Source code for GPy.util.parallel

The module of tools for parallelization (MPI)
import numpy as np

[docs]def get_id_within_node(comm=None): from mpi4py import MPI if comm is None: comm = MPI.COMM_WORLD rank = comm.rank nodename = MPI.Get_processor_name() nodelist = comm.allgather(nodename) return len([i for i in nodelist[:rank] if i==nodename])
[docs]def divide_data(datanum, rank, size): assert rank<size and datanum>0 residue = (datanum)%size datanum_list = np.empty((size),dtype=np.int32) for i in range(size): if i<residue: datanum_list[i] = int(datanum/size)+1 else: datanum_list[i] = int(datanum/size) if rank<residue: size = datanum/size+1 offset = size*rank else: size = datanum/size offset = size*rank+residue return offset, offset+size, datanum_list
[docs]def optimize_parallel(model, optimizer=None, messages=True, max_iters=1000, outpath='.', interval=100, name=None, **kwargs): from math import ceil from datetime import datetime import os if name is None: name = stop = 0 for iter in range(int(ceil(float(max_iters)/interval))): model.optimize(optimizer=optimizer, messages= True if messages and model.mpi_comm.rank==model.mpi_root else False, max_iters=interval, **kwargs) if model.mpi_comm.rank==model.mpi_root: timenow = timestr = timenow.strftime('%Y:%m:%d_%H:%M:%S'), name+'_'+timestr+'.h5')) opt = model.optimization_runs[-1] if opt.funct_eval<opt.max_f_eval: stop = 1 stop = model.mpi_comm.bcast(stop, root=model.mpi_root) if stop: break