std::bind vs lambda performance

std::bind vs lambda performance

本文关键字：performance lambda bind std vs      更新时间：2023-10-16

我想为几个函数的执行计时，我给自己写了一个助手:

using namespace std;
template<int N = 1, class Fun, class... Args>
void timeExec(string name, Fun fun, Args... args) {
    auto start = chrono::steady_clock::now();
    for(int i = 0; i < N; ++i) {
        fun(args...);
    }
    auto end = chrono::steady_clock::now();
    auto diff = end - start;
    cout << name << ": "<< chrono::duration<double, milli>(diff).count() << " ms. << endl;
}

我想用这种方式计时成员函数，我必须使用bind或lambda，我想看看哪个对性能的影响更小，所以我这样做了:

const int TIMES = 10000;
timeExec<TIMES>("Bind evaluation", bind(&decltype(result)::eval, &result));
timeExec<1>("Lambda evaluation", [&]() {
    for(int i = 0; i < TIMES; ++i) {
        result.eval();
    }
});

结果如下:

Bind evaluation: 0.355158 ms.
Lambda evaluation: 0.014414 ms.

我不知道内部原理，但我认为lambda不可能比bind好。我能想到的唯一合理的解释是编译器在lambda循环中优化了后续的函数求值。

你怎么解释?

我假设lambda不可能比bind好。

你真是先入为主。

Lambdas被绑定到编译器内部，因此可能会发现额外的优化机会。此外，它们的设计是为了避免效率低下。

然而，这里可能没有发生编译器优化技巧。罪魁祸首可能是绑定的参数bind(&decltype(result)::eval, &result)。您正在传递一个指向成员函数的指针(PTMF)和一个对象。与lambda类型不同，PTMF不会捕获实际调用的函数;它只包含函数签名(参数和返回类型)。慢循环使用间接分支函数调用，因为编译器无法通过常量传播解析函数指针。

如果将成员eval()重命名为operator () ()并去掉bind，则显式对象的行为本质上就像lambda一样，性能差异应该会消失。

我已经测试过了。我的结果表明，Lambda实际上比bind快。

这是代码(请不要看样式):

#include <iostream>
#include <functional>
#include <chrono>
using namespace std;
using namespace chrono;
using namespace placeholders;
typedef void SumDataBlockEventHandler(uint8_t data[], uint16_t len);
class SpeedTest {
    uint32_t sum = 0;
    uint8_t i = 0;
    void SumDataBlock(uint8_t data[], uint16_t len) {
        for (i = 0; i < len; i++) {
            sum += data[i];
        }
    }
public:
    function<SumDataBlockEventHandler> Bind() {
        return bind(&SpeedTest::SumDataBlock, this, _1, _2);
    }
    function<SumDataBlockEventHandler> Lambda() {
        return [this](auto data, auto len)
        {
            SumDataBlock(data, len);
        };
    }
};
int main()
{
    SpeedTest test;
    function<SumDataBlockEventHandler> testF;
    uint8_t data[] = { 0,1,2,3,4,5,6,7 };
#if _DEBUG
    const uint32_t testFcallCount = 1000000;
#else
    const uint32_t testFcallCount = 100000000;
#endif
    uint32_t callsCount, whileCount = 0;
    auto begin = high_resolution_clock::now();
    auto end = begin;
    while (whileCount++ < 10) {
        testF = test.Bind();
        begin = high_resolution_clock::now();
        callsCount = 0;
        while (callsCount++ < testFcallCount)
            testF(data, 8);
        end = high_resolution_clock::now();
        cout << testFcallCount << " calls of binded function: " << duration_cast<nanoseconds>(end - begin).count() << "ns" << endl;
        testF = test.Lambda();
        begin = high_resolution_clock::now();
        callsCount = 0;
        while (callsCount++ < testFcallCount)
            testF(data, 8);
        end = high_resolution_clock::now();
        cout << testFcallCount << " calls of lambda function: " << duration_cast<nanoseconds>(end - begin).count() << "ns" << endl << endl;
    }
    system("pause");
}

控制台结果(优化版本):

100000000 calls of binded function: 1846298524ns
100000000 calls of lambda function: 1048086461ns
100000000 calls of binded function: 1259759880ns
100000000 calls of lambda function: 1032256243ns
100000000 calls of binded function: 1264817832ns
100000000 calls of lambda function: 1039052353ns
100000000 calls of binded function: 1263404007ns
100000000 calls of lambda function: 1031216018ns
100000000 calls of binded function: 1275305794ns
100000000 calls of lambda function: 1041313446ns
100000000 calls of binded function: 1256565304ns
100000000 calls of lambda function: 1031961675ns
100000000 calls of binded function: 1248132135ns
100000000 calls of lambda function: 1033890224ns
100000000 calls of binded function: 1252277130ns
100000000 calls of lambda function: 1042336736ns
100000000 calls of binded function: 1250320869ns
100000000 calls of lambda function: 1046529458ns

我在Visual Studio Enterprise 2015下以完全优化(/Ox)的发布模式和禁用优化的调试模式编译了它。结果证实lambda比我的笔记本电脑(戴尔Inspiron 7537，英特尔酷睿i7-4510U 2.00GHz, 8GB RAM)上的bind更快。

有人能在你的电脑上验证这一点吗?

相关文章：