我们从Python开源项目中,提取了以下10个代码示例,用于说明如何使用mpi4py.MPI.ANY_TAG。
def _iter(self): sleeped = 0 # measure time w/o messaging # Waiting for any input while not self.comm.Iprobe(source=MPI.ANY_SOURCE, tag=MPI.ANY_TAG): if sleeped == 0.5: secs_since_start = round(time.time() - self.start, 1) logger.info('Sleeping @ %s s.', secs_since_start) # TODO: stats! # observe ram usage # observe free disk space # observe ... # make sure executed every 60? seconds if self.numworkers == 0: self._shutdown() # TODO: think about better use of sleeped sleeped += self._manage_io() if sleeped > 0.5: logger.info("Slept for %s seconds.", sleeped - 0.5) # TODO: catch mpi.send errors properly try: self._process_mpi() except IndexError as e: logger.info('IndexError happend: %s', e)
def recv(self, obj=None, tag=MPI.ANY_TAG, source=None, buffer=False, status=None, comm=None): """Wrapper around MPI.recv/Recv. Returns the received object. Params: obj: variable into which the received object should be placed tag: string indicating which MPI tag should be received source: integer rank of the message source. Defaults to self.parent_rank buffer: True if the received object should be sent as a single-segment buffer (e.g. for numpy arrays) using MPI.Recv rather than MPI.recv status: MPI status object that is filled with received status information comm: MPI communicator to use. Defaults to self.parent_comm""" if comm is None: comm = self.parent_comm if source is None: if self.parent_rank is None: raise Error("Attempting to receive %s from parent, but parent rank is None" % tag) source = self.parent_rank tag_num = self.lookup_mpi_tag(tag) if buffer: comm.Recv( obj, source=source, tag=tag_num, status=status ) return obj else: obj = comm.recv( source=source, tag=tag_num, status=status ) return obj
def _fit_slave(self, X, y): """Pipeline evaluation. Parameters ---------- X : array of float, shape : n_samples x n_features, default : () The input data matrix. """ try: while True: status_ = MPI.Status() received = COMM.recv(source=0, tag=MPI.ANY_TAG, status=status_) # check the tag of the received message if status_.tag == EXIT: return # do the work i, (train_index, test_index) = received # if self.verbose: # print("[{} {}]: Performing experiment {}".format( # NAME, RANK, i)) cv_results_ = _worker(self, i, X, y, train_index, test_index) # if self.verbose: # print("[{} {}]: Experiment {} completed".format( # NAME, RANK, i)) COMM.send(cv_results_, dest=0, tag=0) except StandardError as exc: warnings.warn("Quitting ... TB:", str(exc))
def _worker(self, clf): """Worker node's operation. Receiving tasks from the master to process and sending the result back Parameters ---------- clf: classification function the classifier to be used in cross validation Returns ------- None """ logger.debug( 'worker %d is running, waiting for tasks from master at rank %d' % (MPI.COMM_WORLD.Get_rank(), self.master_rank) ) comm = MPI.COMM_WORLD status = MPI.Status() while 1: task = comm.recv(source=self.master_rank, tag=MPI.ANY_TAG, status=status) if status.Get_tag(): break comm.send(self._voxel_scoring(task, clf), dest=self.master_rank)
def wait(self, callback=None): """Tell the workers to wait and listen for the master process. This is called automatically when using :meth:`MPIPool.map` and doesn't need to be called by the user. """ if self.is_master(): return worker = self.comm.rank status = MPI.Status() while True: log.log(_VERBOSE, "Worker {0} waiting for task".format(worker)) task = self.comm.recv(source=self.master, tag=MPI.ANY_TAG, status=status) if task is None: log.log(_VERBOSE, "Worker {0} told to quit work".format(worker)) break func, arg = task log.log(_VERBOSE, "Worker {0} got task {1} with tag {2}" .format(worker, arg, status.tag)) result = func(arg) log.log(_VERBOSE, "Worker {0} sending answer {1} with tag {2}" .format(worker, result, status.tag)) self.comm.ssend(result, self.master, status.tag) if callback is not None: callback()
def wait(self): """ If this isn't the master process, wait for instructions. """ if self.is_master(): raise RuntimeError("Master node told to await jobs.") status = MPI.Status() while True: # Event loop. # Sit here and await instructions. if self.debug: print("Worker {0} waiting for task.".format(self.rank)) # Blocking receive to wait for instructions. task = self.comm.recv(source=0, tag=MPI.ANY_TAG, status=status) if self.debug: print("Worker {0} got task {1} with tag {2}." .format(self.rank, type(task), status.tag)) # Check if message is special sentinel signaling end. # If so, stop. if isinstance(task, _close_pool_message): if self.debug: print("Worker {0} told to quit.".format(self.rank)) break # Check if message is special type containing new function # to be applied if isinstance(task, _function_wrapper): self.function = task.function if self.debug: print("Worker {0} replaced its task function: {1}." .format(self.rank, self.function)) continue # If not a special message, just run the known function on # the input and return it asynchronously. result = self.function(task) if self.debug: print("Worker {0} sending answer {1} with tag {2}." .format(self.rank, type(result), status.tag)) self.comm.isend(result, dest=0, tag=status.tag) # Kill the process? if self.exit_on_end: sys.exit()
