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* Wrap ck host utitlies in CK namespace. The CK and CK-Tile source code bases are incompatible because CK is not properly using namespaces everywhere. In particular, we need to put hip_check_error in the ck namespace. Move all functions in include/ck_/host_utility that were in global namespace into the ck namespace. There may be additional namespace problems like this, and it's possible we'll have namespace clashes. But it is good design to properly guard our to code bases (CK and CKTile) so that they can both coexist. Moreover, estabilishing this compatiblity is essential if we are going to allow the builder to instantiate kernels from either template library. * Add using declarations to test code. After moving some of the untils into the ck namespace, most examples and a few tests had to be updated to recognize the new namespace declarations. We add using declarations to individual compute units for functions that were previously in the global namespace. * Add using declarations to client examples.
138 lines
6.0 KiB
C++
138 lines
6.0 KiB
C++
// SPDX-License-Identifier: MIT
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// Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved.
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#include <numeric>
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#include <cstdlib>
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#include <iostream>
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#include <initializer_list>
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#include <vector>
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#include <gtest/gtest.h>
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#include "ck/host_utility/kernel_launch.hpp"
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#include "ck/library/utility/device_memory.hpp"
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#include "ck/library/utility/check_err.hpp"
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#include "ck/utility/common_header.hpp"
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#include "ck/wrapper/layout.hpp"
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#include "ck/wrapper/tensor.hpp"
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#include "ck/wrapper/operations/copy.hpp"
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using ::ck::DeviceMem;
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// Test copy from Global to Global through LDS and VGPR
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template <typename InputTensor,
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typename OutputTensor,
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typename BlockShape,
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typename ThreadLayout,
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bool UseOptimizedCopy>
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__global__ void TestCopyDevice(const InputTensor input_tensor,
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OutputTensor output_tensor,
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const BlockShape tile_shape,
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const ThreadLayout thread_layout)
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{
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__shared__ ck::index_t p_shared[ck::wrapper::size(tile_shape)];
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const auto tensor_lds = ck::wrapper::make_tensor<ck::wrapper::MemoryTypeEnum::Lds>(
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p_shared, ck::wrapper::make_layout(tile_shape));
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const auto block_idxs =
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ck::make_tuple(static_cast<ck::index_t>(blockIdx.x), static_cast<ck::index_t>(blockIdx.y));
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// Get local tiles for global memory
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const auto input_local_tile =
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ck::wrapper::make_local_tile(input_tensor, tile_shape, block_idxs);
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const auto output_local_tile =
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ck::wrapper::make_local_tile(output_tensor, tile_shape, block_idxs);
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// Get partition per thread
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const auto input_local_partition =
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ck::wrapper::make_local_partition(input_local_tile, thread_layout, threadIdx.x);
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auto lds_local_partition =
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ck::wrapper::make_local_partition(tensor_lds, thread_layout, threadIdx.x);
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auto output_local_partition =
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ck::wrapper::make_local_partition(output_local_tile, thread_layout, threadIdx.x);
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// Allocate VGPR
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auto tensor_vgpr =
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ck::wrapper::make_register_tensor<ck::wrapper::MemoryTypeEnum::Vgpr, ck::index_t>(
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ck::wrapper::make_layout(shape(lds_local_partition)));
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// Perform copy
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if constexpr(UseOptimizedCopy)
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{
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using DimAccessOrder = ck::Tuple<ck::Number<1>, ck::Number<0>>;
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constexpr ck::index_t vector_dim = 0;
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constexpr ck::index_t scalar_per_vector = 2;
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ck::wrapper::copy<DimAccessOrder, vector_dim, scalar_per_vector>(input_local_partition,
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lds_local_partition);
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// TODO: Enable optimized copy for static buffers
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ck::wrapper::copy<DimAccessOrder, vector_dim, scalar_per_vector>(lds_local_partition,
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tensor_vgpr);
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ck::wrapper::copy<DimAccessOrder, vector_dim, scalar_per_vector>(tensor_vgpr,
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output_local_partition);
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}
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else
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{
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ck::wrapper::copy(input_local_partition, lds_local_partition);
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ck::wrapper::copy(lds_local_partition, tensor_vgpr);
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ck::wrapper::copy(tensor_vgpr, output_local_partition);
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}
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}
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template <bool UseOptimizedCopy>
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void PerformCopyGlobalToGlobalViaLDS()
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{
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const auto shape =
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ck::make_tuple(ck::make_tuple(ck::Number<2>{}, ck::Number<2>{}), ck::Number<256>{});
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const auto strides =
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ck::make_tuple(ck::make_tuple(ck::Number<1>{}, ck::Number<2>{}), ck::Number<4>{});
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const auto layout = ck::wrapper::make_layout(shape, strides);
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// 0, 1, 2, ..., size(shape) - 1
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std::vector<ck::index_t> input_data(ck::wrapper::size(shape));
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std::iota(input_data.begin(), input_data.end(), 0);
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// Global memory buffers
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DeviceMem in_buf(ck::wrapper::size(layout) * sizeof(ck::index_t));
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DeviceMem out_buf(ck::wrapper::size(layout) * sizeof(ck::index_t));
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in_buf.ToDevice(input_data.data());
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out_buf.SetZero();
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// Create tensors for global memory
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const auto input_tensor_global = ck::wrapper::make_tensor<ck::wrapper::MemoryTypeEnum::Global>(
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static_cast<const ck::index_t*>(in_buf.GetDeviceBuffer()), layout);
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auto output_tensor_global = ck::wrapper::make_tensor<ck::wrapper::MemoryTypeEnum::Global>(
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static_cast<ck::index_t*>(out_buf.GetDeviceBuffer()), layout);
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const auto thread_layout =
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ck::wrapper::make_layout(ck::make_tuple(ck::Number<1>{}, ck::Number<32>{}));
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const auto tile_shape = ck::make_tuple(ck::Number<4>{}, ck::Number<64>{});
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const ck::index_t grid_size_x = ck::math::integer_divide_ceil(
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ck::wrapper::size<0>(input_tensor_global), ck::wrapper::size<0>(tile_shape));
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const ck::index_t grid_size_y = ck::math::integer_divide_ceil(
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ck::wrapper::size<1>(input_tensor_global), ck::wrapper::size<1>(tile_shape));
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const auto kernel = TestCopyDevice<decltype(input_tensor_global),
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decltype(output_tensor_global),
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decltype(tile_shape),
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decltype(thread_layout),
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UseOptimizedCopy>;
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launch_and_time_kernel(StreamConfig{},
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kernel,
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dim3(grid_size_x, grid_size_y, 1),
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dim3(ck::wrapper::size(thread_layout)),
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0,
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input_tensor_global,
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output_tensor_global,
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tile_shape,
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thread_layout);
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// Verify results
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std::vector<ck::index_t> output_data(ck::wrapper::size(shape));
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out_buf.FromDevice(output_data.data());
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EXPECT_TRUE(ck::utils::check_err(output_data, input_data));
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}
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TEST(TestCopyGlobalToGlobalViaLDS, GenericCopy) { PerformCopyGlobalToGlobalViaLDS<false>(); }
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TEST(TestCopyGlobalToGlobalViaLDS, OptimizedCopy) { PerformCopyGlobalToGlobalViaLDS<true>(); }
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