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镜像自地址 https://gitee.com/sunhf/gprMax.git 已同步 2025-08-07 04:56:51 +08:00
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Consolidate MPIFractalVolume implementation

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Nathan Mannall
2025-04-14 16:04:55 +01:00
父节点 ecac327840
当前提交 4570aa4d09
共有 1 个文件被更改，包括 86 次插入 和 155 次删除
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241
gprMax/fractals.py
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@@ -16,6 +16,7 @@
# You should have received a copy of the GNU General Public License
# along with gprMax. If not, see <http://www.gnu.org/licenses/>.
import logging
from typing import List, Optional, Tuple, Union
import numpy as np
@@ -33,6 +34,7 @@ from gprMax.utilities.mpi import Dim, Dir, get_relative_neighbour
from .cython.fractals_generate import generate_fractal2D, generate_fractal3D
from .utilities.utilities import round_value
logger = logging.getLogger(__name__)
np.seterr(divide="raise")
@@ -415,52 +417,13 @@ class MPIFractalVolume(FractalVolume):
for k in range(shape[2]):
fractalvolume_initial[:, j, k] = np.digitize(Aj[:, j, k], bins, right=True)
# Negative means send to negative neighbour
# Positive means receive from negative neighbour
negative_offset = np.where(self.start >= 0, 0, self.start + substart)
# Negative means send to positive neighbour
# Positive means receive from positive neighbour
positive_offset = self.upper_bound - (self.start + substart + shape)
print(
f"start: {self.start}, substart: {substart}, shape: {shape}, upper_bound = {self.upper_bound}"
)
print(f"negative_offset: {negative_offset}, positive_offset: {positive_offset}")
self.fractalvolume = np.zeros(
self.upper_bound - np.where(self.start < 0, 0, self.start),
dtype=config.sim_config.dtypes["float_or_double"],
)
requests: List[MPI.Request] = []
static_dimension = Dim(A.alignment)
dims = [dim for dim in Dim if dim != static_dimension]
dims = (dims[0], dims[1])
negative_offset = (negative_offset[dims[0]], negative_offset[dims[1]])
positive_offset = (positive_offset[dims[0]], positive_offset[dims[1]])
negative_spacing = (max(negative_offset[0], 0), max(negative_offset[1], 0))
positive_spacing = (max(positive_offset[0], 0), max(positive_offset[1], 0))
slices = [slice(None)] * 3
slices[dims[0]], slices[dims[1]] = self.create_slices(
negative_spacing, positive_spacing, None, None
)
negative_spacing = (abs(min(negative_offset[0], 0)), abs(min(negative_offset[1], 0)))
positive_spacing = (abs(min(positive_offset[0], 0)), abs(min(positive_offset[1], 0)))
initial_slices = [slice(None)] * 3
initial_slices[dims[0]], initial_slices[dims[1]] = self.create_slices(
negative_spacing, positive_spacing, None, None
)
self.fractalvolume[slices[0], slices[1], slices[2]] = fractalvolume_initial[
initial_slices[0], initial_slices[1], initial_slices[2]
]
# Negative means send to negative neighbour
# Positive means receive from negative neighbour
@@ -470,6 +433,30 @@ class MPIFractalVolume(FractalVolume):
# Positive means receive from positive neighbour
positive_offset = self.upper_bound - (self.start + substart + shape)
dirs = np.full(3, Dir.NONE)
shape = np.array(fractalvolume_initial.shape, dtype=np.int32)
starts, subshape = self.calculate_starts_and_subshape(
shape, -negative_offset, -positive_offset, dirs, sending=True
)
ends = starts + subshape
local_fractalvolume = fractalvolume_initial[
starts[0] : ends[0], starts[1] : ends[1], starts[2] : ends[2]
]
shape = np.array(self.fractalvolume.shape, dtype=np.int32)
starts, subshape = self.calculate_starts_and_subshape(
shape, negative_offset, positive_offset, dirs
)
ends = starts + subshape
self.fractalvolume[
starts[0] : ends[0], starts[1] : ends[1], starts[2] : ends[2]
] = local_fractalvolume
requests: List[MPI.Request] = []
sections = [
(Dir.NEG, Dir.NONE),
(Dir.POS, Dir.NONE),
@@ -482,25 +469,42 @@ class MPIFractalVolume(FractalVolume):
]
for section in sections:
dirs = np.full(3, Dir.NONE)
dirs[dims[0]] = section[0]
dirs[dims[1]] = section[1]
rank = get_relative_neighbour(self.comm, dirs)
self.check_send(
fractalvolume_initial,
negative_offset,
positive_offset,
dirs,
)
if rank == -1:
continue
request = self.check_receive(
self.fractalvolume,
negative_offset,
positive_offset,
dirs,
)
# Check if any data to send
if all(
np.logical_or(
dirs == Dir.NONE,
np.where(dirs == Dir.NEG, negative_offset <= 0, positive_offset <= 0),
