[英]What is the key to implement multi thread sorting algorithm efficient? The naive implementations doesn't work properly
我的第一个版本两线程选择排序为每次迭代启动一个新线程。
一些比较(左-一个线程,右-两个线程版本,时间-ms):
Size: 500 time 1 time 5
Size: 1000 time 1 time 9
Size: 1500 time 4 time 12
Size: 2000 time 5 time 16
Size: 2500 time 10 time 22
Size: 3000 time 14 time 26
Size: 3500 time 19 time 30
Size: 4000 time 24 time 36
Size: 4500 time 30 time 43
Size: 5000 time 37 time 49
Size: 5500 time 46 time 57
Size: 6000 time 55 time 66
Size: 6500 time 63 time 76
Size: 7000 time 74 time 80
Size: 7500 time 85 time 92
Size: 8000 time 96 time 102
Size: 8500 time 108 time 109
Size: 9000 time 122 time 124
Size: 9500 time 135 time 132
Size: 10000 time 150 time 144
Size: 10500 time 165 time 156
Size: 11000 time 181 time 174
Size: 11500 time 200 time 177
Size: 12000 time 218 time 195
Size: 12500 time 235 time 205
Size: 13000 time 255 time 214
Size: 13500 time 273 time 226
Size: 14000 time 296 time 245
在9500大小的数组之后,两个线程的工作速度更快。 在我的第二个实现中,线程启动一次。 但是它具有如此令人难以置信的性能。
我的cpu有4个核心。
Size: 0 time 0 time 0
Size: 50 time 0 time 151
Size: 100 time 0 time 1276
Size: 150 time 0 time 2089
Size: 200 time 0 time 3925
Size: 250 time 0 time 5303
码:
//one thread
template<class ItType>
void selectionSortThreadsHelper2(ItType beg, ItType end)
{
//sorting element by element
for (auto it = beg; it != end; ++it) {
ItType middleIt = it + std::distance(it, end) / 2;
auto search = [&] { return std::min_element(it, middleIt); };
//search
std::future<ItType> minFirstHalfResult(std::async(std::launch::async , search));
//wait searching
ItType minSecondHalfIt = std::min_element(middleIt, end);
ItType minFirstHalfIt = minFirstHalfResult.get();
//swap if
ItType minIt = *minFirstHalfIt < *minSecondHalfIt ? minFirstHalfIt : minSecondHalfIt;
if (minIt != it)
std::iter_swap(minIt, it);
}
}
//two thread
template<class ItType>
void selectionSortThreadsHelper3(ItType beg, ItType end)
{
bool quit = false;
bool readyFlag = false;
bool processed = false;
std::mutex readyMutex;
std::condition_variable readyCondVar;
ItType it;
ItType middleIt;
ItType minFirstHalfIt;
auto search = [&]() {
while (true) {
std::unique_lock<std::mutex> ul(readyMutex);
readyCondVar.wait(ul, [&] {return readyFlag; });
if (quit)
return;
minFirstHalfIt = std::min_element(it, middleIt);
processed = true;
ul.unlock();
readyCondVar.notify_one();
}
};
std::future<void> f(std::async(std::launch::async, search));
//sorting element by element
for (it = beg; it != end; ++it) {
middleIt = it + std::distance(it, end) / 2;
//say second thread to start searching
{
std::lock_guard<std::mutex> lg(readyMutex);
readyFlag = true;
}
readyCondVar.notify_one();
//std::this_thread::yield();
ItType minSecondHalfIt = std::min_element(middleIt, end);
//wait second thread
{
std::unique_lock<std::mutex> ul(readyMutex);
readyCondVar.wait(ul, [&] { return processed; });
processed = false;
readyFlag = false;
}
