如何评估程序的运行时? [英] How to evaluate a program's runtime?

问题描述

我已经开发了一个简单的程序，并希望在实际计算机上评估其运行时性能，例如我的MacBook. 源代码为:

I've developed a simple program and want to evaluate its runtime performance on a real machine, e.g. my MacBook. The source code goes:

#include <stdio.h>
#include <vector>
#include <ctime>

int main () {
    auto beg = std::clock () ;
    for (int i = 0; i < 1e8; ++ i) {

    }
    auto end = std::clock () ;
    printf ("CPU time used: %lf ms\n", 1000.0*(end-beg)/CLOCKS_PER_SEC) ;
}

它使用gcc编译，并且优化标志设置为默认值. 在bash脚本的帮助下，我运行了1000次，并通过MacBook记录了运行时间，如下所示:

It's compiled with gcc and the optimization flag is set to the default. With the help of bash script, I ran it for 1000 times and recorded the runtime by my MacBook, as following:

[130.000000, 136.000000): 0
[136.000000, 142.000000): 1
[142.000000, 148.000000): 234
[148.000000, 154.000000): 116
[154.000000, 160.000000): 138
[160.000000, 166.000000): 318
[166.000000, 172.000000): 139
[172.000000, 178.000000): 40
[178.000000, 184.000000): 11
[184.000000, 190.000000): 3

"[a，b):n"表示同一程序的实际运行时间在a毫秒与b毫秒之间，持续n次.

"[a, b): n" means that the actual runtime of the same program is between a ms and b ms for n times.

很明显，实际运行时变化很大，并且似乎不是正态分布.有人可以告诉我是什么原因造成的，以及如何正确评估运行时间?

It's clear that the real runtime varies greatly and it seems not a normal distribution. Could someone kindly tell me what causes this and how I can evaluate the runtime correctly?

感谢您回答这个问题.

推荐答案

基准化很难！

简短答案:使用 Google基准

长答案: 有很多事情会影响时间安排.

Long answer: There are many things that will interfere with timings.

• 计划(操作系统代替您运行其他事情)
• CPU扩展(操作系统决定通过降低运行速度来节省能源)
• 内存争用(您需要时使用内存的其他方式)
• 总线争用(与您要交谈的设备通话的其他方式)
• 缓存(CPU保留一个值以避免使用内存)
• CPU迁移. (操作系统将您从一个CPU转移到另一个CPU)
• 时钟不准确(只有CPU时钟在任何程度上都是准确的，但是如果您迁移，它们会发生变化)

避免这些影响的唯一方法是禁用CPU扩展，执行缓存刷新"功能(通常在启动前仅触摸大量内存)，高优先级运行以及将自己锁定在单个CPU上.即使如此，您的时间安排仍然很嘈杂，所以最后一件事就是简单地重复很多，并使用平均值.
这就是为什么 google基准之类的工具可能是您最好的选择.

The only way to avoid these effects are to disable CPU scaling, to do "cache-flush" functions (normally just touching a lot of memory before starting), running at high priority, and locking yourself to a single CPU. Even after all that, your timings will still be noisy, so the last thing is simply to repeat a lot, and use the average.
This why tools like google benchmark are probably your best bet.

CPPCon的视频
也可以在线在线在线

video from CPPCon
Also available live online

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