算法导论4.2strassen

strassen

// strassen.h
#ifndef STRASSEN_HH
#define STRASSEN_HH

#include <iostream>
#include <iomanip>

template<typename T>
class Strassen_class{
public:
    void ADD(T** MatrixA, T** MatrixB, T** MatrixResult, int MatrixSize );
    void SUB(T** MatrixA, T** MatrixB, T** MatrixResult, int MatrixSize );
    void MUL(T** MatrixA, T** MatrixB, T** MatrixResult, int MatrixSize ); // 朴素算法实现
    void FillMatrix( T** MatrixA, T** MatrixB, int length);                // A,B矩阵赋值
    void PrintMatrix(T **MatrixA,int MatrixSize);                          // 打印矩阵
    void Strassen(int N, T **MatrixA, T **MatrixB, T **MatrixC);           // Strassen算法实现
};

template<typename T>
void Strassen_class<T>::ADD(T** MatrixA, T** MatrixB, T** MatrixResult, int MatrixSize)
{
    for (int i = 0; i < MatrixSize; i++)
    {
        for (int j = 0; j < MatrixSize; j++)
        {
            MatrixResult[i][j] = MatrixA[i][j] + MatrixB[i][j];
        }
    }
}

template<typename T>
void Strassen_class<T>::SUB(T** MatrixA, T** MatrixB, T** MatrixResult, int MatrixSize)
{
    for ( int i = 0; i < MatrixSize; i++)
    {
        for ( int j = 0; j < MatrixSize; j++)
        {
            MatrixResult[i][j] =  MatrixA[i][j] - MatrixB[i][j];
        }
    }
}

template<typename T>
void Strassen_class<T>::MUL(T** MatrixA, T** MatrixB, T** MatrixResult, int MatrixSize)
{
    for (int i = 0; i < MatrixSize; i++)
    {
        for (int j = 0; j < MatrixSize; j++)
        {
            MatrixResult[i][j] = 0;
            for (int k = 0; k < MatrixSize; k++)
            {
                MatrixResult[i][j] = MatrixResult[i][j] + MatrixA[i][k] * MatrixB[k][j];
            }
        }
    }
}

/*
   c++使用二维数组，申请动态内存方法
   申请
   int **A;
   A = new int *[desired_array_row];
   for ( int i = 0; i < desired_array_row; i++)
   A[i] = new int [desired_column_size];

   释放
   for ( int i = 0; i < your_array_row; i++)
   delete [] A[i];
   delete[] A;

 */
template<typename T>
void Strassen_class<T>::Strassen(int N, T** MatrixA, T** MatrixB, T** MatrixC)
{
    int HalfSize = N / 2;
    int newSize  = N / 2;

    if (N <= 64)    //分治门槛，小于这个值时不再进行递归计算，而是采用常规矩阵计算方法
    {
        MUL(MatrixA, MatrixB, MatrixC, N);
    }
    else
    {
        T** A11;
        T** A12;
        T** A21;
        T** A22;

        T** B11;
        T** B12;
        T** B21;
        T** B22;

        T** C11;
        T** C12;
        T** C21;
        T** C22;

        T** M1;
        T** M2;
        T** M3;
        T** M4;
        T** M5;
        T** M6;
        T** M7;
        T** AResult;
        T** BResult;

        // making a 1 diminsional pointer based array.
        A11 = new T*[newSize];
        A12 = new T*[newSize];
        A21 = new T*[newSize];
        A22 = new T*[newSize];

        B11 = new T*[newSize];
        B12 = new T*[newSize];
        B21 = new T*[newSize];
        B22 = new T*[newSize];

        C11 = new T*[newSize];
        C12 = new T*[newSize];
        C21 = new T*[newSize];
        C22 = new T*[newSize];

        M1 = new T*[newSize];
        M2 = new T*[newSize];
        M3 = new T*[newSize];
        M4 = new T*[newSize];
        M5 = new T*[newSize];
        M6 = new T*[newSize];
        M7 = new T*[newSize];

        AResult = new T*[newSize];
        BResult = new T*[newSize];

        int newLength = newSize;

        //making that 1 dimensional pointer based array , a 2D pointer based array
        for ( int i = 0; i < newSize; i++)
        {
            A11[i] = new T[newLength];
            A12[i] = new T[newLength];
            A21[i] = new T[newLength];
            A22[i] = new T[newLength];

            B11[i] = new T[newLength];
            B12[i] = new T[newLength];
            B21[i] = new T[newLength];
            B22[i] = new T[newLength];

            C11[i] = new T[newLength];
            C12[i] = new T[newLength];
            C21[i] = new T[newLength];
            C22[i] = new T[newLength];

