私はスレッドプログラミングが初めてで、概念的な問題があります。クラスのプロジェクトとして行列乗算を行っています。ただし、スレッドを使用せずに実行し、スレッドを使用して回答行列の各セルのスカラー積を計算し、最初の行列を比率に分割して、各スレッドが計算する部分が等しくなるようにします。私の問題は、スカラー積の実装が非常に迅速に終了することです。これは私が期待することですが、3 番目の実装では、スレッド化されていない実装よりもはるかに高速に答えが計算されません。たとえば、2 つのスレッドを使用する場合、行列の両方の半分を同時に処理できるため、約半分の時間で計算されますが、まったくそうではありません。3 番目の実装に問題があるように感じますが、そうではありません。並列に動作するとは思わないので、コードを以下に示します。誰かがこれについて私をまっすぐに設定できますか? すべてのコードが質問に関連しているわけではありませんが、問題がローカルではない場合に備えて含めました。ありがとう、
主なプログラム:
#include <iostream>
#include <cstdio>
#include <cstdlib>
#include <cmath>
#include<fstream>
#include<string>
#include<sstream>
#include <matrix.h>
#include <timer.h>
#include <random_generator2.h>
const float averager=2.0; //used to find the average of the time taken to multiply the matrices.
//Precondition: The matrix has been manipulated in some way and is ready to output the statistics
//Outputs the size of the matrix along with the user elapsed time.
//Postconidition: The stats are outputted to the file that is specified with the number of threads used
//file name example: "Nonparrallel2.dat"
void output(string file, int numThreads , long double time, int n);
//argv[1] = the size of the matrix
//argv[2] = the number of threads to be used.
//argv[3] =
int main(int argc, char* argv[])
{
random_generator rg;
timer t, nonparallel, scalar, variant;
int n, total = 0, numThreads = 0;
long double totalNonP = 0, totalScalar = 0, totalVar = 0;
n = 100;
/*
* check arguments
*/
n = atoi(argv[1]);
n = (n < 1) ? 1 : n;
numThreads = atoi(argv[2]);
/*
* allocated and generate random strings
*/
int** C;
int** A;
int** B;
cout << "**NOW STARTING ANALYSIS FOR " << n << " X " << n << " MATRICES WITH " << numThreads << "!**"<< endl;
for (int timesThrough = 0; timesThrough < averager; timesThrough++)
{
cout << "Creating the matrices." << endl;
t.start();
C = create_matrix(n);
A = create_random_matrix(n, rg);
B = create_random_matrix(n, rg);
t.stop();
cout << "Timer (generate): " << t << endl;
//---------------------------------------------------------Ends non parallel-----------------------------
/*
* run algorithms
*/
cout << "Running non-parallel matrix multiplication: " << endl;
nonparallel.start();
multiply(C, A, B, n);
nonparallel.stop();
//-----------------------------------------Ends non parallel----------------------------------------------
//cout << "The correct matrix" <<endl;
//output_matrix(C, n);
cout << "Timer (multiplication): " << nonparallel << endl;
totalNonP += nonparallel.user();
//D is the transpose of B so that the p_scalarproduct function does not have to be rewritten
int** D = create_matrix(n);
for (int i = 0; i < n; i++)
for(int j = 0; j < n; j++)
D[i][j] = B[j][i];
//---------------------------------------------------Start Threaded Scalar Poduct--------------------------
cout << "Running scalar product in parallel" << endl;
scalar.start();
//Does the scalar product in parallel to multiply the two matrices.