def wait(self): """ If this isn't the master process, wait for instructions. """ if self.is_master(): raise RuntimeError("Master node told to await jobs.") status = MPI.Status() while True: # Event loop. # Sit here and await instructions. if self.debug: print("Worker {0} waiting for task.".format(self.rank)) # Blocking receive to wait for instructions. task = self.comm.recv(source=0, tag=MPI.ANY_TAG, status=status) if self.debug: print("Worker {0} got task {1} with tag {2}." .format(self.rank, task, status.tag)) # Check if message is special sentinel signaling end. # If so, stop. if isinstance(task, _close_pool_message): if self.debug: print("Worker {0} told to quit.".format(self.rank)) break # Check if message is special type containing new function # to be applied if isinstance(task, _function_wrapper): self.function = task.function if self.debug: print("Worker {0} replaced its task function: {1}." .format(self.rank, self.function)) continue # If not a special message, just run the known function on # the input and return it asynchronously. result = self.function(task) if self.debug: print("Worker {0} sending answer {1} with tag {2}." .format(self.rank, result, status.tag)) self.comm.isend(result, dest=0, tag=status.tag)
def orchestrate_map(self,pds_id): """Orchestrates the slaves/workers to perform a map function This works by keeping track of the workers who haven't finished executing, waiting for them to request the next chunk of data when they are free, responding to them with the data and then sending them a Sentinel signalling that they can exit. """ is_map_done = [True if i in self.master_node_ranks else False for i in range(self.size)] status = MPI.Status() #Copy it to the pending. This is so when master accesses #the PDS data it's not empty. self.pds_pending_store[pds_id] = list(self.pds_store[pds_id]) #While we have some ranks that haven't finished while sum(is_map_done)<self.size: #Wait for a reqest from anyone data_request = self.comm.recv( source=MPI.ANY_SOURCE, tag=MPI.ANY_TAG, status=status, ) request_from_rank = status.source if data_request!=pds_id: print("Ignoring stale PDS data request from", request_from_rank,":",data_request,"/",pds_id) continue #Pointer so we don't have to keep doing dict lookups current_pds_items = self.pds_pending_store[pds_id] num_current_pds_items = len(current_pds_items) #Everyone's already exhausted all the data. # Send a sentinel and mark the node as finished if num_current_pds_items == 0: self.comm.send(None, dest=request_from_rank, tag=pds_id) is_map_done[request_from_rank] = True else: #Create the chunk of data to send. Pop off items and tag them with an id. # so we can sort them later chunk_to_send = [] for i in range(self.chunk_size): chunk_to_send+=[(num_current_pds_items-i,current_pds_items.pop())] self.comm.send(chunk_to_send, dest=request_from_rank, tag=pds_id)
def iter(self,log=None,np=None): ''' The iteration of the Lanczos. Parameters ---------- log : Log, optional The log file to record the iteration information. np : int, optional The number of subprocess to perform the iteration. ''' t0=time.time() if self.method=='S' and (np is None or np<=0): vecs,Qs=self.controllers['vecs'],self.controllers['Qs'] for i,lanczos in enumerate(self.controllers['lczs']): ts=time.time() while lanczos.niter<lanczos.maxiter and not lanczos.stop: lanczos.iter() Qs[i,:,lanczos.niter-1]=vecs.dot(lanczos.vectors[lanczos.niter-1]) te=time.time() if log: log<<'%s%s%s'%('\b'*30 if i>0 else '',('%s/%s(%.2es/%.3es)'%(i+1,len(Qs),te-ts,te-t0)).center(30),'\b'*30 if i==len(Qs)-1 else '') elif self.method=='B': lanczos=self.controllers['lanczos'] for i in xrange(lanczos.maxiter): ts=time.time() lanczos.iter() te=time.time() if log: log<<'%s%s%s'%('\b'*30 if i>0 else '',('%s/%s(%.2es/%.3es)'%(i+1,lanczos.maxiter,te-ts,te-t0)).center(30),'\b'*30 if i==lanczos.maxiter-1 else '') elif self.method=='S' and np is not None: path,Qs=os.path.dirname(os.path.realpath(__file__)),self.controllers['Qs'] datas=[[self.controllers['vecs'],[],[]] for i in xrange(np)] for i,lanczos in enumerate(self.controllers['lczs']): datas[i%np][1].append(lanczos) datas[i%np][2].append(i) comm=MPI.COMM_SELF.Spawn(sys.executable,args=['%s/edbgf.py'%path],maxprocs=np) for i,data in enumerate(datas): comm.send(data,dest=i,tag=0) info,ic,nc=MPI.Status(),0,0 while nc<np: data=comm.recv(source=MPI.ANY_SOURCE,tag=MPI.ANY_TAG,status=info) if info.Get_tag()==0: for index,(_T_,P,niter),Q in data: lanczos=self.controllers['lczs'][index] lanczos._T_,lanczos.P,lanczos.niter=_T_,P,niter Qs[index,:,:]=Q nc+=1 else: ic,(index,t)=ic+1,data if log: log<<'%s%s%s'%('\b'*30 if ic>1 else '',('%s/%s(%.2es/%.3es)'%(ic,len(Qs),t,time.time()-t0)).center(30),'\b'*30 if ic==len(Qs) else '') comm.Disconnect() else: raise ValueError('BGF iter error: not supported.')