我正在开发一种模拟波浪能转换器的工具,我需要将两个软件包相互耦合。一个程序用Fortran编写,另一个用C ++编写。我需要在每个时间步骤将Fortran程序中的信息发送到C ++程序。但是,在将数据发送到C ++程序之前,首先需要在Python中处理数据。我收到了一条使用MPI在程序之间传输数据的提示。
我现在正尝试将一个简单的字符串从Fortran代码发送到Python,但Python代码卡在receive命令中。
我的Fortran代码如下所示:
USE GlobalVariables
USE MPI
IMPLICIT NONE
CHARACTER(LEN=10):: astring
INTEGER :: comm, rank, size, mpierr
! Initialize MPI on first timestep
IF(tstep .LT. 2) THEN
call MPI_INIT(mpierr)
ENDIF
! make string to send to python
astring = "TEST"
! MPI Test
call MPI_Comm_size(MPI_COMM_WORLD, size, mpierr)
call MPI_Comm_rank(MPI_COMM_WORLD, rank, mpierr)
! Send message to python
CALL MPI_SEND(astring, len(astring), MPI_CHARACTER, 0, 22, MPI_COMM_WORLD, mpierr)
print *, 'MPI MESSAGE SENT ', mpierr
! Initialize MPI on first timestep
IF(tstep .EQ. Nsteps-1) THEN
call MPI_FINALIZE(mpierr)
print *, 'MPI FINALIZED!'
ENDIF
我的Python代码如下:
from mpi4py import MPI
import numpy as np
import subprocess as sp
import os
# Start OW3D_SPH in the background and send MPI message
os.chdir('OW3D_run')
args = ['OceanWave3D_SPH','OW3D.inp']
pid = sp.Popen(args,shell=False)
os.chdir('..')
# Check if MPI is initialized
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
# Receive message from fortran
test = comm.recv(source=0, tag=22)
# Let the program end
output = pid.communicate()
with open('test.txt','w') as f:
f.write(test)
Python代码永远不会通过MPI接收命令而无法完成。 Fortran代码完成并正确打印" MPI FINALIZED"消息。
我不知道我做错了什么,消息从过程0发送到过程0并带有标签22并在两个代码中使用MPI_COMM_WORLD
。
答案 0 :(得分:8)
如果要在同一个MPI作业中启动Fortran程序和Python程序,则必须使用以下内容:
mpiexec -n 1 fortran_program : -n 1 python main.py
Fortran程序将成为MPI等级0,Python程序将成为MPI等级1.您还可以启动每个可执行文件中的多个,例如:
mpiexec -n 2 fortran_program : -n 4 python main.py
排名0和1将来自Fortran程序,排名2到5 - 来自Python。
另请注意,comm.recv()
以及mpi4py中以小写字母(comm.send()
,comm.irecv()
等开头)的其他通信方法使用了引擎盖下的Pickle并实际使用序列化Python进行操作对象。这与Fortran代码发送的字符数组不兼容。您必须使用以大写字母(comm.Send()
,comm.Recv()
等)开头的通信方法,这些方法在NumPy阵列上运行并接收显式类型信息。不幸的是,我的Python fu很弱,我现在无法提供完整的工作示例,但MPI部分应该是这样的(未经验证的代码):
# Create an MPI status object
status = MPI.Status()
# Wait for a message without receiving it
comm.Probe(source=0, tag=22, status=status)
# Check the length of the message
nchars = status.Get_count(MPI.CHARACTER)
# Allocate a big enough data array of characters
data = np.empty(nchars, dtype='S')
# Receive the message
comm.Recv([data, MPI.CHARACTER], source=0, tag=22)
# Construct somehow the string out of the individual chars in "data"
在Fortran代码中,您必须指定目标等级1(如果您运行一个Fortran可执行文件,则运行一个Python)。
答案 1 :(得分:5)
当两者都是不同的程序时,你当然不能同时拥有源0和目标0。你说“从进程0到进程0”但你显然有两个不同的进程!其中一个有不同的排名,但你没有显示你的实际mpirun
命令,所以很难说哪个是哪个。
澄清:MPI_COM_WORLD是您的mpirun或同等程序中执行的所有进程的通信器。你必须留下简单的思维图片,第一个Python进程是0级,第一个Fortran进程是0级,第一个C ++是0级...
