Working With NUMA/CPU Pinning

本文详细介绍了如何通过设置进程亲和性、验证当前线程执行情况、确认NUMA配置和使用numactl命令来优化多核服务器上的应用性能。通过将服务进程分配到特定的NUMA节点,可以显著提高应用运行效率。

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Working With NUMA/CPU Pinning

Sep8th, 201611:06 am| Comments

NUMA

The term CPU pinning / process affinity / NUMA generally boils down to the same idea that In a multi socket system, application best performance can be achieved by allowing application threads to get execute on the CPU core which is as close as to its memory bank. In most of the cases Linux process scheduler is intelligent enough to do this , however if you do this manually by yourself , it’s most likely that you will enjoy luxury of increased application performance. Here are some of my notes describing steps required for process affinity setup

Verify how application (radosgw in my case) threads being executed currently. The 5th column psrwhich represents processor core.

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for i in $(pgrep radosgw); do ps -mo pid,tid,fname,user,psr -p $i;done

NUMA requires the following

  • Multi socket system
  • NUMA feature should be enabled from BIOS or UEFI ( most modern motherboards have this feature enabled by default )

First verify if NUMA configuration is available at OS level by looking for numain /var/log/dmesgor /var/log/messages

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[root@ceph-osd1 ~]# grep -i numa /var/log/dmesg
[    0.000000] NUMA: Initialized distance table, cnt=2
[    0.000000] NUMA: Node 0 [mem 0x00000000-0x7fffffff] + [mem 0x100000000-0x107fffffff] -> [mem 0x00000000-0x107fffffff]
[    0.000000] Enabling automatic NUMA balancing. Configure with numa_balancing= or the kernel.numa_balancing sysctl
[    1.023141] pci_bus 0000:00: on NUMA node 0
[    1.026985] pci_bus 0000:80: on NUMA node 1
[root@ceph-osd1 ~]#

To make use of NUMA node pinning, identify your NUMA zones , using numactlCLI

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[root@ceph-osd1 ~]# yum install -y numactl
[root@ceph-osd1 ~]# numactl --hardware
available: 2 nodes (0-1)
node 0 cpus: 0 1 2 3 4 5 6 7 8 9 20 21 22 23 24 25 26 27 28 29
node 0 size: 65430 MB
node 0 free: 3096 MB
node 1 cpus: 10 11 12 13 14 15 16 17 18 19 30 31 32 33 34 35 36 37 38 39
node 1 size: 65536 MB
node 1 free: 7359 MB
node distances:
node   0   1
  0:  10  21
  1:  21  10
[root@ceph-osd1 ~]#
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[root@ceph-osd1 ~]# lscpu
Architecture:          x86_64
CPU op-mode(s):        32-bit, 64-bit
Byte Order:            Little Endian
CPU(s):                40
On-line CPU(s) list:   0-39
Thread(s) per core:    2
Core(s) per socket:    10
Socket(s):             2
NUMA node(s):          2
Vendor ID:             GenuineIntel
CPU family:            6
Model:                 63
Model name:            Intel(R) Xeon(R) CPU E5-2660 v3 @ 2.60GHz
Stepping:              2
CPU MHz:               2824.656
BogoMIPS:              5193.34
Virtualization:        VT-x
L1d cache:             32K
L1i cache:             32K
L2 cache:              256K
L3 cache:              25600K
NUMA node0 CPU(s):     0-9,20-29
NUMA node1 CPU(s):     10-19,30-39
[root@ceph-osd1 ~]#

These 2 commands should give you enough information about your server’s CPU and NUMA configuration.

In my environment, I have a 2 socket server and each socket has 10 cores , so 2 x 10 = 20 cores. On top of it, system has Hyper Threading support which makes 20 cores to 40 cores. These 40 cores are divided into two numa zones - node0 with CPUs 0-9 and 20-29 - node1 with CPUs 10-19 and 30-39 Verify on what cores your service is entitled to run

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[root@ceph-osd1 ~]# for i in $(pgrep radosgw) ; do taskset -pc $i ; done
pid 3793213's current affinity list: 0-39
[root@ceph-osd1 ~]#

Based on the above output, my application (radosgw) can execute on any core between 0-39. I want to do CPU Affinity with the following configuration - radosgw process from CPU’s 0-39 to CPU’s 10-19,30-39 ( allocating whole socket-2 ) Now its the time to tune your application and instruct it to use a specific CPU or NUMA node. For this we need to modify service configuration of your application and add CPU pinning parameters there.

Edit your applications ( in my case radosgw ) systemctl service configuration files /usr/lib/systemd/system/ceph-radosgw\@.serviceand add the following section to [Service] section of unit file

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CPUAffinity= 10 11 12 13 14 15 16 17 18 19 30 31 32 33 34 35 36 37 38 39

Reload changes

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$ sudo systemctl daemon-reload
$ sudo systemctl restart ceph-radosgw@rgw.$(hostname -s).service
$ sudo systemctl status ceph-radosgw@rgw.$(hostname -s).service -l
● ceph-radosgw@rgw.ceph-osd1.service - Ceph rados gateway
   Loaded: loaded (/usr/lib/systemd/system/ceph-radosgw@.service; enabled; vendor preset: disabled)
   Active: active (running) since Fri 2016-09-02 12:20:02 EEST; 9s ago
 Main PID: 229662 (radosgw)
   CGroup: /system.slice/system-ceph\x2dradosgw.slice/ceph-radosgw@rgw.ceph-osd1.service
           └─229662 /usr/bin/radosgw -f --cluster ceph --name client.rgw.ceph-osd1 --setuser ceph --setgroup ceph

Sep 02 12:20:02 ceph-osd1 systemd[1]: Started Ceph rados gateway.
Sep 02 12:20:02 ceph-osd1 systemd[1]: Starting Ceph rados gateway...

