abaqus利用Python实现部件合并及调用Abaqus Python并行化嵌套循环

I have the nested loops below. How can i parallelize the outside loop so i can distribute the outside loop into 4 simultaneous runs and wait for all 4 runs to complete before moving on with the rest of the script?

for r in range(4):

for k in range( r*nAnalysis/4, (r+1)*nAnalysis/4 ):

# - Write Abaqus INP file - #

writeABQfile(ppos,props,totalTime[k],recInt[k],inpFiles[k],i,lineNum[k],aPath[k])

# - Delete LCK file to Enable Another Analysis - #

delFile(aPath[k]+"/"+inpFiles[k]+".lck")

# - Run Analysis - #

runABQfile(inpFiles[k],aPath[k])

I tried using multiprocess.pool as but it never gets in:

def parRunABQfiles(nA,nP,r,ppos,prop0,prop1,totalTime2Run_,recIntervals_,inpFiles_,i,lineNumbers_,aPath_):

from os import path

from auxFunctions import writeABQfile, runABQfile

print("I am Here")

for k in range( r*nA/nP, (r+1)*nA/nP ):

# - Write Abaqus INP file - #

writeABQfile(ppos,prop0,prop1,totalTime2Run_,recIntervals_,inpFiles_,i,lineNumbers_,aPath_)

# - Delete LCK file to Enable Another Analysis - #

delFile(aPath_+"/"+inpFiles[k]+".lck")

# - Run Analysis - #

runABQfile(inpFiles_,aPath_)

# - Make Sure Analysis is not Bypassed - #

while os.path.isfile(aPath_+"/"+inpFiles[k]+".lck") == True:

sleep(0.1)

return k

results = zip(*pool.map(parRunABQfiles, range(0, 4, 1)))

The runABQfile is just a subprocess.call to a sh script that runs abaqus

def runABQfile(inpFile,path):

import subprocess

import os

prcStr1 = ('sbatch '+path+'/runJob.sh')

process = subprocess.call(prcStr1, stdin=None, stdout=None, stderr=None, shell=True )

return

I have no errors showing up so I am not sure why is not getting in there. I know because the writeABQfile does not write the input file. The question again is:

How can i parallelize the outside loop so i can distribute the outside loop into 4 simultaneous runs and wait for all 4 runs to complete before moving on with the rest of the script?

解决方案

Use concurrent.futures module if multiprocessing is what you want.

from concurrent.futures import ProcessPoolExecutor

def each(r):

for k in range( r*nAnalysis/4, (r+1)*nAnalysis/4 ):

writeABQfile(ppos,props,totalTime[k],recInt[k],inpFiles[k],i,lineNum[k],aPath[k])

delFile(aPath[k]+"/"+inpFiles[k]+".lck")

runABQfile(inpFiles[k],aPath[k])

with ProcessPoolExecutor(max_workers=4) as executor:

output = executor.map(each, range(4)) # returns an iterable

If you just want to "do" stuff rather than "produce", check out as_completed function from the same module. There are direct examples in the doc.

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