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36 results

test_assignment_collection.py

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  • test_buffer_gpu.py 10.04 KiB
    """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)
            gpu_buffer_arr = gpuarray.zeros(np.prod(src_arr.shape), 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)