如何测量进程的单独 CPU 核心使用情况?

发布于 2024-09-11 18:02:59 字数 289 浏览 7 评论 0原文

有什么方法可以测量特定进程的CPU使用率吗?

我知道 top 非常适合测量整个系统的 CPU 使用率(按内核),taskset 可以提供有关允许进程在哪个 CPU 核心上运行的信息。

但是如何测量特定进程的 CPU 核心的 CPU 使用率呢?

Is there any way to measure a specific process CPU usage by cores?

I know top is good for measuring the whole system's CPU usage by cores and taskset can provide information about which CPU core is allowed for the process to run on.

But how do I measure a specific process' CPU usage by CPU cores?

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评论(8

如日中天 2024-09-18 18:02:59

您仍然可以在顶部中执行此操作。当 top 运行时,按键盘上的“1”,它将显示每个核心的 CPU 使用情况。

通过在特定用户帐户下运行特定进程来限制显示的进程,并使用类型“u”限制为该用户

You can still do this in top. While top is running, press '1' on your keyboard, it will then show CPU usage per core.

Limit the processes shown by having that specific process run under a specific user account and use Type 'u' to limit to that user

久随 2024-09-18 18:02:59

您可以使用:

 mpstat -P ALL 1

它显示每个核心的繁忙程度,并且每秒自动更新。输出将是这样的(在四核处理器上):

10:54:41 PM  CPU    %usr   %nice    %sys %iowait    %irq   %soft  %steal  %guest   %idle
10:54:42 PM  all    8.20    0.12    0.75    0.00    0.00    0.00    0.00    0.00   90.93
10:54:42 PM    0   24.00    0.00    2.00    0.00    0.00    0.00    0.00    0.00   74.00
10:54:42 PM    1   22.00    0.00    2.00    0.00    0.00    0.00    0.00    0.00   76.00
10:54:42 PM    2    2.02    1.01    0.00    0.00    0.00    0.00    0.00    0.00   96.97
10:54:42 PM    3    2.00    0.00    0.00    0.00    0.00    0.00    0.00    0.00   98.00
10:54:42 PM    4   14.15    0.00    1.89    0.00    0.00    0.00    0.00    0.00   83.96
10:54:42 PM    5    1.00    0.00    0.00    0.00    0.00    0.00    0.00    0.00   99.00
10:54:42 PM    6    0.00    0.00    0.00    0.00    0.00    0.00    0.00    0.00  100.00
10:54:42 PM    7    0.00    0.00    0.00    0.00    0.00    0.00    0.00    0.00  100.00

该命令并没有回答原始问题,即它不显示特定进程的 CPU 核心使用情况。

You can use:

 mpstat -P ALL 1

It shows how much each core is busy and it updates automatically each second. The output would be something like this (on a quad-core processor):

10:54:41 PM  CPU    %usr   %nice    %sys %iowait    %irq   %soft  %steal  %guest   %idle
10:54:42 PM  all    8.20    0.12    0.75    0.00    0.00    0.00    0.00    0.00   90.93
10:54:42 PM    0   24.00    0.00    2.00    0.00    0.00    0.00    0.00    0.00   74.00
10:54:42 PM    1   22.00    0.00    2.00    0.00    0.00    0.00    0.00    0.00   76.00
10:54:42 PM    2    2.02    1.01    0.00    0.00    0.00    0.00    0.00    0.00   96.97
10:54:42 PM    3    2.00    0.00    0.00    0.00    0.00    0.00    0.00    0.00   98.00
10:54:42 PM    4   14.15    0.00    1.89    0.00    0.00    0.00    0.00    0.00   83.96
10:54:42 PM    5    1.00    0.00    0.00    0.00    0.00    0.00    0.00    0.00   99.00
10:54:42 PM    6    0.00    0.00    0.00    0.00    0.00    0.00    0.00    0.00  100.00
10:54:42 PM    7    0.00    0.00    0.00    0.00    0.00    0.00    0.00    0.00  100.00

This command doesn't answer original question though i.e. it does not show CPU core usage for a specific process.

