#!/usr/bin/env python3
# Author: Octavio Castillo Reyes
# Contact: octavio.castillo@bsc.es
"""Define classes and functions for parallel computations within **PETGEM**."""
# ---------------------------------------------------------------
# Load python modules
# ---------------------------------------------------------------
from mpi4py import MPI
from singleton_decorator import singleton
from petsc4py import PETSc
# ###############################################################
# ################ CLASSES DEFINITION ##################
# ###############################################################
@singleton
class MPIEnvironment():
"""MPI class definition."""
def __init__(self):
"""Class for initialization of an MPI environment.
:param: None.
:return: class for MPI environment.
:rtype: mpi_env class.
"""
# Store the MPI environment
self.MPI = MPI
# MPI communicator
self.comm = MPI.COMM_WORLD
# MPI process identifier
self.rank = self.comm.Get_rank()
# Size of the group associated with a communicator
self.num_proc = self.comm.Get_size()
# Machine name
self.machine_name = self.MPI.Get_processor_name()
return
# ###############################################################
# ################ FUNCTIONS DEFINITION #################
# ###############################################################
[docs]def createSequentialDenseMatrixWithArray(dimension1, dimension2, data):
"""Given an input array, create a sequential dense matrix in petsc format.
:param int dimension1: matrix dimension (rows).
:param int dimension2: matrix dimension (columns).
:param ndarray data: data to be exported.
:return: parallel matrix.
:rtype: petsc parallel and dense matrix.
"""
parallel_matrix = PETSc.Mat().createDense([dimension1, dimension2],
array=data, comm=PETSc.COMM_SELF)
parallel_matrix.setFromOptions()
parallel_matrix.setUp()
return parallel_matrix
[docs]def writeParallelDenseMatrix(output_file, data, communicator=None):
"""Write a Petsc parallel dense matrix which format is defined by two files: output_file.dat and output_file.info.
:param str output_file: file name to be saved.
:param petsc matrix data: dense matrix to be saved.
:param str communicator: mpi communicator.
:return: None.
"""
if communicator is None:
communicator = PETSc.COMM_WORLD
viewer = PETSc.Viewer().createBinary(output_file, mode='w', comm=communicator)
viewer(data)
return
[docs]def createSequentialVectorWithArray(data):
"""Given an input array, create a sequential vector in petsc format.
:param ndarray data: data to be exported.
:return: parallel matrix.
:rtype: petsc parallel and dense matrix.
"""
parallel_vector = PETSc.Vec().createWithArray(data, comm=PETSc.COMM_SELF)
parallel_vector.setUp()
return parallel_vector
[docs]def writePetscVector(output_file, data, communicator=None):
"""Write a Petsc vector which format is defined by two files: output_file.dat and output_file.info.
:param str output_file: file name to be saved.
:param petsc vector data: array to be saved.
:param str communicator: mpi communicator.
:return: None.
"""
if communicator is None:
communicator = PETSc.COMM_WORLD
viewer = PETSc.Viewer().createBinary(output_file, mode='w',
comm=communicator)
viewer(data)
return
[docs]def readPetscMatrix(input_file, communicator=None):
"""Read a Petsc matrix which format is defined by two files: input_file.dat and input_file.info.
:param str input_file: file name to be readed.
:param str communicator: mpi communicator.
:return: petsc_matrix.
:rtype: petsc sparse matrix.
"""
if communicator is None:
communicator = PETSc.COMM_WORLD
viewer = PETSc.Viewer().createBinary(input_file, mode='r',
comm=communicator)
petsc_matrix = PETSc.Mat().load(viewer)
return petsc_matrix
[docs]def readPetscVector(input_file, communicator=None):
"""Read a Petsc vector which format is defined by two files: input_file.dat and input_file.info.
:param str input_file: file name to be readed.
:param str communicator: mpi communicator.
:return: petsc_vector.
:rtype: petsc vector.
"""
if communicator is None:
communicator = PETSc.COMM_WORLD
viewer = PETSc.Viewer().createBinary(input_file, mode='r',
comm=communicator)
petsc_vector = PETSc.Vec().load(viewer)
return petsc_vector
[docs]def createParallelMatrix(dimension1,dimension2,nnz,matrix_type,communicator=None):
"""Create a parallel sparse matrix in petsc format.
