test_buffer_gpu.py 14.46 KiB
"""Tests for the (un)packing (from)to buffers on a CUDA GPU."""
from dataclasses import replace
import numpy as np
import pytest
import pystencils
from pystencils import Assignment, Field, FieldType, Target, CreateKernelConfig, create_kernel, fields
from pystencils.bit_masks import flag_cond
from pystencils.field import create_numpy_array_with_layout, layout_string_to_tuple
from pystencils.slicing import (
add_ghost_layers, get_ghost_region_slice, get_slice_before_ghost_layer)
from pystencils.stencil import direction_string_to_offset
try:
# noinspection PyUnresolvedReferences
import cupy as cp
except ImportError:
pass
FIELD_SIZES = [(4, 3), (9, 3, 7)]
def _generate_fields(dt=np.uint8, stencil_directions=1, layout='numpy'):
pytest.importorskip('cupy')
field_sizes = FIELD_SIZES
if stencil_directions > 1:
field_sizes = [s + (stencil_directions,) for s in field_sizes]
fields = []
for size in field_sizes:
field_layout = layout_string_to_tuple(layout, len(size))
src_arr = create_numpy_array_with_layout(size, field_layout).astype(dt)
array_data = np.reshape(np.arange(1, int(np.prod(size)+1)), size)
# Use flat iterator to input data into the array
src_arr.flat = add_ghost_layers(array_data,
index_dimensions=1 if stencil_directions > 1 else 0).astype(dt).flat
gpu_src_arr = cp.asarray(src_arr)
gpu_dst_arr = cp.zeros_like(gpu_src_arr)
size = int(np.prod(src_arr.shape))
gpu_buffer_arr = cp.zeros(size, dtype=dt)
fields.append((src_arr, gpu_src_arr, gpu_dst_arr, gpu_buffer_arr))
return fields
def test_full_scalar_field():
"""Tests fully (un)packing a scalar field (from)to a GPU buffer."""
fields = _generate_fields()
for (src_arr, gpu_src_arr, gpu_dst_arr, gpu_buffer_arr) in fields:
src_field = Field.create_from_numpy_array("src_field", src_arr)
dst_field = Field.create_from_numpy_array("dst_field", src_arr)
buffer = Field.create_generic("buffer", spatial_dimensions=1,
field_type=FieldType.BUFFER, dtype=src_arr.dtype)
pack_eqs = [Assignment(buffer.center(), src_field.center())]
pack_types = {'src_field': gpu_src_arr.dtype, 'buffer': gpu_buffer_arr.dtype}
config = CreateKernelConfig(target=pystencils.Target.GPU, data_type=pack_types)
pack_ast = create_kernel(pack_eqs, config=config)
pack_kernel = pack_ast.compile()
pack_kernel(buffer=gpu_buffer_arr, src_field=gpu_src_arr)
unpack_eqs = [Assignment(dst_field.center(), buffer.center())]
unpack_types = {'dst_field': gpu_dst_arr.dtype, 'buffer': gpu_buffer_arr.dtype}
config = CreateKernelConfig(target=pystencils.Target.GPU, data_type=unpack_types)
unpack_ast = create_kernel(unpack_eqs, config=config)
unpack_kernel = unpack_ast.compile()
unpack_kernel(dst_field=gpu_dst_arr, buffer=gpu_buffer_arr)
dst_arr = gpu_dst_arr.get()
np.testing.assert_equal(src_arr, dst_arr)
def test_field_slice():
"""Tests (un)packing slices of a scalar field (from)to a buffer."""
