Exemplo n.º 1
0
    def _specialize_iet(cls, graph, **kwargs):
        options = kwargs['options']
        platform = kwargs['platform']

        # Flush denormal numbers
        avoid_denormals(graph)

        # Distributed-memory parallelism
        optimize_halospots(graph)
        if options['mpi']:
            mpiize(graph, mode=options['mpi'])

        # Lower IncrDimensions so that blocks of arbitrary shape may be used
        relax_incr_dimensions(graph, counter=generator())

        # SIMD-level parallelism
        ompizer = Ompizer()
        ompizer.make_simd(graph, simd_reg_size=platform.simd_reg_size)

        # Shared-memory parallelism
        ompizer.make_parallel(graph)

        # Misc optimizations
        hoist_prodders(graph)

        # Symbol definitions
        data_manager = DataManager()
        data_manager.place_definitions(graph)
        data_manager.place_casts(graph)

        return graph
Exemplo n.º 2
0
    def _specialize_iet(cls, graph, **kwargs):
        options = kwargs['options']
        platform = kwargs['platform']

        # Flush denormal numbers
        avoid_denormals(graph)

        # Distributed-memory parallelism
        optimize_halospots(graph)
        if options['mpi']:
            mpiize(graph, mode=options['mpi'])

        # Tiling
        blocker = Blocker(options['blockinner'], options['blocklevels']
                          or cls.BLOCK_LEVELS)
        blocker.make_blocking(graph)

        # Shared-memory and SIMD-level parallelism
        ompizer = Ompizer()
        ompizer.make_simd(graph, simd_reg_size=platform.simd_reg_size)
        if options['openmp']:
            ompizer.make_parallel(graph)

        # Misc optimizations
        hoist_prodders(graph)

        # Symbol definitions
        data_manager = DataManager()
        data_manager.place_definitions(graph)
        data_manager.place_casts(graph)

        return graph
Exemplo n.º 3
0
    def _specialize_iet(cls, graph, **kwargs):
        options = kwargs['options']
        platform = kwargs['platform']
        sregistry = kwargs['sregistry']

        # Distributed-memory parallelism
        optimize_halospots(graph)
        if options['mpi']:
            mpiize(graph, mode=options['mpi'])

        # Lower IncrDimensions so that blocks of arbitrary shape may be used
        relax_incr_dimensions(graph, sregistry=sregistry)

        # SIMD-level parallelism
        ompizer = Ompizer(sregistry, options)
        ompizer.make_simd(graph, simd_reg_size=platform.simd_reg_size)

        # Shared-memory parallelism
        ompizer.make_parallel(graph)

        # Misc optimizations
        hoist_prodders(graph)

        # Symbol definitions
        DataManager(sregistry).process(graph)

        return graph
Exemplo n.º 4
0
    def _specialize_iet(cls, graph, **kwargs):
        options = kwargs['options']
        sregistry = kwargs['sregistry']

        # Distributed-memory parallelism
        if options['mpi']:
            mpiize(graph, mode=options['mpi'])

        # Shared-memory parallelism
        if options['openmp']:
            ompizer = Ompizer(sregistry, options)
            ompizer.make_parallel(graph)

        # Symbol definitions
        DataManager(sregistry).process(graph)

        return graph
Exemplo n.º 5
0
    def _specialize_iet(cls, graph, **kwargs):
        options = kwargs['options']

        # Distributed-memory parallelism
        if options['mpi']:
            mpiize(graph, mode=options['mpi'])

        # Shared-memory parallelism
        if options['openmp']:
            ompizer = Ompizer()
            ompizer.make_parallel(graph)

        # Symbol definitions
        data_manager = DataManager()
        data_manager.place_definitions(graph)
        data_manager.place_casts(graph)

        return graph