我的问题涉及pthread库并使用多核系统。系统似乎在适当的参数下得到改善，对于小数据大小，最大的改进是大约65000.数据表明，当你增加线程时，它开始减少所需的时间，但随后不久就会增加。当线程数= 1,2,4时，它可能会慢慢增加，有时会增加8，但随后16时间开始逐渐减少。在大型数据中，没有任何改进，并且所有时间都保持相当接近。 如果有人能告诉我某些事情是否迫使我的话题顺序行动或另一个问题会很棒。
继承数据
1395525080 0 num thread: 1 data size: 1024 0 1395525080
1395525080 0 num thread: 2 data size: 1024 0 1395525080
1395525080 0 num thread: 4 data size: 1024 0 1395525080
1395525080 15 num thread: 8 data size: 1024 0 1395525080
1395525080 47 num thread: 16 data size: 1024 0 1395525080
1395525080 31 num thread: 32 data size: 1024 0 1395525080
1395525080 16 num thread: 1 data size: 4096 0 1395525080
1395525080 0 num thread: 2 data size: 4096 0 1395525080
1395525080 0 num thread: 4 data size: 4096 0 1395525080
1395525080 15 num thread: 8 data size: 4096 0 1395525080
1395525080 78 num thread: 16 data size: 4096 0 1395525080
1395525080 31 num thread: 32 data size: 4096 0 1395525080
1395525080 140 num thread: 1 data size: 65536 0 1395525080
1395525081 156 num thread: 2 data size: 65536 0 1395525081
1395525081 109 num thread: 4 data size: 65536 0 1395525081
1395525081 94 num thread: 8 data size: 65536 0 1395525081
1395525081 93 num thread: 16 data size: 65536 0 1395525081
1395525081 187 num thread: 32 data size: 65536 0 1395525082
1395525082 171 num thread: 1 data size: 75536 0 1395525082
1395525082 172 num thread: 2 data size: 75536 0 1395525082
1395525082 141 num thread: 4 data size: 75536 0 1395525083
1395525083 109 num thread: 8 data size: 75536 0 1395525083
1395525083 140 num thread: 16 data size: 75536 0 1395525083
1395525083 234 num thread: 32 data size: 75536 0 1395525084
1395525084 203 num thread: 1 data size: 85536 0 1395525084
1395525084 203 num thread: 2 data size: 85536 0 1395525084
1395525084 172 num thread: 4 data size: 85536 0 1395525085
1395525085 202 num thread: 8 data size: 85536 0 1395525085
1395525085 125 num thread: 16 data size: 85536 0 1395525085
1395525085 187 num thread: 32 data size: 85536 0 1395525086
1395525086 125 num thread: 1 data size: 55536 0 1395525086
1395525086 109 num thread: 2 data size: 55536 0 1395525086
1395525086 141 num thread: 4 data size: 55536 0 1395525086
1395525086 78 num thread: 8 data size: 55536 0 1395525086
1395525087 140 num thread: 16 data size: 55536 0 1395525087
1395525087 156 num thread: 32 data size: 55536 0 1395525087
1395525120 153271 num thread: 1 data size: 70000000 153 1395525274
1395525398 152630 num thread: 2 data size: 70000000 152 1395525551
1395525675 154846 num thread: 4 data size: 70000000 154 1395525830
1395525956 153988 num thread: 8 data size: 70000000 153 1395526110
1395526236 153956 num thread: 16 data size: 70000000 153 1395526390
1395526515 157935 num thread: 32 data size: 70000000 157 1395526673
struct bucket
{
std::vector<int> data;
} ;
void *sort_bucket(void *unsorted_bucket);
int _tmain(int argc, _TCHAR* argv[])
{
int array_N[] = {1024, 4096, 65536,75536,85536,55536, 70000000, 16777216};
int array_number_of_threads[] = {1, 2, 4, 8, 16, 32};
std::vector<int> N;
std::vector<int> number_of_threads;
number_of_threads.assign(array_number_of_threads, array_number_of_threads+6);
N.assign(array_N, array_N+7);
for(int size_index = 0; size_index < N.size(); size_index++)
{
for(int thread_index = 0; thread_index < number_of_threads.size(); thread_index++)
{
std::vector<int> unsorted_data;
std::vector<int> sorted_data;
std::vector<std::thread> thread_array;
std::vector<bucket> buckets;
std::vector<pthread_t> thread;
while(buckets.size() < number_of_threads[thread_index]){ // checks against the number of threads and creates the number of buckets
bucket new_bucket;
pthread_t new_thread;
buckets.push_back(new_bucket);
thread.push_back(new_thread);
}
for(int index = 0; index < N[size_index]; index++) // gathers the data
{
unsorted_data.push_back(rand() % N[size_index]);
}
clock_t t = 0;
t = clock();
time_t start = 0;
time_t end = 0;
time(&start);
std::cout << start << " ";
int difference = N[size_index]/number_of_threads[thread_index];
int placeholder = 0;
for(int index = 0; index < N[size_index]; index++) {//calculates which bucket the data belong in and places the data in that bucket
//std::cout << unsorted_data[index] << " " << difference << " ";
placeholder = unsorted_data[index]/difference;
//std::cout << placeholder << std::endl;
buckets[placeholder].data.push_back(unsorted_data[index]);
}
for(int index = 0; index < number_of_threads[thread_index]; index++){ // sends the data to the threads
//thread_array.push_back(std::thread(sort_bucket ,buckets[index]));
pthread_create(&thread[index],
NULL,
sort_bucket ,
(void*) &buckets[index].data);
}
// bring the data back to the root process
for(int index = 0; index < number_of_threads[thread_index]; index++) {
void *data;
struct bucket *ret_bucket;
pthread_join(thread[index],(void**) &data);
ret_bucket = (struct bucket *) data;
sorted_data.insert(sorted_data.end(), ret_bucket->data.begin(), ret_bucket->data.end());
//sorted_data.assign(ret_bucket->data.begin(), ret_bucket->data.end());
}
/*
for(int index = 0; index < sorted_data.size(); index++)
{
std::cout << sorted_data[index] << " ";
}
*/
t = clock() - t;
std::cout << t << " ";
t = t/CLOCKS_PER_SEC;
std::cout << "num thread: " << number_of_threads[thread_index] << " ";
std::cout << "data size: " << N[size_index] << " ";
std::cout << t << " ";
time(&end);
std::cout << end << std::endl;
sort(unsorted_data.begin(), unsorted_data.end());
for(int index = 0; index < unsorted_data.size(); index++)
{
if(unsorted_data[index] != sorted_data[index])
{
std::cout << "data sorting failed" << std::endl;
}
}
}
}
int placeholder;
std::cin >> placeholder;
return 0;
}
void *sort_bucket(void *unsorted_bucket)
{
bucket *temp_sorted_bucket = (struct bucket *) unsorted_bucket;
std::sort(temp_sorted_bucket->data.begin(), temp_sorted_bucket->data.end());
/*for(int index = 0; index < temp_sorted_bucket->data.size(); index++)
{
std::cout << temp_sorted_bucket->data.at(index) << " ";
}*/
pthread_exit(temp_sorted_bucket);
return 0;
}
答案 0 :(得分：0)
请记住，您的线程受CPU上物理内核数量的限制。一旦达到限制，它必须使用资源在同一核心上的线程之间切换，这需要时间。例如，i3处理器有2个具有超线程的物理内核，可在CPU上提供4个虚拟内核，因此任何超过4个线程的内容通常都不会带来任何好处。