fields = _generate_fields()
for d in ['N', 'S', 'NW', 'SW', 'TNW', 'B']:
for (src_arr, gpu_src_arr, gpu_dst_arr, gpu_buffer_arr) in fields:
# Extract slice from N direction of the field
slice_dir = direction_string_to_offset(d, dim=len(src_arr.shape))
pack_slice = get_slice_before_ghost_layer(slice_dir)
unpack_slice = get_ghost_region_slice(slice_dir)
src_field = Field.create_from_numpy_array("src_field", src_arr[pack_slice])
dst_field = Field.create_from_numpy_array("dst_field", src_arr[unpack_slice])
buffer = Field.create_generic("buffer", spatial_dimensions=1,
field_type=FieldType.BUFFER, dtype=src_arr.dtype)
pack_eqs = [Assignment(buffer.center(), src_field.center())]
pack_types = {'src_field': gpu_src_arr.dtype, 'buffer': gpu_buffer_arr.dtype}
config = CreateKernelConfig(target=pystencils.Target.GPU, data_type=pack_types)
pack_ast = create_kernel(pack_eqs, config=config)
pack_kernel = pack_ast.compile()
pack_kernel(buffer=gpu_buffer_arr, src_field=gpu_src_arr[pack_slice])
# Unpack into ghost layer of dst_field in N direction
unpack_eqs = [Assignment(dst_field.center(), buffer.center())]
unpack_types = {'dst_field': gpu_dst_arr.dtype, 'buffer': gpu_buffer_arr.dtype}
config = CreateKernelConfig(target=pystencils.Target.GPU, data_type=unpack_types)
unpack_ast = create_kernel(unpack_eqs, config=config)
unpack_kernel = unpack_ast.compile()
unpack_kernel(buffer=gpu_buffer_arr, dst_field=gpu_dst_arr[unpack_slice])
dst_arr = gpu_dst_arr.get()
np.testing.assert_equal(src_arr[pack_slice], dst_arr[unpack_slice])
def test_all_cell_values():
"""Tests (un)packing all cell values of the a field (from)to a buffer."""
num_cell_values = 7
fields = _generate_fields(stencil_directions=num_cell_values)
for (src_arr, gpu_src_arr, gpu_dst_arr, gpu_buffer_arr) in fields:
src_field = Field.create_from_numpy_array("src_field", gpu_src_arr, index_dimensions=1)
dst_field = Field.create_from_numpy_array("dst_field", gpu_src_arr, index_dimensions=1)
buffer = Field.create_generic("buffer", spatial_dimensions=1, index_dimensions=1,
field_type=FieldType.BUFFER, dtype=gpu_src_arr.dtype)
pack_eqs = []
# Since we are packing all cell values for all cells, then
# the buffer index is equivalent to the field index
for idx in range(num_cell_values):
eq = Assignment(buffer(idx), src_field(idx))
pack_eqs.append(eq)
pack_types = {'src_field': gpu_src_arr.dtype, 'buffer': gpu_buffer_arr.dtype}
config = CreateKernelConfig(target=pystencils.Target.GPU, data_type=pack_types)
pack_code = create_kernel(pack_eqs, config=config)
pack_kernel = pack_code.compile()
pack_kernel(buffer=gpu_buffer_arr, src_field=gpu_src_arr)
unpack_eqs = []
for idx in range(num_cell_values):
eq = Assignment(dst_field(idx), buffer(idx))
unpack_eqs.append(eq)
unpack_types = {'dst_field': gpu_dst_arr.dtype, 'buffer': gpu_buffer_arr.dtype}
config = CreateKernelConfig(target=pystencils.Target.GPU, data_type=unpack_types)
unpack_ast = create_kernel(unpack_eqs, config=config)
unpack_kernel = unpack_ast.compile()
unpack_kernel(buffer=gpu_buffer_arr, dst_field=gpu_dst_arr)
dst_arr = gpu_dst_arr.get()
np.testing.assert_equal(src_arr, dst_arr)
def test_subset_cell_values():
"""Tests (un)packing a subset of cell values of a field (from)to a buffer."""
