查看CPU/CACHE的拓扑结构

时间:2021-04-22 03:19:54

转自 http://smilejay.com/2017/12/cpu-cache-topology/

Linux上,CPU和Cache相关的拓扑结构,都可以从sysfs文件系统的目录 /sys/devices/system/cpu/ 来获取详细信息。
在网上,找了对CPU相关拓扑结构的解析的两个脚本,觉得还不错;尽管看起来仍有些粗糙,也暂时去改进了。

一个是来自:https://gist.github.com/stedolan/1089968 ; 它可以打印出每个逻辑CPU属于那儿Socket、哪个core,以及与哪些CPU共享L1/L2/L3的Cache。

 
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#!/bin/bash
 
unshared () {
    grep '^[0-9]\+$' "$1" > /dev/null
}
 
for cpu in $(ls -d /sys/devices/system/cpu/cpu[0-9]* | sort -t u -k 3 -n); do
    echo "${cpu##*/}: [Package #$(cat $cpu/topology/physical_package_id), Core #$(cat $cpu/topology/core_id)]"
    if ! unshared $cpu/topology/core_siblings_list; then
        echo "  same package as $(cat $cpu/topology/core_siblings_list)"
    fi
    if ! unshared $cpu/topology/thread_siblings_list; then
        echo "  same core as    $(cat $cpu/topology/thread_siblings_list)"
    fi
    for cache in $cpu/cache/index*; do
        printf "  %-15s " "L$(cat $cache/level) $(cat $cache/type):"
        echo "$(cat $cache/size) $(cat $cache/ways_of_associativity)-way with $(cat $cache/coherency_line_size) byte lines"
        if ! unshared $cache/shared_cpu_list; then
            printf "  %-15s [%s]\n" "" "shared with $(cat $cache/shared_cpu_list)"
        fi
    done
    echo
done

另一个时候cpu_layout.py脚本,来自dpdk项目,用于展示CPU的拓扑结构(不包括cache的信息):http://dpdk.org/browse/dpdk/tree/usertools/cpu_layout.py

 
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#!/usr/bin/env python
 
#
#   BSD LICENSE  (此处省略过多的License信息)
 
from __future__ import print_function
import sys
try:
    xrange # Python 2
except NameError:
    xrange = range # Python 3
 
sockets = []
cores = []
core_map = {}
base_path = "/sys/devices/system/cpu"
fd = open("{}/kernel_max".format(base_path))
max_cpus = int(fd.read())
fd.close()
for cpu in xrange(max_cpus + 1):
    try:
        fd = open("{}/cpu{}/topology/core_id".format(base_path, cpu))
    except IOError:
        continue
    except:
        break
    core = int(fd.read())
    fd.close()
    fd = open("{}/cpu{}/topology/physical_package_id".format(base_path, cpu))
    socket = int(fd.read())
    fd.close()
    if core not in cores:
        cores.append(core)
    if socket not in sockets:
        sockets.append(socket)
    key = (socket, core)
    if key not in core_map:
        core_map[key] = []
    core_map[key].append(cpu)
 
print(format("=" * (47 + len(base_path))))
print("Core and Socket Information (as reported by '{}')".format(base_path))
print("{}\n".format("=" * (47 + len(base_path))))
print("cores = ", cores)
print("sockets = ", sockets)
print("")
 
max_processor_len = len(str(len(cores) * len(sockets) * 2 - 1))
max_thread_count = len(list(core_map.values())[0])
max_core_map_len = (max_processor_len * max_thread_count)  \
                      + len(", ") * (max_thread_count - 1) \
                      + len('[]') + len('Socket ')
max_core_id_len = len(str(max(cores)))
 
output = " ".ljust(max_core_id_len + len('Core '))
for s in sockets:
    output += " Socket %s" % str(s).ljust(max_core_map_len - len('Socket '))
print(output)
 
output = " ".ljust(max_core_id_len + len('Core '))
for s in sockets:
    output += " --------".ljust(max_core_map_len)
    output += " "
print(output)
 
for c in cores:
    output = "Core %s" % str(c).ljust(max_core_id_len)
    for s in sockets:
        if (s,c) in core_map:
            output += " " + str(core_map[(s, c)]).ljust(max_core_map_len)
        else:
            output += " " * (max_core_map_len + 1)
    print(output)

当NUMA架构下,你可能还需要了解NUMA的分布,包括每个节点上有哪些逻辑处理器、有多少内存等信息,那么使用numactl工具来查看(在CentOS上可以用yum install numactl命令来安装该工具)。

 
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[root@jay-linux ~]$ numactl --hardware
available: 2 nodes (0-1)
node 0 cpus: 0 1 2 3 4 5 6 7 16 17 18 19 20 21 22 23
node 0 size: 64395 MB
node 0 free: 62846 MB
node 1 cpus: 8 9 10 11 12 13 14 15 24 25 26 27 28 29 30 31
node 1 size: 64507 MB
node 1 free: 63676 MB
node distances:
node   0   1
  0:  10  20
  1:  20  10

另外,lscpu 命令也是可以查看很多CPU的信息(包括:架构、逻辑CPU数量、核数、主频、Cache大小、NUMA信息等),该命令在CentOS上是在 util-linux 软件包中。