Verify your daemon is getting pinned to the correct CPU cores

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$ sudo for i in $(pgrep radosgw) ; do taskset -pc $i ; done
pid 229662's current affinity list: 10-19,30-39

Another way of doing this or may more easier way is to use numactl command which can bind application to entire NUMA node which includes both CPU and Memory bindings

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$ sudo numactl --cpunodebind=1 --membind=1 radosgw

Image source: stackoverflow.com , Thanks

Hope this is useful for you :)

Posted by Karan SinghSep8th, 201611:06 ambenchmarkingceph

<think>我们正在处理关于NUMA架构下均衡分配CPU和内存的问题。根据用户提供的引用,我们可以总结出以下关键点:1.NUMA架构中,多个CPU节点各自有本地内存,访问远程内存会有延迟[^1]。2.在连接层面,如果没有正确配置NUMA,可能导致资源分配不均衡(如某些节点过忙而其他节点空闲)[^2]。3.解决方案包括使用numactl工具进行内存交错分配(interleave)、调整内核参数以及绑定特定节点等[^3][^4]。用户需求:如何在NUMA架构下均衡分配CPU上的内存使用。回答结构:1.解释NUMA架构的基本概念和均衡分配的重要性。2.介绍配置方法(工具和参数调整)。3.提供具体操作步骤和示例。4.注意事项。同时,根据指令,我们需要生成相关问题。参考引用:[^1]:解释了NUMA架构的基本特点(多个CPU节点,统一内存访问变为非统一)。[^2]:说明了在连接层面配置NUMA的重要性,否则可能导致资源不均衡。[^3]:提供了解决方案:使用numactl进行内存交错分配、调整swappiness参数以及选择合适策略。[^4]:介绍了numactl、taskset和cgroups等工具的区别。具体回答:</think>### NUMA架构下的CPU与内存均衡分配方法 在NUMA(非统一内存访问)架构中,每个CPU节点拥有本地内存模块,访问本地内存速度远快于远程节点内存[^1]。均衡分配的核心目标是减少跨节点访问延迟,避免某些节点过载而其他节点空闲。以下是关键配置方法: #### 一、操作系统级配置 1. **内存交错分配(Interleave)** 使用`numactl`强制进程在所有节点上轮询分配内存: ```bash numactl --interleave=all <应用程序命令> ``` 例如Redis推荐此配置以消除热点内存问题[^3]。 2. **NUMA节点绑定** 将进程绑定到特定CPU节点,同时限制其内存分配范围: ```bash numactl --cpunodebind=0 --membind=0,1 <应用程序> # 绑定到节点0,内存仅使用节点0和1 ``` 3. **调整内核参数** - 降低Swap倾向(减少非必要磁盘交换): ```bash sysctl vm.swappiness=10 ``` - 启用NUMA平衡(自动迁移内存页): ```bash sysctl kernel.numa_balancing=1 ``` #### 二、应用程序级优化 1. **线程绑定(CPU Affinity)** 使用`taskset`将线程固定到特定CPU核心: ```bash taskset -c 0,2,4 <应用程序> # 绑定到核心0,2,4 ``` 2. **NUMA感知的内存分配** 在代码中使用`libnuma`库(如C/C++): ```c #include <numa.h> void* mem = numa_alloc_onnode(size, target_node); ``` #### 三、高级资源管理(适用于容器化环境) 1. **cgroups v2控制** 通过cpuset限制CPU和内存节点: ```bash echo "0-1" > /sys/fs/cgroup/cpuset.cpus echo "0" > /sys/fs/cgroup/cpuset.mems # 限制使用节点0的内存 ``` 2. **动态策略选择工具** - `numad`:后台服务自动优化NUMA资源分配 - `virsh`(虚拟化):为虚拟机配置NUMA策略 ```xml <numatune> <memory mode="strict" nodeset="0-1"/> </numatune> ``` #### 四、验证与监控工具 ```bash numastat -c <进程名> # 查看各节点内存使用比例 numactl -H # 显示NUMA拓扑结构 lscpu --extended # 查看CPU与节点映射关系 ``` > **关键注意事项** > - 数据库类应用(如SQL Server)需在连接层配置NUMA亲和性,避免Round-Robin分配导致负载不均[^2] > - 内存密集型应用优先使用`--interleave=all`,计算密集型应用适合绑定本地节点 > - 虚拟化环境中需同时配置宿主机和Guest OS的NUMA策略 通过上述方法,可显著降低跨节点访问延迟(通常从300+周期降至100周期内),提升吞吐量30%以上[^3][^4]。 --- ### 相关问题 1. 如何检测NUMA架构下的内存访问瓶颈? 2. 在Kubernetes中如何为容器配置NUMA亲和性? 3. NUMA架构与SMP架构在性能优化上有哪些本质区别? 4. 哪些开源数据库原生支持NUMA优化?如何配置? [^1]: 多个CPU之间是平等的,无主从关系;内存访问存在本地与远程差异 [^2]: SQL Server需避免Round-Robin分配导致节点负载不均 [^3]: 内存交叉分配(interleave)是解决热点内存的有效方案 [^4]: numactl与cgroups工具可实现动态资源绑定
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