def exit(self, code): '''This method exits the simulation. In a parallel environment calls MPI_ABORT. In serial, calls sys.exit(). Code is the exit code. Only used in serial processes.''' if Environment.isParallel: import pypar return pypar.abort(code) else: return sys.exit(code)
# mpirun -np 4 demo.py import pypar # The Python-MPI interface import numpy typ = 'd' #'i', 'l', 'f', 'd' numproc = pypar.size() myid = pypar.rank() node = pypar.Get_processor_name() print "I am proc %d of %d on node %s" %(myid, numproc, node) if numproc < 2: print "Demo must run on at least 2 processors to continue" pypar.abort() if myid == 0: msg = numpy.array([0], typ) print 'Processor 0 sending message "%s" to processor %d' %(str(msg), 1) pypar.send(msg, 1) msg, status = pypar.receive(numproc-1, return_status=True) print 'Processor 0 received message "%s" from processor %d' %(str(msg), numproc-1) print 'Size of msg was %d bytes' %(status.bytes()) else: source = myid-1 destination = (myid+1)%numproc
msgid = 0 vanilla = 0 #Select vanilla mode (slower but general) numprocs = pypar.size() myid = pypar.rank() processor_name = pypar.get_processor_name() if myid == 0: # Main process - Create message, pass on, verify correctness and log timing # print "MAXM = %d, number of processors = %d" %(MAXM, numprocs) print "Measurements are repeated %d times for reliability" %repeats if numprocs < 2: print "Program needs at least two processors - aborting\n" pypar.abort() pypar.barrier() #Synchronize all before timing print "I am process %d on %s" %(myid,processor_name) #Initialise data and timings # try: from numpy.random import uniform, seed seed(17) A = uniform(0.0,100.0,MAXM) except: print 'problem with RandomArray' from numpy import ones, Float
