"""Tests for the (un)packing (from)to buffers on a CUDA GPU.""" import numpy as np import pytest from pystencils import Assignment, Field, FieldType from pystencils.field import create_numpy_array_with_layout, layout_string_to_tuple from pystencils.gpucuda import create_cuda_kernel, make_python_function 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 pycuda.autoinit import pycuda.gpuarray as gpuarray except ImportError: pass FIELD_SIZES = [(4, 3), (9, 3, 7)] def _generate_fields(dt=np.uint8, stencil_directions=1, layout='numpy'): pytest.importorskip('pycuda') 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 = gpuarray.to_gpu(src_arr) gpu_dst_arr = gpuarray.zeros_like(gpu_src_arr) size = int(np.prod(src_arr.shape)) gpu_buffer_arr = gpuarray.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} pack_code = create_cuda_kernel(pack_eqs, type_info=pack_types) pack_kernel = make_python_function(pack_code) 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} unpack_code = create_cuda_kernel(unpack_eqs, type_info=unpack_types) unpack_kernel = make_python_function(unpack_code) 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} pack_code = create_cuda_kernel(pack_eqs, type_info=pack_types) pack_kernel = make_python_function(pack_code) 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} unpack_code = create_cuda_kernel(unpack_eqs, type_info=unpack_types) unpack_kernel = make_python_function(unpack_code) 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} pack_code = create_cuda_kernel(pack_eqs, type_info=pack_types) pack_kernel = make_python_function(pack_code) 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} unpack_code = create_cuda_kernel(unpack_eqs, type_info=unpack_types) unpack_kernel = make_python_function(unpack_code) 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 the 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} pack_code = create_cuda_kernel(pack_eqs, type_info=pack_types) pack_kernel = make_python_function(pack_code) 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} unpack_code = create_cuda_kernel(unpack_eqs, type_info=unpack_types) unpack_kernel = make_python_function(unpack_code) 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} pack_code = create_cuda_kernel(pack_eqs, type_info=pack_types) pack_kernel = make_python_function(pack_code) 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} unpack_code = create_cuda_kernel(unpack_eqs, type_info=unpack_types) unpack_kernel = make_python_function(unpack_code) unpack_kernel(buffer=gpu_buffer_arr, dst_field=gpu_dst_arr)