我已经分析了c ++ vector和c-style数组之间的性能。结果有点出乎意料,因为文献说矢量的性能应该非常接近原始阵列,但事实并非如此。我在剖析中做错了什么?
void getVector1(int n)
{
if (n < 0)
{
throw std::invalid_argument(std::string("negative argument n:") + std::to_string(n));
}
auto tp1 = std::chrono::steady_clock::now();
std::vector<int> ivec(n);
int i = 0;
for (auto& x : ivec)
{
x = ++i;
}
auto tp2 = std::chrono::steady_clock::now();
std::chrono::duration<double, std::micro> dd = tp2 - tp1;
printf("spend %6.2f us time to create: %d elements vector inside %s() at %s:%d \n", dd.count(), n, __func__, __FILE__, __LINE__);
}
void getVector2(int n)
{
if (n < 0)
{
throw std::invalid_argument(std::string("negative argument n:") + std::to_string(n));
}
auto tp1 = std::chrono::steady_clock::now();
auto pvec = new int[n];
for (int i = 0; i < n; ++i)
{
pvec[i] = i;
}
auto tp2 = std::chrono::steady_clock::now();
std::chrono::duration<double, std::micro> dd = tp2 - tp1;
delete[] pvec;
printf("spend %6.2f us time to create: %d elements vector inside %s() at %s:%d \n", dd.count(), n, __func__, __FILE__, __LINE__);
}
int main()
{
int n = 10000000;
getVector1(n);
getVector2(n);
return 0;
}
使用带有-O3选项的g ++编译代码。
花费11946.38我们的时间在testVectorSpeed.cpp上创建:getVector1()内的10000000个元素向量
花7298.66美元来创建:testVectorSpeed.cpp中getVector2()内的10000000个元素向量
答案 0 :(得分:8)
此成本归结为通过其分配器将内存向量归零。
首先,使用像google benchmark这样的基准测试库而不是滚动自己的基准测试总是一个好主意。我们可以使用quick-bench.com来快速使用该库。重写您的代码以使用它:
// Just the benchmark code:
void getVector1(benchmark::State& state)
{
int n = state.range(0);
for (auto _ : state) {
std::vector<int> ivec(n);
// This is the same operation that you are doing
std::iota(ivec.begin(), ivec.end(), 1);
// We don't want the compiler to see that we aren't
// using `ivec` and thus optimize away the entire
// loop body
benchmark::DoNotOptimize(ivec);
}
}
void getArray1(benchmark::State& state)
{
int n = state.range(0);
for (auto _ : state) {
auto pvec = new int[n];
std::iota(pvec, pvec + n, 1);
benchmark::DoNotOptimize(pvec);
delete[] pvec;
}
}
// Smaller number still reproduces it
BENCHMARK(getVector1)->Arg(10000);
BENCHMARK(getArray1)->Arg(10000);
Click on image for quick-bench link
通过一点点游戏,我们可以发现成本差异只是用std::uninitialized_fill
(on quick-bench)将内存归零的成本。
事实上,如果我们改为使用an allocator that leaves the memory uninitialized,两者之间就没有可衡量的差异:
// Allocator from https://stackoverflow.com/a/41049640
template <typename T, typename A = std::allocator<T>>
class default_init_allocator : public A {
typedef std::allocator_traits<A> a_t;
public:
// http://en.cppreference.com/w/cpp/language/using_declaration
using A::A; // Inherit constructors from A
template <typename U> struct rebind {
using other =
default_init_allocator
< U, typename a_t::template rebind_alloc<U> >;
};
template <typename U>
void construct(U* ptr)
noexcept(std::is_nothrow_default_constructible<U>::value) {
::new(static_cast<void*>(ptr)) U;
}
template <typename U, typename...Args>
void construct(U* ptr, Args&&... args) {
a_t::construct(static_cast<A&>(*this),
ptr, std::forward<Args>(args)...);
}
};
void getVector1(benchmark::State& state)
{
int n = state.range(0);
for (auto _ : state) {
std::vector<int, default_init_allocator<int>> ivec(n);
std::iota(ivec.begin(), ivec.end(), 1);
benchmark::DoNotOptimize(ivec);
}
}
void getArray1(benchmark::State& state)
{
int n = state.range(0);
for (auto _ : state) {
auto pvec = new int[n];
std::iota(pvec, pvec + n, 1);
benchmark::DoNotOptimize(pvec);
delete[] pvec;
}
}
BENCHMARK(getVector1)->Arg(10000);
BENCHMARK(getArray1)->Arg(10000);