num_cell_values = 7
# Cell indices of the field to be (un)packed (from)to the buffer
cell_indices = [1, 3, 5, 6]
fields = _generate_fields(stencil_directions=num_cell_values)
for (src_arr, gpu_src_arr, gpu_dst_arr, gpu_buffer_arr) in fields:
src_field = Field.create_from_numpy_array("src_field", gpu_src_arr, index_dimensions=1)
dst_field = Field.create_from_numpy_array("dst_field", gpu_src_arr, index_dimensions=1)
buffer = Field.create_generic("buffer", spatial_dimensions=1, index_dimensions=1,
field_type=FieldType.BUFFER, dtype=gpu_src_arr.dtype)
pack_eqs = []
# Since we are packing all cell values for all cells, then
# the buffer index is equivalent to the field index
for buffer_idx, cell_idx in enumerate(cell_indices):
eq = Assignment(buffer(buffer_idx), src_field(cell_idx))
pack_eqs.append(eq)
pack_types = {'src_field': gpu_src_arr.dtype, 'buffer': gpu_buffer_arr.dtype}
config = CreateKernelConfig(target=pystencils.Target.GPU, data_type=pack_types)
pack_ast = create_kernel(pack_eqs, config=config)
pack_kernel = pack_ast.compile()
pack_kernel(buffer=gpu_buffer_arr, src_field=gpu_src_arr)
unpack_eqs = []
for buffer_idx, cell_idx in enumerate(cell_indices):
eq = Assignment(dst_field(cell_idx), buffer(buffer_idx))
unpack_eqs.append(eq)
unpack_types = {'dst_field': gpu_dst_arr.dtype, 'buffer': gpu_buffer_arr.dtype}
config = CreateKernelConfig(target=pystencils.Target.GPU, data_type=unpack_types)
unpack_ast = create_kernel(unpack_eqs, config=config)
unpack_kernel = unpack_ast.compile()
unpack_kernel(buffer=gpu_buffer_arr, dst_field=gpu_dst_arr)
dst_arr = gpu_dst_arr.get()
mask_arr = np.ma.masked_where((src_arr - dst_arr) != 0, src_arr)
np.testing.assert_equal(dst_arr, mask_arr.filled(int(0)))
def test_field_layouts():
num_cell_values = 7
for layout_str in ['numpy', 'fzyx', 'zyxf', 'reverse_numpy']:
fields = _generate_fields(stencil_directions=num_cell_values, layout=layout_str)
for (src_arr, gpu_src_arr, gpu_dst_arr, gpu_buffer_arr) in fields:
src_field = Field.create_from_numpy_array("src_field", gpu_src_arr, index_dimensions=1)
dst_field = Field.create_from_numpy_array("dst_field", gpu_src_arr, index_dimensions=1)
buffer = Field.create_generic("buffer", spatial_dimensions=1, index_dimensions=1,
field_type=FieldType.BUFFER, dtype=src_arr.dtype)
pack_eqs = []
# Since we are packing all cell values for all cells, then
# the buffer index is equivalent to the field index
for idx in range(num_cell_values):
eq = Assignment(buffer(idx), src_field(idx))
pack_eqs.append(eq)
pack_types = {'src_field': gpu_src_arr.dtype, 'buffer': gpu_buffer_arr.dtype}
config = CreateKernelConfig(target=pystencils.Target.GPU, data_type=pack_types)
pack_ast = create_kernel(pack_eqs, config=config)
pack_kernel = pack_ast.compile()
pack_kernel(buffer=gpu_buffer_arr, src_field=gpu_src_arr)
unpack_eqs = []
for idx in range(num_cell_values):
eq = Assignment(dst_field(idx), buffer(idx))
unpack_eqs.append(eq)
unpack_types = {'dst_field': gpu_dst_arr.dtype, 'buffer': gpu_buffer_arr.dtype}
config = CreateKernelConfig(target=pystencils.Target.GPU, data_type=unpack_types)
unpack_ast = create_kernel(unpack_eqs, config=config)
unpack_kernel = unpack_ast.compile()
unpack_kernel(buffer=gpu_buffer_arr, dst_field=gpu_dst_arr)
