b78588d163
* CUTLASS 3.7 * clean up changelog --------- Co-authored-by: yuzhai <yuzhai@nvidia.com> Co-authored-by: Haicheng Wu <haichengw@nvidia.com>
85 lines
3.5 KiB
C++
85 lines
3.5 KiB
C++
/******************************************************************************
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* Copyright (c) 2024 - 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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* SPDX-License-Identifier: BSD-3-Clause
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions are met:
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*
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* 1. Redistributions of source code must retain the above copyright notice, this
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* list of conditions and the following disclaimer.
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*
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* 2. Redistributions in binary form must reproduce the above copyright notice,
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* this list of conditions and the following disclaimer in the documentation
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* and/or other materials provided with the distribution.
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*
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* 3. Neither the name of the copyright holder nor the names of its
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* contributors may be used to endorse or promote products derived from
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* this software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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* DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
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* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
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* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
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* SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
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* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*
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******************************************************************************/
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/*! \file
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\brief generic device-to-device data movement kernel based for CuTe tensors.
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NOTE: this kernel assigns one element copy to every thread, and is by no means
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an efficient way of copying tensors. It should only be used for convenience in
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reference checks.
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*/
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#pragma once
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#include "cute/layout.hpp"
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#include "cute/tensor.hpp"
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#include "cutlass/cutlass.h"
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#include "cutlass/cuda_host_adapter.hpp"
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namespace cutlass {
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template <typename TensorSource, typename TensorDestination>
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void device_copy(TensorSource tensor_source,
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TensorDestination tensor_destination,
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cudaStream_t stream);
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template <typename TensorSource, typename TensorDestination>
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__global__ void device_copy_kernel(TensorSource const tensor_source,
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TensorDestination tensor_destination) {
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auto linear_idx = blockIdx.x * blockDim.x + threadIdx.x;
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using ElementSrc = typename TensorSource::value_type;
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using ElementDst = typename TensorDestination::value_type;
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NumericConverter<ElementDst, ElementSrc> converter;
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if (linear_idx < size(tensor_source)) {
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tensor_destination(linear_idx) = converter(tensor_source(linear_idx));
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}
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}
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template <typename TensorSource, typename TensorDestination>
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void device_copy(TensorSource tensor_source,
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TensorDestination tensor_destination,
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cudaStream_t stream) {
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assert(tensor_source.size() == tensor_destination.size());
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auto numel = tensor_source.size();
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static constexpr int NumThreads = 128;
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auto grid_size = cute::ceil_div(numel, NumThreads);
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dim3 grid(grid_size);
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dim3 block(NumThreads);
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device_copy_kernel<<<grid, block, 0, stream>>>(tensor_source, tensor_destination);
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}
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} //namespace cutlass
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