Python implements a simple parallel matrix multiplication

The matrix multiplication method used in this paper is to multiply the rows of a matrix and the columns of two matrices without affecting each other. Suppose a (M,n) represents the M-row, N-column of the Matrix. So C (m,m) =a (m,n) B (n,m):
Calculate C matrix when decomposed into:
Process-1:
C (A) = A (1,:)B (:, 1)

Process-2:
C (from) = A (1,:) * B (:, 2)

..........

Process-m
C (m,m) = A (M,:) * B (:, M)

Realize the source code:
Import multiprocessing #导入多进程模块 for multi-process
Import OS #验证, the ID of the print process
Import NumPy as NP #这个模块是为了实现矩阵乘法

def matrix_muti (i,j):
Print (' current process is {0} '. Format (Os.getpid ())) #打印执行该函数时候的进程
A = [[1, 2], [5, 8]]
B = [[4, 8], [6, 5]]
A = Np.array (a)
b = Np.array (b)
#print (I,J)
Try
Print (sum (a[i,:]*b[:,j]))
Except
Pass

If name = = 'main':
M=1
N=0
Print (' parent process is {0} '. Format (Os.getpid ())) #获取父进程id
For I in range (4):
#控制矩阵的行列数字变化
N=n+1
If n% 3 = = 0:
m = m + 1
n = 1

            #查看下标变化是否正确    print(‘下标变化：‘,m-1,n-1)    p = multiprocessing.Process(target=matrix_muti,args=(m-1,n-1,))   #固定格式，使用4个子进程求矩阵的乘积    p.start()   #开始p.join()

Copy time to run under, found that the code is copied to pycharm the indentation changes, need to manually adjust, or will error

    贴出运行结果如下：

Python implements a simple parallel matrix multiplication