def test_buffer_indexing():
src_field, dst_field = fields(f'pdfs_src(19), pdfs_dst(19) :double[3D]')
mask_field = fields(f'mask : uint32 [3D]')
buffer = Field.create_generic('buffer', spatial_dimensions=1, field_type=FieldType.BUFFER,
dtype="float64",
index_shape=(19,))
src_field_size = src_field.spatial_shape
mask_field_size = mask_field.spatial_shape
up = Assignment(buffer(0), flag_cond(1, mask_field.center, src_field[0, 1, 0](1)))
iteration_slice = tuple(slice(None, None, 2) for _ in range(3))
config = CreateKernelConfig(target=Target.GPU)
config = replace(config, iteration_slice=iteration_slice, ghost_layers=0)
ast = create_kernel(up, config=config)
parameters = ast.get_parameters()
spatial_shape_symbols = [p.symbol for p in parameters if p.is_field_shape]
# The loop counters as well as the resolved field access should depend on one common spatial shape
if spatial_shape_symbols[0] in mask_field_size:
for s in spatial_shape_symbols:
assert s in mask_field_size
if spatial_shape_symbols[0] in src_field_size:
for s in spatial_shape_symbols:
assert s in src_field_size
assert len(spatial_shape_symbols) <= 3
def test_iteration_slices():
num_cell_values = 19
dt = np.uint64
fields = _generate_fields(dt=dt, stencil_directions=num_cell_values)
for (src_arr, gpu_src_arr, gpu_dst_arr, gpu_buffer_arr) in fields:
src_field = Field.create_from_numpy_array("src_field", gpu_src_arr, index_dimensions=1)
dst_field = Field.create_from_numpy_array("dst_field", gpu_src_arr, index_dimensions=1)
buffer = Field.create_generic("buffer", spatial_dimensions=1, index_dimensions=1,
field_type=FieldType.BUFFER, dtype=src_arr.dtype)
pack_eqs = []
# Since we are packing all cell values for all cells, then
# the buffer index is equivalent to the field index
for idx in range(num_cell_values):
eq = Assignment(buffer(idx), src_field(idx))
pack_eqs.append(eq)
dim = src_field.spatial_dimensions
# Pack only the leftmost slice, only every second cell
pack_slice = (slice(None, None, 2),) * (dim - 1) + (0,)
# Fill the entire array with data
src_arr[(slice(None, None, 1),) * dim] = np.arange(num_cell_values)
gpu_src_arr.set(src_arr)
gpu_dst_arr.fill(0)
config = CreateKernelConfig(target=Target.GPU, iteration_slice=pack_slice,
data_type={'src_field': gpu_src_arr.dtype, 'buffer': gpu_buffer_arr.dtype})
pack_code = create_kernel(pack_eqs, config=config)
pack_kernel = pack_code.compile()
pack_kernel(buffer=gpu_buffer_arr, src_field=gpu_src_arr)
unpack_eqs = []
for idx in range(num_cell_values):
eq = Assignment(dst_field(idx), buffer(idx))
unpack_eqs.append(eq)
config = CreateKernelConfig(target=Target.GPU, iteration_slice=pack_slice,
data_type={'dst_field': gpu_dst_arr.dtype, 'buffer': gpu_buffer_arr.dtype})
unpack_code = create_kernel(unpack_eqs, config=config)
unpack_kernel = unpack_code.compile()
unpack_kernel(buffer=gpu_buffer_arr, dst_field=gpu_dst_arr)
dst_arr = gpu_dst_arr.get()
src_arr = gpu_src_arr.get()
# Check if only every second entry of the leftmost slice has been copied
np.testing.assert_equal(dst_arr[pack_slice], src_arr[pack_slice])
np.testing.assert_equal(dst_arr[(slice(1, None, 2),) * (dim - 1) + (0,)], 0)
np.testing.assert_equal(dst_arr[(slice(None, None, 1),) * (dim - 1) + (slice(1, None),)], 0)