如何在Python中进行并行编程？

Question

solve1(A)
solve2(B)

def solve(Q, G, n):
    i = 0
    tol = 10 ** -4

    while i < 1000:
        inneropt, partition, x = setinner(Q, G, n)
        outeropt = setouter(Q, G, n)

        if (outeropt - inneropt) / (1 + abs(outeropt) + abs(inneropt)) < tol:
            break
            
        node1 = partition[0]
        node2 = partition[1]
    
        G = updateGraph(G, node1, node2)

        if i == 999:
            print "Maximum iteration reaches"
    print inneropt

其中setinner和setouter是两个独立的函数。那就是我想平行的地方...

Answer 1

您可以使用multiprocessing模块。对于这种情况，我可能会使用一个处理池：

from multiprocessing import Pool
pool = Pool()
result1 = pool.apply_async(solve1, [A])    # evaluate "solve1(A)" asynchronously
result2 = pool.apply_async(solve2, [B])    # evaluate "solve2(B)" asynchronously
answer1 = result1.get(timeout=10)
answer2 = result2.get(timeout=10)

这将产生可以为您完成一般工作的流程。因为我们没有传递processes，所以它将为机器上的每个CPU核生成一个进程。每个CPU核可以同时执行一个进程。

如果要将列表映射到单个函数，可以这样做：

args = [A, B]
results = pool.map(solve1, args)