            M1[i] = new T[newLength];
            M2[i] = new T[newLength];
            M3[i] = new T[newLength];
            M4[i] = new T[newLength];
            M5[i] = new T[newLength];
            M6[i] = new T[newLength];
            M7[i] = new T[newLength];

            AResult[i] = new T[newLength];
            BResult[i] = new T[newLength];
        }
        // splitting input Matrices, into 4 sub matrices each.
        for (int i = 0; i < N / 2; i++)
        {
            for (int j = 0; j < N / 2; j++)
            {
                A11[i][j] = MatrixA[i][j];
                A12[i][j] = MatrixA[i][j + N / 2];
                A21[i][j] = MatrixA[i + N / 2][j];
                A22[i][j] = MatrixA[i + N / 2][j + N / 2];

                B11[i][j] = MatrixB[i][j];
                B12[i][j] = MatrixB[i][j + N / 2];
                B21[i][j] = MatrixB[i + N / 2][j];
                B22[i][j] = MatrixB[i + N / 2][j + N / 2];

            }
        }

        // here we calculate M1..M7 matrices .
        // M1[][]
        ADD(A11, A22, AResult, HalfSize);
        ADD(B11, B22, BResult, HalfSize);         // p5=(a+d)*(e+h)
        Strassen(HalfSize, AResult, BResult, M1); // now that we need to multiply this , we use the strassen itself .


        //M2[][]
        ADD(A21, A22, AResult, HalfSize);           // M2=(A21+A22)B11   p3=(c+d)*e
        Strassen(HalfSize, AResult, B11, M2);       // Mul(AResult,B11,M2);

        //M3[][]
        SUB(B12, B22, BResult, HalfSize);           // M3=A11(B12-B22)   p1=a*(f-h)
        Strassen(HalfSize, A11, BResult, M3);       // Mul(A11,BResult,M3);

        //M4[][]
        SUB(B21, B11, BResult, HalfSize);           // M4=A22(B21-B11)    p4=d*(g-e)
        Strassen(HalfSize, A22, BResult, M4);       // Mul(A22,BResult,M4);

        //M5[][]
        ADD(A11, A12, AResult, HalfSize);           // M5=(A11+A12)B22   p2=(a+b)*h
        Strassen(HalfSize, AResult, B22, M5);       // Mul(AResult,B22,M5);


        //M6[][]
        SUB(A21, A11, AResult, HalfSize);
        ADD(B11, B12, BResult, HalfSize);            // M6=(A21-A11)(B11+B12)   p7=(c-a)(e+f)
        Strassen(HalfSize, AResult, BResult, M6);    // Mul(AResult,BResult,M6);

        //M7[][]
        SUB(A12, A22, AResult, HalfSize);
        ADD(B21, B22, BResult, HalfSize);            // M7=(A12-A22)(B21+B22)    p6=(b-d)*(g+h)
        Strassen(HalfSize, AResult, BResult, M7);    // Mul(AResult,BResult,M7);

        // C11 = M1 + M4 - M5 + M7;
        ADD(M1, M4, AResult, HalfSize);
        SUB(M7, M5, BResult, HalfSize);
        ADD(AResult, BResult, C11, HalfSize);

        // C12 = M3 + M5;
        ADD(M3, M5, C12, HalfSize);

        // C21 = M2 + M4;
        ADD(M2, M4, C21, HalfSize);

        // C22 = M1 + M3 - M2 + M6;
        ADD(M1, M3, AResult, HalfSize);
        SUB(M6, M2, BResult, HalfSize);
        ADD(AResult, BResult, C22, HalfSize);

        // at this point , we have calculated the c11..c22 matrices, and now we are going to
        // put them together and make a unit matrix which would describe our resulting Matrix.
        // 组合小矩阵到一个大矩阵
        for (int i = 0; i < N / 2 ; i++)
        {
            for (int j = 0 ; j < N / 2 ; j++)
            {
                MatrixC[i][j] = C11[i][j];
                MatrixC[i][j + N / 2] = C12[i][j];
                MatrixC[i + N / 2][j] = C21[i][j];
                MatrixC[i + N / 2][j + N / 2] = C22[i][j];
            }
        }

