在我的编译器和mergesort的实现上比较我的quicksort实现和std :: sort时,我注意到大数据集上有一个奇怪的模式:当在64位整数上运行时,quicksort始终比mergesort快; 但是,在较小的int大小上,quicksort变慢,mergesort变得更快.
这是测试代码:
#include <iostream>
#include <vector>
#include <iterator>
#include <algorithm>
#include <utility>
#include <random>
#include <chrono>
#include <limits>
#include <functional>
#include <cstdint>
template <typename Iterator>
void insertion_sort(Iterator first, Iterator last)
{
using namespace std;
Iterator head = first;
Iterator new_position;
while(head != last)
{
new_position = head;
while(new_position != first && *new_position < *prev(new_position))
{
swap(*new_position, *prev(new_position));
--new_position;
}
++head;
}
}
template <typename Iterator>
void recursive_mergesort_impl(Iterator first, Iterator last, std::vector<typename Iterator::value_type>& temp)
{
if(last - first > 32)
{
auto middle = first + (last-first)/2;
recursive_mergesort_impl(first, middle, temp);
recursive_mergesort_impl(middle, last, temp);
auto last_merged = merge_move(first, middle, middle, last, temp.begin());
std::move(temp.begin(), last_merged, first);
}
else
{
insertion_sort(first, last);
}
}
template <typename Iterator>
void recursive_mergesort(Iterator first, Iterator last)
{
std::vector<typename Iterator::value_type> temp(last-first);
recursive_mergesort_impl(first, last, temp);
}
// Pick a pivot and move it to front of range
template <typename Iterator>
template <typename Iterator>
void quicksort_pivot_back(Iterator first, Iterator last)
{
using namespace std;
auto middle = first + (last-first)/2;
auto last_elem = prev(last);
Iterator pivot;
if(*first < *middle)
{
if(*middle < *last_elem)
pivot = middle;
else if(*first < *last_elem)
pivot = last_elem;
else
pivot = first;
}
else if(*first < *last_elem)
pivot = first;
else if(*middle < *last_elem)
pivot = last_elem;
else
pivot = middle;
swap(*last_elem, *pivot);
}
template <typename Iterator, typename Function>
std::pair<Iterator, Iterator> quicksort_partition(Iterator first, Iterator last, Function pivot_select)
{
using namespace std;
pivot_select(first, last);
auto pivot = prev(last);
auto bottom = first;
auto top = pivot;
while(bottom != top)
{
if(*bottom < *pivot) ++bottom;
else swap(*bottom, *--top);
}
swap(*pivot, *top++);
return make_pair(bottom, top);
}
template <typename Iterator>
void quicksort_loop(Iterator first, Iterator last)
{
using namespace std;
while(last - first > 32)
{
auto bounds = quicksort_partition(first, last, quicksort_pivot_back<Iterator>);
quicksort_loop(bounds.second, last);
last = bounds.first;
}
}
template <typename Iterator>
void quicksort(Iterator first, Iterator last)
{
quicksort_loop(first, last);
insertion_sort(first, last);
}
template <typename IntType = uint64_t, typename Duration = std::chrono::microseconds, typename Timer = std::chrono::high_resolution_clock, typename Function, typename Generator>
void run_trial(Function sort_func, Generator gen, std::string name, std::size_t trial_size, std::size_t trial_count)
{
using namespace std;
using namespace chrono;
vector<IntType> data(trial_size);
Duration elapsed(0);
cout << "Sorting with " << name << endl;
for(unsigned int i = 0; i < trial_count; ++i)
{
generate(data.begin(), data.end(), gen);
auto start = Timer::now();
sort_func(data.begin(), data.end());
auto finish = Timer::now();
elapsed += duration_cast<Duration>(finish-start);
}
cout << "Done. Average elapsed time: " << elapsed.count() / trial_count << endl;
cout << "Is correct: " << is_sorted(data.begin(), data.end()) << endl << endl;
}
int main()
{
using namespace std;
using namespace chrono;
using int_type = uint64_t;
const size_t trial_size = 12800000;
const int trial_count = 15;
vector<int_type> data(trial_size);
uniform_int_distribution<int_type> distr;
mt19937_64 rnd;
run_trial<int_type>(recursive_mergesort<vector<int_type>::iterator>, bind(distr, rnd), "recursive mergesort", trial_size, trial_count);
run_trial<int_type>(quicksort<vector<int_type>::iterator>, bind(distr, rnd), "quicksort", trial_size, trial_count);
run_trial<int_type>(sort<vector<int_type>::iterator>, bind(distr, rnd), "std::sort", trial_size, trial_count);
}
以下是来自12个12800000元素的15次试验的时间:
uint64_t:
Sorting with recursive mergesort
Done. Average elapsed time: 1725431
Is correct: 1
Sorting with quicksort
Done. Average elapsed time: 1238070
Is correct: 1
Sorting with std::sort
Done. Average elapsed time: 1131464
Is correct: 1
uint16_t:
Sorting with recursive mergesort
Done. Average elapsed time: 1186467
Is correct: 1
Sorting with quicksort
Done. Average elapsed time: 2368535
Is correct: 1
Sorting with std::sort
Done. Average elapsed time: 888517
Is correct: 1
我有一种感觉,问题与未对齐的内存访问有关,但是这仍然让我想知道为什么其他算法在快速排序减慢时获得加速.