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我正在使用 mpi4py 将处理任务分布在一组内核上。我的代码如下所示：

comm = MPI.COMM_WORLD
size = comm.Get_size()
rank = comm.Get_rank()

'''Perform processing operations with each processor returning 
   two arrays of equal size, array1 and array2'''

all_data1 = comm.gather(array1, root = 0)
all_data2 = comm.gather(array2, root = 0)

这将返回以下错误：

SystemError: Negative size passed to PyString_FromStringAndSize

我相信这个错误意味着存储的数据数组all_data1超过了Python中数组的最大大小，这是很有可能的。

我尝试将其分成较小的部分，如下所示：

comm.isend(array1, dest = 0, tag = rank+1)
comm.isend(array2, dest = 0, tag = rank+2)
if rank == 0:
    for proc in xrange(size):
        partial_array1 = comm.irecv(source = proc, tag = proc+1)
        partial_array2 = comm.irecv(source = proc, tag = proc+2)

但这会返回以下错误。

[node10:20210] *** Process received signal ***
[node10:20210] Signal: Segmentation fault (11)
[node10:20210] Signal code: Address not mapped (1)
[node10:20210] Failing at address: 0x2319982b

接下来是一大堆难以理解的类似路径的信息和最后一条消息：

mpirun noticed that process rank 0 with PID 0 on node node10 exited on signal 11 (Segmentation fault).

无论我使用多少个处理器，这似乎都会发生。

对于 C 中的类似问题，解决方案似乎巧妙地改变了recv调用中参数的解析方式。使用 Python 的语法是不同的，所以如果有人能说明为什么会出现这个错误以及如何修复它，我将不胜感激。

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1 回答 1

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我设法通过执行以下操作解决了我遇到的问题。

if rank != 0:
    comm.Isend([array1, MPI.FLOAT], dest = 0, tag = 77) 
    # Non-blocking send; allows code to continue before data is received.

if rank == 0:
    final_array1 = array1
    for proc in xrange(1,size):
        partial_array1 = np.empty(len(array1), dtype = float)
        comm.Recv([partial_array1, MPI.FLOAT], source = proc, tag = 77) 
        # A blocking receive is necessary here to avoid a Segfault.

        final_array1 += partial_array1

if rank != 0:
    comm.Isend([array2, MPI.FLOAT], dest = 0, tag = 135)

if rank == 0:
    final_array2 = array2
    for proc in xrange(1,size):
        partial_array2 = np.empty(len(array2), dtype = float)
        comm.Recv([partial_array2, MPI.FLOAT], source = proc, tag = 135)

        final_array2 += partial_array2

comm.barrier() # This barrier call resolves the Segfault.
if rank == 0:
    return final_array1, final_array2
else:
    return None
于 2015-11-18T23:58:04.590 回答