如果你这样做
mpirun -n 1 python main.py : -n 1 ./fortran_main : -n 1 ./c++_main
然后在MPI_COMM_WORLD中,Python程序将排名为0,Fortran进程将排名为1,C ++将排名为2.您可以创建仅限于Python子集或Fortran子集或C ++的通信器和您将在每个中排名为0,但这将在不同的沟通者中编号,而不是在MPI_COMM_WORLD中。
答案 2 :(得分:4)
MPI进程可以使用函数MPI_Comm_spawn()
生成进程。在python程序中,此函数是通信器的一种方法:comm.Spawn()
。有关示例,请参阅the mpi4py tutorial。 生成的进程根据可执行文件运行,可执行文件可能是另一个python程序,ac / c ++ / fortran程序或任何你想要的。然后,一个intercommunicator可以merged来定义一个interracommunicator主进程和在mpi4py: Communicating between spawned processes中执行的生成进程因此,主进程和生成的进程可以无任何限制地自由通信。
我们来介绍一个Python / c示例。 Python代码生成进程并接收一个字符:
from mpi4py import MPI
import sys
import numpy
'''
slavec is an executable built starting from slave.c
'''
# Spawing a process running an executable
# sub_comm is an MPI intercommunicator
sub_comm = MPI.COMM_SELF.Spawn('slavec', args=[], maxprocs=1)
# common_comm is an intracommunicator accross the python process and the spawned process. All kind sof collective communication (Bcast...) are now possible between the python process and the c process
common_comm=sub_comm.Merge(False)
#print 'parent in common_comm ', common_comm.Get_rank(), ' of ',common_comm.Get_size()
data = numpy.arange(1, dtype='int8')
common_comm.Recv([data, MPI.CHAR], source=1, tag=0)
print "Python received message from C:",data
# disconnecting the shared communicators is required to finalize the spawned process.
common_comm.Disconnect()
sub_comm.Disconnect()
mpicc slave.c -o slavec -Wall
编译的C代码使用合并的通信器发送角色:
#include <mpi.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
int main(int argc,char *argv[])
{
int rank,size;
MPI_Comm parentcomm,intracomm;
MPI_Init( &argc, &argv );
//MPI_Comm_rank(MPI_COMM_WORLD, &rank);
MPI_Comm_get_parent( &parentcomm );
if (parentcomm == MPI_COMM_NULL){fprintf(stderr,"module1 : i'm supposed to be the spawned process!");exit(1);}
MPI_Intercomm_merge(parentcomm,1,&intracomm);
MPI_Comm_size(intracomm, &size);
MPI_Comm_rank(intracomm, &rank);
//printf("child had rank %d in communicator of size %d\n",rank,size);
char s= 42;
printf("sending message %d from C\n",s);
MPI_Send(&s,1,MPI_CHAR,0,0,intracomm);
MPI_Comm_disconnect(&intracomm); //disconnect after all communications
MPI_Comm_disconnect(&parentcomm);
MPI_Finalize();
return 0;
}
让我们从C ++代码接收一个字符并将一个整数发送到fortran程序:
'''
slavecpp is an executable built starting from slave.cpp
'''
# Spawing a process running an executable
# sub_comm is an MPI intercommunicator
sub_comm = MPI.COMM_SELF.Spawn('slavecpp', args=[], maxprocs=1)
# common_comm is an intracommunicator accross the python process and the spawned process. All kind sof collective communication (Bcast...) are now possible between the python process and the c process
common_comm=sub_comm.Merge(False)
#print 'parent in common_comm ', common_comm.Get_rank(), ' of ',common_comm.Get_size()
data = numpy.arange(1, dtype='int8')
common_comm.Recv([data, MPI.CHAR], source=1, tag=0)