readyCondVar.notify_all();
//swap if
ItType minIt = *minFirstHalfIt < *minSecondHalfIt ? minFirstHalfIt : minSecondHalfIt;
if (minIt != it)
std::iter_swap(minIt, it);
}
//quit thread
{
std::lock_guard<std::mutex> lg(readyMutex);
readyFlag = true;
quit = true;
}
readyCondVar.notify_all();
f.get();
}
有很多方法可以不用编写自己的代码就可以进行并行排序。 首先,有一个实验性的并行性命名空间,可以让您说sort(par, data.begin(), data.end())
: http : sort(par, data.begin(), data.end())
该名称空间已被合并为C ++ 17中的标准,因此在某些时候它应该位于std::
名称空间中( https://parallelstl.codeplex.com/ )。 还有一个基于OpenMP的较旧的非标准GNU g ++并行排序实现: https : //gcc.gnu.org/onlinedocs/libstdc++/manual/parallel_mode.html
最后,在线上有很多页面描述如何在C ++ 11中编写自己的并行排序。 尝试搜索。 这是一个非常全面的页面: https : //software.intel.com/zh-cn/articles/a-parallel-stable-sort-using-c11-for-tbb-cilk-plus-and-openmp
使用Windows线程接口的示例多线程自底向上合并排序,在这种情况下,4个线程用于具有4个(或更多)内核的处理器。 根据数组的大小,它的速度大约是单线程合并排序的3倍,这主要是由于每个内核的本地L1和L2缓存中发生的操作所致。 信号量用于同时启动所有线程以进行基准测试。 在我的系统(Intel 2600K 3.4ghz)上,排序1600万个32位整数大约需要0.5秒,而单线程合并排序大约需要1.5秒。
#include <cstdlib>
#include <ctime>
#include <iostream>
#include <windows.h>
#define SIZE (16*1024*1024) // must be multiple of 4
static HANDLE hs0; // semaphore handles
static HANDLE hs1;
static HANDLE hs2;
static HANDLE hs3;
static HANDLE ht1; // thread handles
static HANDLE ht2;
static HANDLE ht3;
static DWORD WINAPI Thread0(LPVOID); // thread functions
static DWORD WINAPI Thread1(LPVOID);
static DWORD WINAPI Thread2(LPVOID);
static DWORD WINAPI Thread3(LPVOID);
static int *pa; // pointers to buffers
static int *pb;
void BottomUpMergeSort(int a[], int b[], size_t n);
void BottomUpMerge(int a[], int b[], size_t ll, size_t rr, size_t ee);
void BottomUpCopy(int a[], int b[], size_t ll, size_t rr);
size_t GetPassCount(size_t n);
int main()
{
int *array = new int[SIZE];
int *buffer = new int[SIZE];
clock_t ctTimeStart; // clock values
clock_t ctTimeStop;
pa = array;
pb = buffer;
for(int i = 0; i < SIZE; i++){ // generate pseudo random data
int r;
r = (((int)((rand()>>4) & 0xff))<< 0);
r += (((int)((rand()>>4) & 0xff))<< 8);
r += (((int)((rand()>>4) & 0xff))<<16);
r += (((int)((rand()>>4) & 0x7f))<<24);
array[i] = r;
}
hs0 = CreateSemaphore(NULL,0,1,NULL);
hs1 = CreateSemaphore(NULL,0,1,NULL);
hs2 = CreateSemaphore(NULL,0,1,NULL);
hs3 = CreateSemaphore(NULL,0,1,NULL);
ht1 = CreateThread(NULL, 0, Thread1, 0, 0, 0);
ht2 = CreateThread(NULL, 0, Thread2, 0, 0, 0);
ht3 = CreateThread(NULL, 0, Thread3, 0, 0, 0);
ctTimeStart = clock();
ReleaseSemaphore(hs0, 1, NULL); // start sorts
ReleaseSemaphore(hs1, 1, NULL);
ReleaseSemaphore(hs2, 1, NULL);
ReleaseSemaphore(hs3, 1, NULL);
Thread0((LPVOID)NULL);
WaitForSingleObject(ht2, INFINITE);
// merge 1st and 2nd halves
BottomUpMerge(pb, pa, 0, SIZE>>1, SIZE);
ctTimeStop = clock();
std::cout << "Number of ticks " << (ctTimeStop - ctTimeStart) << std::endl;
for(int i = 1; i < SIZE; i++){ // check result
if(array[i-1] > array[i]){
std::cout << "failed" << std::endl;
}
}