つ可否回来 2024-09-18 18:02:59

您可以使用ps
例如,在双核 CPU 上有两个繁忙线程的 python 进程:

$ ps -p 29492 -L -o pid,tid,psr,pcpu
  PID   TID PSR %CPU
29492 29492   1  0.0
29492 29493   1 48.7
29492 29494   1 51.9

(PSR 是线程当前分配给的 CPU id)

您会看到线程在同一个 cpu 核心上运行(因为 GIL)

,在 jython 中运行相同的 python 脚本,我们看到,该脚本正在利用两个核心(并且还有许多其他服务或任何线程,它们几乎处于空闲状态):

$ ps -p 28671 -L -o pid,tid,psr,pcpu
  PID   TID PSR %CPU
28671 28671   1  0.0
28671 28672   0  4.4
28671 28673   0  0.6
28671 28674   0  0.5
28671 28675   0  2.3
28671 28676   0  0.0
28671 28677   1  0.0
28671 28678   1  0.0
28671 28679   0  4.6
28671 28680   0  4.4
28671 28681   1  0.0
28671 28682   1  0.0
28671 28721   1  0.0
28671 28729   0 88.6
28671 28730   1 88.5

您可以处理输出并计算每个 CPU 核心的总 CPU。

不幸的是,这种方法似乎并不是 100% 可靠,有时我看到在第一种情况下,两个工作线程被报告为分离到每个 CPU 核心,或者在后一种情况下,两个线程被报告为开启同一个核心..

you can use ps.
e.g. having python process with two busy threads on dual core CPU:

$ ps -p 29492 -L -o pid,tid,psr,pcpu
  PID   TID PSR %CPU
29492 29492   1  0.0
29492 29493   1 48.7
29492 29494   1 51.9

(PSR is CPU id the thread is currently assigned to)

you see that the threads are running on the same cpu core (because of GIL)

running the same python script in jython, we see, that the script is utilizing both cores (and there are many other service or whatever threads, which are almost idle):

$ ps -p 28671 -L -o pid,tid,psr,pcpu
  PID   TID PSR %CPU
28671 28671   1  0.0
28671 28672   0  4.4
28671 28673   0  0.6
28671 28674   0  0.5
28671 28675   0  2.3
28671 28676   0  0.0
28671 28677   1  0.0
28671 28678   1  0.0
28671 28679   0  4.6
28671 28680   0  4.4
28671 28681   1  0.0
28671 28682   1  0.0
28671 28721   1  0.0
28671 28729   0 88.6
28671 28730   1 88.5

you can process the output and calculate the total CPU for each CPU core.

Unfortunately, this approach does not seem to be 100% reliable, sometimes i see that in the first case, the two working threads are reported to be separated to each CPU core, or in the latter case, the two threads are reported to be on the same core..

我的影子我的梦 2024-09-18 18:02:59

htop 很好地概述了各个核心的使用情况

htop gives a nice overview of individual core usage

ぇ气 2024-09-18 18:02:59

ps 解决方案几乎是我所需要的,并且添加了一些 bash 完全符合原始问题的要求:查看特定进程的每个核心使用情况

这显示了每个- 多线程进程的核心使用也是如此。

使用如下:
cpustat `pgrep processname` `pgrep otherprocessname` ...

#!/bin/bash

pids=()
while [ $# != 0 ]; do
        pids=("${pids[@]}" "$1")
        shift
done

if [ -z "${pids[0]}" ]; then
        echo "Usage: $0 <pid1> [pid2] ..."
        exit 1
fi

for pid in "${pids[@]}"; do
        if [ ! -e /proc/$pid ]; then
                echo "Error: pid $pid doesn't exist"
                exit 1
        fi
done

while [ true ]; do
        echo -e "\033[H\033[J"
        for pid in "${pids[@]}"; do
                ps -p $pid -L -o pid,tid,psr,pcpu,comm=
        done
        sleep 1
done

注意:这些统计信息基于进程生命周期,而不是最后X秒,因此您需要重新启动进程才能重置计数器。

The ps solution was nearly what I needed and with some bash thrown in does exactly what the original question asked for: to see per-core usage of specific processes

This shows per-core usage of multi-threaded processes too.

Use like:
cpustat `pgrep processname` `pgrep otherprocessname` ...