print "Python received message from C++:",data
# disconnecting the shared communicators is required to finalize the spawned process.
common_comm.Disconnect()
sub_comm.Disconnect()
'''
slavef90 is an executable built starting from slave.cpp
'''
# Spawing a process running an executable
# sub_comm is an MPI intercommunicator
sub_comm = MPI.COMM_SELF.Spawn('slavef90', args=[], maxprocs=1)
# common_comm is an intracommunicator accross the python process and the spawned process. All kind sof collective communication (Bcast...) are now possible between the python process and the c process
common_comm=sub_comm.Merge(False)
#print 'parent in common_comm ', common_comm.Get_rank(), ' of ',common_comm.Get_size()
data = numpy.arange(1, dtype='int32')
data[0]=42
print "Python sending message to fortran:",data
common_comm.Send([data, MPI.INT], dest=1, tag=0)
print "Python over"
# disconnecting the shared communicators is required to finalize the spawned process.
common_comm.Disconnect()
sub_comm.Disconnect()
由mpiCC slave.cpp -o slavecpp -Wall
编译的C ++程序非常接近C 1:
#include <iostream>
#include <mpi.h>
#include <stdlib.h>
using namespace std;
int main(int argc,char *argv[])
{
int rank,size;
MPI_Comm parentcomm,intracomm;
MPI_Init( &argc, &argv );
//MPI_Comm_rank(MPI_COMM_WORLD, &rank);
MPI_Comm_get_parent( &parentcomm );
if (parentcomm == MPI_COMM_NULL){fprintf(stderr,"module1 : i'm supposed to be the spawned process!");exit(1);}
MPI_Intercomm_merge(parentcomm,1,&intracomm);
MPI_Comm_size(intracomm, &size);
MPI_Comm_rank(intracomm, &rank);
//cout<<"child had rank "<<rank<<" in communicator of size "<<size<<endl;
char s= 42;
cout<<"sending message "<<(int)s<<" from C++"<<endl;
MPI_Send(&s,1,MPI_CHAR,0,0,intracomm);
MPI_Comm_disconnect(&intracomm); //disconnect after all communications
MPI_Comm_disconnect(&parentcomm);
MPI_Finalize();
return 0;
}
最后,由mpif90 slave.f90 -o slavef90 -Wall
编译的Fortran程序接收整数:
program test
!
implicit none
!
include 'mpif.h'
!
integer :: ierr,s(1),stat(MPI_STATUS_SIZE)
integer :: parentcomm,intracomm
!
call MPI_INIT(ierr)
call MPI_COMM_GET_PARENT(parentcomm, ierr)
call MPI_INTERCOMM_MERGE(parentcomm, 1, intracomm, ierr)
call MPI_RECV(s, 1, MPI_INTEGER, 0, 0, intracomm,stat, ierr)
print*, 'fortran program received: ', s
call MPI_COMM_DISCONNECT(intracomm, ierr)
call MPI_COMM_DISCONNECT(parentcomm, ierr)
call MPI_FINALIZE(ierr)
endprogram test
通过对通信器的更多工作,“C ++进程”可以直接向“fortran进程”发送消息,甚至不涉及通信中的主进程。
最后,以这种方式混合语言似乎很容易,但从长远来看,它可能不是一个好的解决方案。实际上,您可能会面临与表演有关的问题或维护系统可能会变得困难(三种语言......)。对于C ++部分,Cython和F2PY可能是一个有价值的选择。毕竟,Python is a little bit like a glue ......
答案 3 :(得分:1)
我不会为此目的使用MPI(除非明确要求并行执行代码)。如果您的目标是连接用Fortran,C ++和Python编写的例程,那么我建议在Python中编写(主要)连接部分,同时为Fortran和C ++例程创建适配器,以便在Python中导入它们。然后,您可以管理主Python程序中的所有函数调用,并根据需要发送数据。
查看以下链接:
f2py
现在附带numpy
,允许您将Fortran源代码编译为Python字节代码。