用java编写两个n阶的方阵A和B的相乘程序，结果存放在方阵C中，其中使用Runnable接口实现矩阵的乘法。
方阵A和B的初始值如下：（同时开两个线程）
输出：c中所有元素之和、程序的执行时间
具体的程序如下：
package com.xing.matrix;
/**
*
* @author Yinxing
*
*/
public class Matrixmul {
public static void main(String[] args) throws InterruptedException {
// TODO Auto-generated method stub
int i,j,t = 0;
int leng = 1500;
long startTime,endTime;
long a[][] = new long[leng][leng];
long b[][] = new long[leng][leng];
//--------------对矩阵A和矩阵B进行初始化-------------
for(i=0;i<leng;i++)
{
t=i+1;
for(j=0;j<leng;j++)
{
a[i][j]=t++;
b[i][j]=1;
}
}
Matrix matrixone = new Matrix(a, b, 0, leng);
Matrix matrixtwo = new Matrix(a, b, 1, leng);
Thread threadone = new Thread(matrixone);
Thread threadtwo = new Thread(matrixtwo);
//-------------------并行计算--------------------
startTime = System.currentTimeMillis();
threadone.start();
threadtwo.start();
threadone.join();
threadtwo.join();
endTime = System.currentTimeMillis();
System.out.println("并行结果 = " + (matrixone.getSum() + matrixtwo.getSum()));
System.out.println("并行时间 = " + (endTime - startTime));
//-------------------串行计算--------------------
startTime = System.currentTimeMillis();
Matrix matrixthree = new Matrix(a, b, 0, leng);
matrixthree.serial();
endTime = System.currentTimeMillis();
System.out.println("串行结果 = " + matrixthree.getSum());
System.out.println("串行时间 = " + (endTime - startTime));
}
}
class Matrix implements Runnable{
private long A[][];
private long B[][];
private long C[][];
private int start ;
private int end ;
private long sum = 0 ;
public Matrix(long a[][],long b[][],int st,int en){
this.A = a;
this.B = b;
this.start = st;
this.end = en;
this.C = new long[en][en];
}
@Override
public void run() {
// TODO Auto-generated method stub
int i,j,k;
for( i=start; i< end; i += 2)
{
for( j=0;j<end;j++)
{
C [i][j] = 0;
for( k=0; k< end;k++)
{
C[i][j]+=A[i][k]*B[k][j];
}
}
}
for( i=start; i<end; i+=2)
for( j=0; j<end; j++)
sum += C[i][j];
}
public void serial() { //串行计算一个矩阵的乘法然后在求和
int i,j,k;
for( i=0; i< end; i ++)
{
for( j=0;j<end;j++)
{
C[i][j]=0;
for( k=0; k< end;k++)
{
C[i][j]+=A[i][k]*B[k][j];
}
}
}
for( i=0; i<end; i++)
for( j=0; j<end; j++)
sum += C[i][j];
}
public long getSum() {
return this.sum;
}
}
运行结果如下：（其中利用多核并行的部分为乘法和求和）
相对加速比为：58692/32020= 1.832979387882573