#!/bin/bash

pids=()
while [ $# != 0 ]; do
        pids=("${pids[@]}" "$1")
        shift
done

if [ -z "${pids[0]}" ]; then
        echo "Usage: $0 <pid1> [pid2] ..."
        exit 1
fi

for pid in "${pids[@]}"; do
        if [ ! -e /proc/$pid ]; then
                echo "Error: pid $pid doesn't exist"
                exit 1
        fi
done

while [ true ]; do
        echo -e "\033[H\033[J"
        for pid in "${pids[@]}"; do
                ps -p $pid -L -o pid,tid,psr,pcpu,comm=
        done
        sleep 1
done

Note: These stats are based on process lifetime, not the last X seconds, so you'll need to restart your process to reset the counter.

飘然心甜 2024-09-18 18:02:59

我认为 perf stat 正是您所需要的。

当您指定 --cpu=list 选项时,它会显示进程的特定用法。以下是使用 perf stat --cpu=0-7 --no-aggr -- make all -j 命令监控构建项目的 cpu 使用情况的示例。输出为:

CPU0         119254.719293 task-clock (msec)         #    1.000 CPUs utilized            (100.00%)
CPU1         119254.724776 task-clock (msec)         #    1.000 CPUs utilized            (100.00%)
CPU2         119254.724179 task-clock (msec)         #    1.000 CPUs utilized            (100.00%)
CPU3         119254.720833 task-clock (msec)         #    1.000 CPUs utilized            (100.00%)
CPU4         119254.714109 task-clock (msec)         #    1.000 CPUs utilized            (100.00%)
CPU5         119254.727721 task-clock (msec)         #    1.000 CPUs utilized            (100.00%)
CPU6         119254.723447 task-clock (msec)         #    1.000 CPUs utilized            (100.00%)
CPU7         119254.722418 task-clock (msec)         #    1.000 CPUs utilized            (100.00%)
CPU0                 8,108 context-switches          #    0.068 K/sec                    (100.00%)
CPU1                26,494 context-switches                                              (100.00%)
CPU2                10,193 context-switches                                              (100.00%)
CPU3                12,298 context-switches                                              (100.00%)
CPU4                16,179 context-switches                                              (100.00%)
CPU5                57,389 context-switches                                              (100.00%)
CPU6                 8,485 context-switches                                              (100.00%)
CPU7                10,845 context-switches                                              (100.00%)
CPU0                   167 cpu-migrations            #    0.001 K/sec                    (100.00%)
CPU1                    80 cpu-migrations                                                (100.00%)
CPU2                   165 cpu-migrations                                                (100.00%)
CPU3                   139 cpu-migrations                                                (100.00%)
CPU4                   136 cpu-migrations                                                (100.00%)
CPU5                   175 cpu-migrations                                                (100.00%)
CPU6                   256 cpu-migrations                                                (100.00%)
CPU7                   195 cpu-migrations                                                (100.00%)

左边一列是具体的CPU索引,最右边一列是CPU的使用情况。如果不指定 --no-aggr 选项,结果将聚合在一起。如果您想监视正在运行的进程,--pid=pid 选项将有所帮助。

也可以尝试 -a --per-core-a perf-socket,这将显示更多机密信息。

有关 perf stat 用法的更多信息,请参阅本教程:perf cpu statistic ,还有 perf help stat 将帮助了解选项的含义。

I thought perf stat is what you need.

It shows a specific usage of a process when you specify a --cpu=list option. Here is an example of monitoring cpu usage of building a project using perf stat --cpu=0-7 --no-aggr -- make all -j command. The output is:

CPU0         119254.719293 task-clock (msec)         #    1.000 CPUs utilized            (100.00%)
CPU1         119254.724776 task-clock (msec)         #    1.000 CPUs utilized            (100.00%)
CPU2         119254.724179 task-clock (msec)         #    1.000 CPUs utilized            (100.00%)
CPU3         119254.720833 task-clock (msec)         #    1.000 CPUs utilized            (100.00%)
CPU4         119254.714109 task-clock (msec)         #    1.000 CPUs utilized            (100.00%)
CPU5         119254.727721 task-clock (msec)         #    1.000 CPUs utilized            (100.00%)
CPU6         119254.723447 task-clock (msec)         #    1.000 CPUs utilized            (100.00%)
CPU7         119254.722418 task-clock (msec)         #    1.000 CPUs utilized            (100.00%)
CPU0                 8,108 context-switches          #    0.068 K/sec                    (100.00%)
CPU1                26,494 context-switches                                              (100.00%)
CPU2                10,193 context-switches                                              (100.00%)
CPU3                12,298 context-switches                                              (100.00%)
CPU4                16,179 context-switches                                              (100.00%)
CPU5                57,389 context-switches                                              (100.00%)
CPU6                 8,485 context-switches                                              (100.00%)
CPU7                10,845 context-switches                                              (100.00%)
CPU0                   167 cpu-migrations            #    0.001 K/sec                    (100.00%)
CPU1                    80 cpu-migrations                                                (100.00%)
CPU2                   165 cpu-migrations                                                (100.00%)
CPU3                   139 cpu-migrations                                                (100.00%)
CPU4                   136 cpu-migrations                                                (100.00%)
CPU5                   175 cpu-migrations                                                (100.00%)
CPU6                   256 cpu-migrations                                                (100.00%)
CPU7                   195 cpu-migrations                                                (100.00%)

The left column is the specific CPU index and the right most column is the usage of the CPU. If you don't specify the --no-aggr option, the result will aggregated together. The --pid=pid option will help if you want to monitor a running process.

Try -a --per-core or -a perf-socket too, which will present more classified information.

More about usage of perf stat can be seen in this tutorial: perf cpu statistic, also perf help stat will help on the meaning of the options.

╭⌒浅淡时光〆 2024-09-18 18:02:59

我刚刚遇到这个问题,我在这里找到了类似的答案。

方法是按照您想要的方式设置top,然后按W(大写W)。
这会将 top 的当前布局保存到 $HOME/.toprc 中的配置文件中,

但如果您想使用不同的配置运行多个 top,这可能不起作用。

因此,通过我认为的解决方法,您可以通过执行以下操作之一写入不同的配置文件/使用不同的配置文件...

1)重命名二进制文件

  ln -s /usr/bin/top top2
  ./top2

现在将写入 .top2rc你的 $HOME

2) 将 $HOME 设置为某个替代路径,因为它会将其配置文件写入 $HOME/.binary-name.rc 文件

HOME=./
top

现在 .toprc 将被写入当前文件夹。

通过使用其他人的评论在顶部添加各种使用情况统计,您可以为该信息创建批处理输出,然后通过脚本合并该信息。也许不像你的脚本那么简单,但我发现 top 为我提供了所有进程,以便稍后我可以在长时间运行期间回顾和捕获我可能会错过的状态(由于杂散进程而导致无法解释的突然 CPU 使用)

I had just this problem and I found a similar answer here.

The method is to set top the way you want it and then press W (capital W).
This saves top's current layout to a configuration file in $HOME/.toprc

Although this might not work if you want to run multiple top's with different configurations.

So via what I consider a work around you can write to different config files / use different config files by doing one of the following...

1) Rename the binary

  ln -s /usr/bin/top top2
  ./top2

Now .top2rc is going to be written to your $HOME

2) Set $HOME to some alternative path, since it will write its config file to the $HOME/.binary-name.rc file

HOME=./
top

Now .toprc is going to be written to the current folder.

Via use of other peoples comments to add the various usage accounting in top you can create a batch output for that information and latter coalesces the information via a script. Maybe not quite as simple as you script but I found top to provide me ALL processes so that later I can recap and capture a state during a long run that I might have missed otherwise (unexplained sudden CPU usage due to stray processes)

星星的軌跡 2024-09-18 18:02:59
dstat -C 0,1,2,3 

还将为您提供前 4 个核心的 CPU 使用情况。当然,如果您有 32 个核心,则此命令会有点长,但如果您只对少数核心感兴趣,则该命令很有用。

例如,如果您只对核心 3 和 7 感兴趣,那么您可以这样做

dstat -C 3,7
dstat -C 0,1,2,3 

Will also give you the CPU usage of first 4 cores. Of course, if you have 32 cores then this command gets a little bit longer but useful if you only interested in few cores.

For example, if you only interested in core 3 and 7 then you could do

dstat -C 3,7
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