Example #1
0
import cffi
import dolfinx
import numba
import numba.core.typing.cffi_utils as cffi_support
import numpy as np
import petsc4py.lib
import pytest
import ufl
from dolfinx.jit import dolfinx_pc
from mpi4py import MPI
from petsc4py import PETSc
from petsc4py import get_config as PETSc_get_config
from ufl import dx, inner

# Get details of PETSc install
petsc_dir = PETSc_get_config()['PETSC_DIR']
petsc_arch = petsc4py.lib.getPathArchPETSc()[1]


# Get PETSc int and scalar types
if np.dtype(PETSc.ScalarType).kind == 'c':
    complex = True
else:
    complex = False

scalar_size = np.dtype(PETSc.ScalarType).itemsize
index_size = np.dtype(PETSc.IntType).itemsize

if index_size == 8:
    c_int_t = "int64_t"
    ctypes_index = ctypes.c_int64
Example #2
0
def initialize_petsc() -> typing.Tuple[cffi.FFI, typing.Any]:
    """
    Initialize petsc and CFFI for usage in numba
    """
    # Get details of PETSc install
    petsc_dir = PETSc_get_config()['PETSC_DIR']
    petsc_arch = petsc4py.lib.getPathArchPETSc()[1]

    # Get PETSc int and scalar types
    cmplx = True if np.dtype(PETSc.ScalarType).kind == 'c' else False

    scalar_size = np.dtype(PETSc.ScalarType).itemsize
    index_size = np.dtype(PETSc.IntType).itemsize
    if index_size == 8:
        c_int_t = "int64_t"
        ctypes_index = ctypes.c_int64  # type: ignore
    elif index_size == 4:
        c_int_t = "int32_t"
        ctypes_index = ctypes.c_int32  # type: ignore
    else:
        raise RuntimeError(
            "Cannot translate PETSc index size into a C type, index_size: {}."
            .format(index_size))

    if cmplx and scalar_size == 16:
        c_scalar_t = "double _Complex"
        numba_scalar_t = numba.types.complex128
    elif cmplx and scalar_size == 8:
        c_scalar_t = "float _Complex"
        numba_scalar_t = numba.types.complex64
    elif not cmplx and scalar_size == 8:
        c_scalar_t = "double"
        numba_scalar_t = numba.types.float64
    elif not cmplx and scalar_size == 4:
        c_scalar_t = "float"
        numba_scalar_t = numba.types.float32
    else:
        raise RuntimeError(
            "Cannot translate PETSc scalar type to a C type, complex: {} size: {}."
            .format(complex, scalar_size))

    # Load PETSc library via ctypes
    petsc_lib_name = ctypes.util.find_library("petsc")
    if petsc_lib_name is not None:
        petsc_lib_ctypes = ctypes.CDLL(petsc_lib_name)
    else:
        try:
            petsc_lib_ctypes = ctypes.CDLL(os.path.join(
                petsc_dir, petsc_arch, "lib", "libpetsc.so"))
        except OSError:
            try:
                petsc_lib_ctypes = ctypes.CDLL(os.path.join(
                    petsc_dir, petsc_arch, "lib", "libpetsc.dylib"))
            except OSError:
                raise RuntimeError("Could not load PETSc library for CFFI (ABI mode).")

    # Get the PETSc MatSetValuesLocal function via ctypes
    MatSetValues_ctypes = petsc_lib_ctypes.MatSetValuesLocal
    MatSetValues_ctypes.argtypes = (ctypes.c_void_p, ctypes_index, ctypes.POINTER(
        ctypes_index), ctypes_index, ctypes.POINTER(ctypes_index),
        ctypes.c_void_p, ctypes.c_int)
    del petsc_lib_ctypes

    # CFFI - register complex types
    ffi = cffi.FFI()
    cffi_support.register_type(ffi.typeof(
        'double _Complex'), numba.types.complex128)
    cffi_support.register_type(ffi.typeof('float _Complex'), numba.types.complex64)

    # Get MatSetValuesLocal from PETSc available via cffi in ABI mode
    ffi.cdef("""int MatSetValuesLocal(void* mat, {0} nrow, const {0}* irow,
                {0} ncol, const {0}* icol, const {1}* y, int addv);
    """.format(c_int_t, c_scalar_t))

    if petsc_lib_name is not None:
        ffi.dlopen(petsc_lib_name)
    else:
        try:
            ffi.dlopen(os.path.join(petsc_dir, petsc_arch, "lib", "libpetsc.so"))
        except OSError:
            try:
                ffi.dlopen(os.path.join(petsc_dir, petsc_arch, "lib", "libpetsc.dylib"))
            except OSError:
                raise RuntimeError("Could not load PETSc library for CFFI (ABI mode).")

    # Make MatSetValuesLocal from PETSc available via cffi in API mode
    worker = os.getenv('ASSEMBLE_XDIST_WORKER', None)
    module_name = "_petsc_cffi_{}".format(worker)
    if MPI.COMM_WORLD.Get_rank() == 0:
        os.environ["CC"] = "mpicc"
        ffibuilder = cffi.FFI()
        ffibuilder.cdef("""
            typedef int... PetscInt;
            typedef ... PetscScalar;
            typedef int... InsertMode;
            int MatSetValuesLocal(void* mat, PetscInt nrow, const PetscInt* irow,
                                    PetscInt ncol, const PetscInt* icol,
                                    const PetscScalar* y, InsertMode addv);

        """)
        ffibuilder.set_source(module_name, """
            # include "petscmat.h"
        """,
                              libraries=['petsc'],
                              include_dirs=[os.path.join(petsc_dir, petsc_arch,
                                                         'include'),
                                            os.path.join(petsc_dir, 'include')],
                              library_dirs=[os.path.join(
                                  petsc_dir, petsc_arch, 'lib')],
                              extra_compile_args=[])

        # Build module in same directory as python script
        ffibuilder.compile(".", verbose=False)
    MPI.COMM_WORLD.Barrier()
    module = importlib.import_module(module_name, ".")

    cffi_support.register_module(module)

    MatSetValuesLocal_api = module.lib.MatSetValuesLocal

    cffi_support.register_type(module.ffi.typeof("PetscScalar"),
                               numba_scalar_t)
    return ffi, MatSetValuesLocal_api