)
):
shape = np.array(fractalvolume_initial.shape, dtype=np.int32)
mpi_type = self.create_mpi_type(
shape, -negative_offset, -positive_offset, dirs, sending=True
)
if request is not None:
logger.debug(f"Sending fractal volume to rank {rank}, MPI type={mpi_type.decode()}")
self.comm.Isend([fractalvolume_initial, mpi_type], rank)
# Check if any data to receive
if all(
np.logical_or(
dirs == Dir.NONE,
np.where(dirs == Dir.NEG, negative_offset > 0, positive_offset > 0),
)
):
shape = np.array(self.fractalvolume.shape, dtype=np.int32)
mpi_type = self.create_mpi_type(shape, negative_offset, positive_offset, dirs)
logger.debug(
f"Receiving fractal volume from rank {rank}, MPI type={mpi_type.decode()}"
)
request = self.comm.Irecv([self.fractalvolume, mpi_type], rank)
requests.append(request)
if len(requests) > 0:
@@ -516,104 +520,39 @@ class MPIFractalVolume(FractalVolume):
return True
def check_send(
def calculate_starts_and_subshape(
self,
array: npt.NDArray[np.float32],
shape: npt.NDArray[np.int32],
negative_offset: npt.NDArray[np.int32],
positive_offset: npt.NDArray[np.int32],
dirs: npt.NDArray[np.int32],
):
if all(
np.logical_or(
dirs == Dir.NONE,
np.where(dirs == Dir.NEG, negative_offset < 0, positive_offset < 0),
)
):
negative_spacing = np.where(
dirs == Dir.NONE,
np.maximum(-negative_offset, 0),
np.abs(negative_offset),
)
positive_spacing = np.where(
dirs == Dir.NONE,
np.maximum(-positive_offset, 0),
np.abs(positive_offset),
)
rank = get_relative_neighbour(self.comm, dirs)
shape = np.array(array.shape, dtype=np.int32)
mpi_type = self.create_mpi_type(
shape, negative_spacing, positive_spacing, dirs, sending=True
)
self.comm.Isend([array, mpi_type], rank)
def check_receive(
self,
array,
negative_offset: npt.NDArray[np.int32],
positive_offset: npt.NDArray[np.int32],
dirs: npt.NDArray[np.int32],
) -> Optional[MPI.Request]:
if all(
np.logical_or(
dirs == Dir.NONE,
np.where(dirs == Dir.NEG, negative_offset > 0, positive_offset > 0),
)
):
negative_spacing = np.where(
dirs == Dir.NONE,
np.maximum(negative_offset, 0),
np.abs(negative_offset),
)
positive_spacing = np.where(
dirs == Dir.NONE,
np.maximum(positive_offset, 0),
np.abs(positive_offset),
)
rank = get_relative_neighbour(self.comm, dirs)
shape = np.array(array.shape, dtype=np.int32)
mpi_type = self.create_mpi_type(shape, negative_spacing, positive_spacing, dirs)
return self.comm.Irecv([array, mpi_type], rank)
else:
return None
def create_slices(
self,
negative_offset: Tuple[int, int],
positive_offset: Tuple[int, int],
dir1: Optional[Dir],
dir2: Optional[Dir],
sending: bool = False,
) -> Tuple[slice, slice]:
n1, n2 = negative_offset
p1, p2 = positive_offset
) -> Tuple[npt.NDArray[np.int32], npt.NDArray[np.int32]]:
negative_offset = np.where(
dirs == Dir.NONE,
np.maximum(negative_offset, 0),
np.abs(negative_offset),
)
if dir1 == Dir.NEG:
slice1 = slice(n1 + sending)
elif dir1 == Dir.POS:
slice1 = slice(-p1 - sending, None)
elif p1 != 0:
slice1 = slice(n1, -p1)
else:
slice1 = slice(n1, None)
positive_offset = np.where(
dirs == Dir.NONE,
np.maximum(positive_offset, 0),
np.abs(positive_offset),
)
if dir2 == Dir.NEG:
slice2 = slice(n2 + sending)
elif dir2 == Dir.POS:
slice2 = slice(-p2 - sending, None)
elif p2 != 0:
slice2 = slice(n2, -p2)
else:
slice2 = slice(n2, None)
starts = np.select(
[dirs == Dir.NEG, dirs == Dir.POS],
[0, shape - positive_offset - sending],
default=negative_offset,
)
return slice1, slice2
subshape = np.select(
[dirs == Dir.NEG, dirs == Dir.POS],
[negative_offset + sending, positive_offset + sending],
default=shape - negative_offset - positive_offset,
)
return starts, subshape
def create_mpi_type(
self,
@@ -623,19 +562,11 @@ class MPIFractalVolume(FractalVolume):
dirs: npt.NDArray[np.int32],
sending: bool = False,
) -> MPI.Datatype:
starts = np.select(
[dirs == Dir.NEG, dirs == Dir.POS],
[0, shape - positive_offset - sending],
default=negative_offset,
).tolist()
starts, subshape = self.calculate_starts_and_subshape(
shape, negative_offset, positive_offset, dirs, sending
)
subshape = np.select(
[dirs == Dir.NEG, dirs == Dir.POS],
[negative_offset + sending, positive_offset + sending],
default=shape - negative_offset - positive_offset,
).tolist()
mpi_type = MPI.FLOAT.Create_subarray(shape.tolist(), subshape, starts)
mpi_type = MPI.FLOAT.Create_subarray(shape.tolist(), subshape.tolist(), starts.tolist())
mpi_type.Commit()
return mpi_type