for (int i = 0; i < n; i++)
for (int j = 0; j < n; j++){
C[i][j] = 0;
C[i][j] = p_scalarproduct(A[i],D[j],n,numThreads);
}//ends the for loop with j
scalar.stop();
cout << "Timer (scalar product in parallel): " << scalar << endl;
totalScalar += scalar.user();
//---------------------------------------------------Ends Threaded Scalar Poduct------------------------
//---------------------------------------------------Starts Threaded Variant For Loop---------------
cout << "Running the variation on the for loop." << endl;
boost :: thread** thrds;
//create threads and bind to p_variantforloop_t
thrds = new boost::thread*[numThreads];
variant.start();
for (int i = 1; i <= numThreads; i++)
thrds[i-1] = new boost::thread(boost::bind(&p_variantforloop_t,
C, A, B, ((i)*n - n)/numThreads ,(i * n)/numThreads, numThreads, n));
cout << "before join" <<endl;
// join threads
for (int i = 0; i < numThreads; i++)
thrds[i]->join();
variant.stop();
// cleanup
for (int i = 0; i < numThreads; i++)
delete thrds[i];
delete[] thrds;
cout << "Timer (variation of for loop): " << variant <<endl;
totalVar += variant.user();
//---------------------------------------------------Ends Threaded Variant For Loop------------------------
// output_matrix(A, n);
// output_matrix(B, n);
// output_matrix(E,n);
/*
* free allocated storage
*/
cout << "Deleting Storage" <<endl;
delete_matrix(A, n);
delete_matrix(B, n);
delete_matrix(C, n);
delete_matrix(D, n);
//avoids dangling pointers
A = NULL;
B = NULL;
C = NULL;
D = NULL;
}//ends the timesThrough for loop
//output the results to .dat files
output("Nonparallel", numThreads, (totalNonP / averager) , n);
output("Scalar", numThreads, (totalScalar / averager), n);
output("Variant", numThreads, (totalVar / averager), n);
cout << "Nonparallel = " << (totalNonP / averager) << endl;
cout << "Scalar = " << (totalScalar / averager) << endl;
cout << "Variant = " << (totalVar / averager) << endl;
return 0;
}
void output(string file, int numThreads , long double time, int n)
{
ofstream dataFile;
stringstream ss;
ss << numThreads;
file += ss.str();
file += ".dat";
dataFile.open(file.c_str(), ios::app);
if(dataFile.fail())
{
cout << "The output file didn't open." << endl;
exit(1);
}//ends the if statement.
dataFile << n << " " << time << endl;
dataFile.close();
}//ends optimalOutput function
マトリックス ファイル:
#include <matrix.h>
#include <stdlib.h>
using namespace std;
int** create_matrix(int n)
{
int** matrix;
if (n < 1)
return 0;
matrix = new int*[n];
for (int i = 0; i < n; i++)
matrix[i] = new int[n];
return matrix;
}
int** create_random_matrix(int n, random_generator& rg)
{
int** matrix;
if (n < 1)
return 0;
matrix = new int*[n];
for (int i = 0; i < n; i++)
{
matrix[i] = new int[n];
for (int j = 0; j < n; j++)
//rg >> matrix[i][j];
matrix[i][j] = rand() % 100;
}
return matrix;
}
void delete_matrix(int** matrix, int n)
{
for (int i = 0; i < n; i++)
delete[] matrix[i];
delete[] matrix;
//avoids dangling pointers.
matrix = NULL;
}
/*
* non-parallel matrix multiplication
*/
void multiply(int** C, int** A, int** B, int n)
{
if ((C == A) || (C == B))
{
cout << "ERROR: C equals A or B!" << endl;
return;
}
for (int i = 0; i < n; i++)
for (int j = 0; j < n; j++)
{
C[i][j] = 0;
for (int k = 0; k < n; k++)
C[i][j] += A[i][k] * B[k][j];
}
}
void p_scalarproduct_t(int* c, int* a, int* b,
int s, int e, boost::mutex* lock)
{
int tmp;
tmp = 0;
for (int k = s; k < e; k++){
tmp += a[k] * b[k];
//cout << "a[k]= "<<a[k]<<"b[k]= "<< b[k] <<" "<<k<<endl;
}
lock->lock();
*c = *c + tmp;
lock->unlock();
}
int p_scalarproduct(int* a, int* b, int n, int m)
{
int c;
boost::mutex lock;
boost::thread** thrds;
c = 0;
/* create threads and bind to p_merge_sort_t */
thrds = new boost::thread*[m];
for (int i = 0; i < m; i++)
thrds[i] = new boost::thread(boost::bind(&p_scalarproduct_t,
&c, a, b, i*n/m, (i+1)*n/m, &lock));
/* join threads */
for (int i = 0; i < m; i++)
thrds[i]->join();
/* cleanup */
for (int i = 0; i < m; i++)
delete thrds[i];
delete[] thrds;
return c;
}
void output_matrix(int** matrix, int n)
{
cout << "[";
for (int i = 0; i < n; i++)
{
cout << "[ ";
for (int j = 0; j < n; j++)
cout << matrix[i][j] << " ";
cout << "]" << endl;
}
cout << "]" << endl;
}
void p_variantforloop_t(int** C, int** A, int** B, int s, int e, int numThreads, int n)
{
//cout << "s= " <<s<<endl<< "e= " << e << endl;
for(int i = s; i < e; i++)
for(int j = 0; j < n; j++){
C[i][j] = 0;
//cout << "i " << i << " j " << j << endl;
for (int k = 0; k < n; k++){
C[i][j] += A[i][k] * B[k][j];}
}
}//ends the function