        // 释放矩阵内存空间
        for (int i = 0; i < newLength; i++)
        {
            delete[] A11[i]; delete[] A12[i]; delete[] A21[i];
            delete[] A22[i];

            delete[] B11[i]; delete[] B12[i];delete[] B21[i];
            delete[] B22[i];
            delete[] C11[i]; delete[] C12[i]; delete[] C21[i];
            delete[] C22[i];
            delete[] M1[i]; delete[] M2[i]; delete[] M3[i]; delete[] M4[i];
            delete[] M5[i]; delete[] M6[i]; delete[] M7[i];
            delete[] AResult[i]; delete[] BResult[i] ;
        }
        delete[] A11; delete[] A12; delete[] A21; delete[] A22;
        delete[] B11; delete[] B12; delete[] B21; delete[] B22;
        delete[] C11; delete[] C12; delete[] C21; delete[] C22;
        delete[] M1; delete[] M2; delete[] M3; delete[] M4; delete[] M5;
        delete[] M6; delete[] M7;
        delete[] AResult;
        delete[] BResult ;
    }//end of else
}

template<typename T>
void Strassen_class<T>::FillMatrix(T** MatrixA, T** MatrixB, int length)
{
    for(int row = 0; row < length; row++)
    {
        for(int column = 0; column < length; column++)
        {
            // MatrixB[row][column] = (MatrixA[row][column] = rand() % 5);
            MatrixB[row][column] = (MatrixA[row][column] = rand() % 2);
            //matrix2[row][column] = rand() % 2;//ba hazfe in khat 50% afzayeshe soorat khahim dasht
        }
    }
}

template<typename T>
void Strassen_class<T>::PrintMatrix(T** MatrixA, int MatrixSize)
{
    std::cout.setf(std::ios::right, std::ios::adjustfield);
    std::cout.fill(‘0‘);
    std::cout << std::endl;
    for(int row = 0; row < MatrixSize; row++)
    {
        for(int column = 0; column < MatrixSize; column++)
        {
            std::cout << std::setw(4) << MatrixA[row][column] << "\t";
            if ((column + 1) % ((MatrixSize)) == 0)
                std::cout << std::endl;
        }
    }
    std::cout << std::endl;
}

#endif

// strassen.cpp
#include <ctime>
#include "strassen.h"

using std::cout;
using std::cin;
using std::endl;

int main()
{
    Strassen_class<int> stra; // 定义Strassen_class类对象
    int MatrixSize = 0;

    int** MatrixA;            // 存放矩阵A
    int** MatrixB;            // 存放矩阵B
    int** MatrixC;            // 存放结果矩阵

    clock_t startTime_For_Normal_Multipilication ;
    clock_t endTime_For_Normal_Multipilication ;

    clock_t startTime_For_Strassen ;
    clock_t endTime_For_Strassen ;
    srand(static_cast<unsigned int>(time(0)));

    cout << "\n请输入矩阵大小(必须是2的幂指数值(例如:32,64,512,..): ";
    cin >> MatrixSize;
    cout << endl;
    int N = MatrixSize; // for readiblity.

    // 申请内存
    MatrixA = new int*[MatrixSize];
    MatrixB = new int*[MatrixSize];
    MatrixC = new int*[MatrixSize];

    for (int i = 0; i < MatrixSize; i++)
    {
        MatrixA[i] = new int[MatrixSize];
        MatrixB[i] = new int[MatrixSize];
        MatrixC[i] = new int[MatrixSize];
    }

    stra.FillMatrix(MatrixA, MatrixB, MatrixSize);  // 矩阵赋值

    //*******************conventional multiplication test
    cout << "朴素矩阵算法开始时钟: " << (startTime_For_Normal_Multipilication = clock());

    stra.MUL(MatrixA, MatrixB, MatrixC, MatrixSize); // 朴素矩阵相乘算法 T(n) = O(n^3)

    cout << "\n朴素矩阵算法结束时钟: " << (endTime_For_Normal_Multipilication = clock());

    cout << "\n矩阵运算结果... \n";
    stra.PrintMatrix(MatrixC, MatrixSize);

    //*******************Strassen multiplication test
    cout << "\nStrassen算法开始时钟: " << (startTime_For_Strassen = clock());

    stra.Strassen(N, MatrixA, MatrixB, MatrixC); // strassen矩阵相乘算法

    cout << "\nStrassen算法结束时钟: " << (endTime_For_Strassen = clock());


    cout << "\n矩阵运算结果... \n";
    stra.PrintMatrix(MatrixC, MatrixSize);

    cout << "矩阵大小 " << MatrixSize;
    cout << "\n朴素矩阵算法: " << (endTime_For_Normal_Multipilication - startTime_For_Normal_Multipilication) << " Clocks.." << (endTime_For_Normal_Multipilication - startTime_For_Normal_Multipilication) / CLOCKS_PER_SEC << " Sec";
    cout << "\nStrassen算法: " << (endTime_For_Strassen - startTime_For_Strassen) << " Clocks.." << (endTime_For_Strassen - startTime_For_Strassen) / CLOCKS_PER_SEC << " Sec\n";

    getchar();
    return 0;

}

strassen

算法导论4.2strassen

原文：http://www.cnblogs.com/sunyongjie1984/p/4271049.html