c++ 在google benchmark中测试一个已经多线程的函数时如何暂停计时器?

vohkndzv  于 2023-10-20  发布在  Go
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GitHub上的文档中有一节是关于多线程基准的,但是,它需要将多线程代码放在基准定义中,并且库本身将使用多线程调用此代码。
我想测试一个在内部创建线程的函数。我只对优化多线程部分感兴趣,所以我想单独对这部分进行基准测试。因此,我想在函数的顺序代码正在运行或内部线程正在创建/销毁时暂停计时器,并进行设置/拆除。

ecr0jaav

ecr0jaav1#

使用线程屏障同步原语等待,直到所有线程都被创建,或者完成设置等。此解决方案使用boost::barrier,但从C++20开始也可以使用std::barrier,或实现自定义屏障。如果自己实现要小心,因为很容易搞砸,但this answer似乎是正确的。
benchmark::State & state传递给你的函数和线程,以便在需要时暂停/取消暂停。

#include <thread>
#include <vector>

#include <benchmark/benchmark.h>
#include <boost/thread/barrier.hpp>

void work() {
    volatile int sum = 0;
    for (int i = 0; i < 100'000'000; i++) {
        sum += i;
    }
}

static void thread_routine(boost::barrier& barrier, benchmark::State& state, int thread_id) {
    // do setup here, if needed
    barrier.wait();  // wait until each thread is created
    if (thread_id == 0) {
        state.ResumeTiming();
    }
    barrier.wait();  // wait until the timer is started before doing the work

    // do some work
    work();

    barrier.wait();  // wait until each thread completes the work
    if (thread_id == 0) {
        state.PauseTiming();
    }
    barrier.wait();  // wait until the timer is stopped before destructing the thread
    // do teardown here, if needed
}

void f(benchmark::State& state) {
    const int num_threads = 1000;
    boost::barrier barrier(num_threads);
    std::vector<std::thread> threads;
    threads.reserve(num_threads);
    for (int i = 0; i < num_threads; i++) {
        threads.emplace_back(thread_routine, std::ref(barrier), std::ref(state), i);
    }
    for (std::thread& thread : threads) {
        thread.join();
    }
}

static void BM_AlreadyMultiThreaded(benchmark::State& state) {
    for (auto _ : state) {
        state.PauseTiming();
        f(state);
        state.ResumeTiming();
    }
}

BENCHMARK(BM_AlreadyMultiThreaded)->Iterations(10)->Unit(benchmark::kMillisecond)->MeasureProcessCPUTime(); // NOLINT(cert-err58-cpp)
BENCHMARK_MAIN();

在我的机器上,这段代码输出(跳过头部):

---------------------------------------------------------------------------------------------
Benchmark                                                   Time             CPU   Iterations
---------------------------------------------------------------------------------------------
BM_AlreadyMultiThreaded/iterations:10/process_time       1604 ms       200309 ms           10

如果我注解掉所有的state.PauseTimer()/state.ResumeTimer(),它会输出:

---------------------------------------------------------------------------------------------
Benchmark                                                   Time             CPU   Iterations
---------------------------------------------------------------------------------------------
BM_AlreadyMultiThreaded/iterations:10/process_time       1680 ms       200102 ms           10

我认为80 ms的真实的时间/ 200 ms的CPU时间差在统计上是显著的,而不是噪声,这支持了这个例子正确工作的假设。

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