch still supports users manually writing weights into the nodeN
sysfs interface by entering into manual mode. When a user enters manual
mode, the system stops dynamically updating any of the node weights, even
during hotplug events that shift the optimal weight distribution.
A new sysfs interface "auto" is introduced, which allows users to switch
between the auto (writing 1 or Y) and manual (writing 0 or N) modes. The
system also automatically enters manual mode when a nodeN interface is
manually written to.
There is one functional change that this patch makes to the existing
weighted_interleave ABI: previously, writing 0 directly to a nodeN
interface was said to reset the weight to the system default. Before this
patch, the default for all weights were 1, which meant that writing 0 and
1 were functionally equivalent. With this patch, writing 0 is invalid.
Link: https://lkml.kernel.org/r/20250520141236.2987309-1-joshua.hahnjy@gmail.com
[joshua.hahnjy@gmail.com: wordsmithing changes, simplification, fixes]
Link: https://lkml.kernel.org/r/20250511025840.2410154-1-joshua.hahnjy@gmail.com
[joshua.hahnjy@gmail.com: remove auto_kobj_attr field from struct sysfs_wi_group]
Link: https://lkml.kernel.org/r/20250512142511.3959833-1-joshua.hahnjy@gmail.com
https://lore.kernel.org/linux-mm/20240202170238.90004-1-gregory.price@memverge.com/ [1]
Link: https://lkml.kernel.org/r/20250505182328.4148265-1-joshua.hahnjy@gmail.com
Co-developed-by: Gregory Price <gourry@gourry.net>
Signed-off-by: Gregory Price <gourry@gourry.net>
Signed-off-by: Joshua Hahn <joshua.hahnjy@gmail.com>
Suggested-by: Yunjeong Mun <yunjeong.mun@sk.com>
Suggested-by: Oscar Salvador <osalvador@suse.de>
Suggested-by: Ying Huang <ying.huang@linux.alibaba.com>
Suggested-by: Harry Yoo <harry.yoo@oracle.com>
Reviewed-by: Harry Yoo <harry.yoo@oracle.com>
Reviewed-by: Huang Ying <ying.huang@linux.alibaba.com>
Reviewed-by: Honggyu Kim <honggyu.kim@sk.com>
Cc: Dan Williams <dan.j.williams@intel.com>
Cc: Dave Jiang <dave.jiang@intel.com>
Cc: Greg Kroah-Hartman <gregkh@linuxfoundation.org>
Cc: Joanthan Cameron <Jonathan.Cameron@huawei.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Len Brown <lenb@kernel.org>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
2025-05-05 11:23:28 -07:00
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Writing invalid values (i.e. any values not in [1,255],
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empty string, ...) will return -EINVAL.
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Changing the weight to a valid value will automatically
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switch the system to manual mode as well.
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What: /sys/kernel/mm/mempolicy/weighted_interleave/auto
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Date: May 2025
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Contact: Linux memory management mailing list <linux-mm@kvack.org>
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Description: Auto-weighting configuration interface
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Configuration mode for weighted interleave. 'true' indicates
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that the system is in auto mode, and a 'false' indicates that
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the system is in manual mode.
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In auto mode, all node weights are re-calculated and overwritten
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(visible via the nodeN interfaces) whenever new bandwidth data
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is made available during either boot or hotplug events.
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In manual mode, node weights can only be updated by the user.
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Note that nodes that are onlined with previously set weights
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will reuse those weights. If they were not previously set or
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are onlined with missing bandwidth data, the weights will use
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a default weight of 1.
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Writing any true value string (e.g. Y or 1) will enable auto
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mode, while writing any false value string (e.g. N or 0) will
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enable manual mode. All other strings are ignored and will
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return -EINVAL.
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Writing a new weight to a node directly via the nodeN interface
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will also automatically switch the system to manual mode.
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