:param int dimension1: matrix dimension (rows).
:param int dimension2: matrix dimension (columns).
:param int nnz: not zero pattern for allocation.
:param int matrix_type: matrix type for parallel computations.
:param str communicator: mpi communicator.
:return: parallel matrix.
:rtype: petsc AIJ parallel matrix.
"""
if communicator is None:
communicator = PETSc.COMM_WORLD
if matrix_type: # Cuda support
parallel_matrix = PETSc.Mat().create(comm=communicator)
parallel_matrix.setType('aijcusparse')
parallel_matrix.setSizes([dimension1, dimension2])
elif not matrix_type: # No cuda support
parallel_matrix = PETSc.Mat().createAIJ([dimension1, dimension2], comm=communicator)
else:
raise ValueError('Cuda option=', matrix_type, ' not supported.')
parallel_matrix.setPreallocationNNZ((nnz, nnz))
parallel_matrix.setFromOptions()
parallel_matrix.setUp()
return parallel_matrix
[docs]def createParallelVector(size, vector_type, communicator=None):
"""Create a parallel vector in petsc format.
:param int size: vector size.
:param int vector_type: vector type for parallel computations.
:param str communicator: mpi communicator.
:return: parallel vector.
:rtype: petsc parallel vector.
"""
if communicator is None:
communicator = PETSc.COMM_WORLD
if vector_type: # Cuda support
parallel_vector = PETSc.Vec().create(comm=communicator)
parallel_vector.setType('cuda')
parallel_vector.setSizes(size)
elif not vector_type: # No cuda support
parallel_vector = PETSc.Vec().createMPI(size, comm=communicator)
else:
raise ValueError('Cuda option=', vector_type, ' not supported.')
parallel_vector.setUp()
return parallel_vector
[docs]def createSequentialVector(size, vector_type, communicator=None):
"""Create a sequential vector in petsc format.
:param int size: vector size.
:param int vector_type: vector type for parallel computations.
:param str communicator: mpi communicator.
:return: sequential vector.
:rtype: petsc sequential vector.
"""
if communicator is None:
communicator = PETSc.COMM_SELF
if vector_type == 0: # No cuda support
sequential_vector = PETSc.Vec().createSeq(size, comm=communicator)
elif vector_type == 1: # Cuda support
sequential_vector = PETSc.Vec().create(comm=communicator)
sequential_vector.setType('cuda')
sequential_vector.setSizes(size)
sequential_vector.setUp()
return sequential_vector
[docs]def createParallelDenseMatrix(dimension1, dimension2, communicator=None):
"""Create a parallel dense matrix in petsc format.
:param int dimension1: matrix dimension (rows).
:param int dimension2: matrix dimension (columns).
:param str communicator: mpi communicator.
:return: parallel matrix.
:rtype: petsc parallel and dense matrix.
"""
if communicator is None:
communicator = PETSc.COMM_WORLD
parallel_matrix = PETSc.Mat().createDense([dimension1, dimension2],
comm=communicator)
parallel_matrix.setFromOptions()
parallel_matrix.setUp()
return parallel_matrix
[docs]def writeDenseMatrix(output_file, data, communicator=None):
"""Write a Petsc dense matrix which format is defined by two files: output_file.dat and output_file.info.
:param str output_file: file name to be saved.
:param petsc matrix data: dense matrix to be saved.
:param str communicator: mpi communicator.
:return: None.
"""
if communicator is None:
communicator = PETSc.COMM_WORLD
viewer = PETSc.Viewer().createBinary(output_file, mode='w',
comm=communicator)
viewer.pushFormat(viewer.Format.NATIVE)
viewer(data)
return
[docs]def unitary_test():
"""Unitary test for parallel.py script."""
# ###############################################################
# ################ MAIN #################
# ###############################################################
if __name__ == '__main__':
# ---------------------------------------------------------------
# Run unitary test
# ---------------------------------------------------------------
unitary_test()
