I am trying to parallelise some operations on a large numpy array using mpi4py. I am currently using numpy.array_split
to divide the array into chunks, followed by com.scatter
to send the array to different cores and then comm.gather
to collect the resulting arrays. A minimal (not) working example is below:
import numpy as np
from mpi4py import MPI
comm = MPI.COMM_WORLD
size = comm.Get_size()
rank = comm.Get_rank()
if rank == 0:
test = np.random.rand(411,48,52,40)
test_chunks = np.array_split(test,size,axis=0)
else:
test_chunks = None
test_chunk = comm.scatter(test_chunks,root=0)
output_chunk = np.zeros([np.shape(test_chunk)[0],128,128,128])
for i in range(0,np.shape(test_chunk)[0],1):
print(i)
output_chunk[i,0:48,0:52,0:40] = test_chunk[i]
outputData = comm.gather(output_chunk,root=0)
if rank == 0:
outputData = np.concatenate(outputData,axis = 0)
Running this gives me the error:
File "test_4d.py", line 23, in <module>
outputData = comm.gather(output_chunk,root=0)
File "Comm.pyx", line 869, in mpi4py.MPI.Comm.gather (src/mpi4py.MPI.c:73266)
File "pickled.pxi", line 614, in mpi4py.MPI.PyMPI_gather (src/mpi4py.MPI.c:33592)
File "pickled.pxi", line 146, in mpi4py.MPI._p_Pickle.allocv (src/mpi4py.MPI.c:28517)
File "pickled.pxi", line 95, in mpi4py.MPI._p_Pickle.alloc (src/mpi4py.MPI.c:27832)
SystemError: Negative size passed to PyString_FromStringAndSize
This error seems to result from the large size of the numpy arrays being collected by gather; since scatter and gather send the arrays as a list of arrays, it appears easy to exceed the list size. One suggestion I have come across is to use comm.Scatter and comm.Gather. However, I am struggling to find clear documentation for these functions and so far have been unable to successfully implement them. For example:
replacing
outputData = comm.gather(output_chunk,root=0)
with the line
outputData=comm.Gather(sendbuf[test_chunks,MPI.DOUBLE],recvbuf=output_chunk,MPI.DOUBLE],root=0)
gives the error:
File "Comm.pyx", line 415, in mpi4py.MPI.Comm.Gather (src/mpi4py.MPI.c:66916)
File "message.pxi", line 426, in mpi4py.MPI._p_msg_cco.for_gather (src/mpi4py.MPI.c:23559)
File "message.pxi", line 355, in mpi4py.MPI._p_msg_cco.for_cco_send (src/mpi4py.MPI.c:22959)
File "message.pxi", line 111, in mpi4py.MPI.message_simple (src/mpi4py.MPI.c:20516)
File "message.pxi", line 51, in mpi4py.MPI.message_basic (src/mpi4py.MPI.c:19644)
File "asbuffer.pxi", line 108, in mpi4py.MPI.getbuffer (src/mpi4py.MPI.c:6757)
File "asbuffer.pxi", line 50, in mpi4py.MPI.PyObject_GetBufferEx (src/mpi4py.MPI.c:6093)
TypeError: expected a readable buffer object
or with the line:
outputData = comm.Gather(sendbuf=test_chunks, recvbuf=output_chunk,root=0)
gives the error:
File "test_4d_2.py", line 24, in <module>
outputData = comm.Gather(sendbuf=test_chunks, recvbuf=output_chunk,root=0)
File "Comm.pyx", line 415, in mpi4py.MPI.Comm.Gather (src/mpi4py.MPI.c:66916)
File "message.pxi", line 426, in mpi4py.MPI._p_msg_cco.for_gather (src/mpi4py.MPI.c:23559)
File "message.pxi", line 355, in mpi4py.MPI._p_msg_cco.for_cco_send (src/mpi4py.MPI.c:22959)
File "message.pxi", line 111, in mpi4py.MPI.message_simple (src/mpi4py.MPI.c:20516)
File "message.pxi", line 60, in mpi4py.MPI.message_basic (src/mpi4py.MPI.c:19747)
TypeError: unhashable type: 'numpy.ndarray'
Furthermore, the input matrix, test
may also increase in size, which could cause similar problems for comm.scatter
. Aside from the problems I already have with comm.Gather
, I am not sure how to set up comm.Scatter
, since recvbuf
is defined based on the size of test_chunk
, which is the output of comm.scatter
, so hence I can't specify recvbuf
within comm.Scatter
.
The solution is to use comm.Scatterv
and comm.Gatherv
which send and receive the data as a block of memory, rather than a list of numpy arrays, getting around the data size issue. comm.Scatterv
and comm.Gatherv
assume a block of data in C-order (row-major) in memory and it is necessary to specify two vectors, sendcounts
and displacements
. Sendcounts
gives the integer value (index) for the positions at which to split the input data (i.e. the starting point of each vector to send to a given core), while displacements
gives the length of that vector. Hence it is possible to vary the amount of data sent to each core. More details can be found here: http://materials.jeremybejarano.com/MPIwithPython/collectiveCom.html
An example using comm.Scatterv
and comm.Gatherv
for a 2D matrix is given here:
Along what axis does mpi4py Scatterv function split a numpy array?