Пример #1
0
    def update_timestep(self, yieldstep, finaltime):
        """Calculate local timestep
        """

        generic_comms.communicate_flux_timestep(self, yieldstep, finaltime)

        Domain.update_timestep(self, yieldstep, finaltime)
Пример #2
0
    def update_timestep(self, yieldstep, finaltime):
        """Calculate local timestep
        """

        generic_comms.communicate_flux_timestep(self, yieldstep, finaltime)

        Domain.update_timestep(self, yieldstep, finaltime)
Пример #3
0
    def update_timestep(self, yieldstep, finaltime):

        #LINDA:
        # moved the calculation so that it is done after timestep
        # has been broadcast

        #        # Calculate local timestep
        #        Domain.update_timestep(self, yieldstep, finaltime)

        import time
        t0 = time.time()

        # For some reason it looks like pypar only reduces numeric arrays
        # hence we need to create some dummy arrays for communication
        ltimestep = num.ones(1, num.float)
        ltimestep[0] = self.flux_timestep
        gtimestep = num.zeros(1, num.float)  # Buffer for results

        #ltimestep = self.flux_timeste

        #print self.processor, ltimestep, gtimestep

        gtimestep = pypar.reduce(ltimestep, pypar.MIN, 0, buffer=gtimestep)

        #print self.processor, ltimestep, gtimestep

        pypar.broadcast(gtimestep, 0)

        #print self.processor, ltimestep, gtimestep

        self.flux_timestep = gtimestep[0]

        self.communication_reduce_time += time.time() - t0

        # LINDA:
        # Now update time stats

        # Calculate local timestep
        Domain.update_timestep(self, yieldstep, finaltime)
    def update_timestep(self, yieldstep, finaltime):

        #LINDA:
        # moved the calculation so that it is done after timestep
        # has been broadcast
        
#        # Calculate local timestep
#        Domain.update_timestep(self, yieldstep, finaltime)

        import time
        t0 = time.time()

        # For some reason it looks like pypar only reduces numeric arrays
        # hence we need to create some dummy arrays for communication
        ltimestep = num.ones( 1, num.float )
        ltimestep[0] = self.flux_timestep
        gtimestep = num.zeros( 1, num.float ) # Buffer for results

        #ltimestep = self.flux_timeste

        #print self.processor, ltimestep, gtimestep
        
        gtimestep = pypar.reduce(ltimestep, pypar.MIN, 0, buffer=gtimestep)

        #print self.processor, ltimestep, gtimestep
        
        pypar.broadcast(gtimestep,0)

        #print self.processor, ltimestep, gtimestep

        self.flux_timestep = gtimestep[0]
        
        self.communication_reduce_time += time.time()-t0

        # LINDA:
        # Now update time stats
        
        # Calculate local timestep
        Domain.update_timestep(self, yieldstep, finaltime)