CloseHandle(ht3);
CloseHandle(ht2);
CloseHandle(ht1);
CloseHandle(hs3);
CloseHandle(hs2);
CloseHandle(hs1);
CloseHandle(hs0);
delete[] buffer;
delete[] array;
return 0;
}
static DWORD WINAPI Thread0(LPVOID lpvoid)
{
WaitForSingleObject(hs0, INFINITE); // wait for semaphore
// sort 1st quarter
BottomUpMergeSort(pa + 0*(SIZE>>2), pb + 0*(SIZE>>2), SIZE>>2);
WaitForSingleObject(ht1, INFINITE); // wait for thead 1
// merge 1st and 2nd quarter
BottomUpMerge(pa + 0*(SIZE>>1), pb + 0*(SIZE>>1), 0, SIZE>>2, SIZE>>1);
return 0;
}
static DWORD WINAPI Thread1(LPVOID lpvoid)
{
WaitForSingleObject(hs1, INFINITE); // wait for semaphore
// sort 2nd quarter
BottomUpMergeSort(pa + 1*(SIZE>>2), pb + 1*(SIZE>>2), SIZE>>2);
return 0;
}
static DWORD WINAPI Thread2(LPVOID lpvoid)
{
WaitForSingleObject(hs2, INFINITE); // wait for semaphore
// sort 3rd quarter
BottomUpMergeSort(pa + 2*(SIZE>>2), pb + 2*(SIZE>>2), SIZE>>2);
WaitForSingleObject(ht3, INFINITE); // wait for thread 3
// merge 3rd and 4th quarter
BottomUpMerge(pa + 1*(SIZE>>1), pb + 1*(SIZE>>1), 0, SIZE>>2, SIZE>>1);
return 0;
}
static DWORD WINAPI Thread3(LPVOID lpvoid)
{
WaitForSingleObject(hs3, INFINITE); // wait for semaphore
// sort 4th quarter
BottomUpMergeSort(pa + 3*(SIZE>>2), pb + 3*(SIZE>>2), SIZE>>2);
return 0;
}
void BottomUpMergeSort(int a[], int b[], size_t n)
{
size_t s = 1; // run size
if(GetPassCount(n) & 1){ // if odd number of passes
for(s = 1; s < n; s += 2) // swap in place for 1st pass
if(a[s] < a[s-1])
std::swap(a[s], a[s-1]);
s = 2;
}
while(s < n){ // while not done
size_t ee = 0; // reset end index
while(ee < n){ // merge pairs of runs
size_t ll = ee; // ll = start of left run
size_t rr = ll+s; // rr = start of right run
if(rr >= n){ // if only left run
rr = n;
BottomUpCopy(a, b, ll, rr); // copy left run
break; // end of pass
}
ee = rr+s; // ee = end of right run
if(ee > n)
ee = n;
BottomUpMerge(a, b, ll, rr, ee);
}
std::swap(a, b); // swap a and b
s <<= 1; // double the run size
}
}
void BottomUpMerge(int a[], int b[], size_t ll, size_t rr, size_t ee)
{
size_t o = ll; // b[] index
size_t l = ll; // a[] left index
size_t r = rr; // a[] right index
while(1){ // merge data
if(a[l] <= a[r]){ // if a[l] <= a[r]
b[o++] = a[l++]; // copy a[l]
if(l < rr) // if not end of left run
continue; // continue (back to while)
do // else copy rest of right run
b[o++] = a[r++];
while(r < ee);
break; // and return
} else { // else a[l] > a[r]
b[o++] = a[r++]; // copy a[r]
if(r < ee) // if not end of right run
continue; // continue (back to while)
do // else copy rest of left run
b[o++] = a[l++];
while(l < rr);
break; // and return
}
}
}
void BottomUpCopy(int a[], int b[], size_t ll, size_t rr)
{
do // copy left run
b[ll] = a[ll];
while(++ll < rr);
}
size_t GetPassCount(size_t n) // return # passes
{
size_t i = 0;
for(size_t s = 1; s < n; s <<= 1)
i += 1;
return(i);
}
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