111 lines
3.5 KiB
C++
111 lines
3.5 KiB
C++
/***************************************************************************************************
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* Copyright (c) 2023 - 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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#pragma once
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#include "cutlass/cutlass.h"
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#if defined(__CUDACC_RTC__)
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#include CUDA_STD_HEADER(type_traits)
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#else
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#include <type_traits>
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#endif
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#include <cute/config.hpp>
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#include <cute/tensor.hpp>
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namespace cute {
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//
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// A generic tiling of thread-value layouts
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//
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template <class Layout_TV_, // (tid,vid) -> coord [Need not be 2D...]
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class Tiler_MN_> // coord space
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struct TV_Tiler
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{
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using Tiler_MN = Tiler_MN_;
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using TiledLayout_TV = Layout_TV_;
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// Tile a tensor or a layout from shape
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// (M,N,...)
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// to shape
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// ((ThrV,FrgV),(RestM,RestN,...))
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// where
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// ThrV: The threads local to a tile.
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// FrgV: The values local to a tile.
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// RestM: The values tiled in M.
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// RestN: The values tiled in N.
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template <class Tensor>
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CUTE_HOST_DEVICE constexpr static
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auto
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apply(Tensor&& tensor)
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{
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// If Layout_TV and Tiler_MN were composable in general, then this won't be needed!
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// ((thr_id,val_id),(RestM,RestN,...))
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return zipped_divide(tensor, Tiler_MN{}).compose(TiledLayout_TV{}, _);
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}
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template <class SliceCoord>
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struct TV_Partitioner
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{
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SliceCoord coord_;
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template <class TargetTensor>
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CUTE_HOST_DEVICE
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auto
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partition(TargetTensor&& target) {
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Tensor thr_tensor = make_tensor(static_cast<TargetTensor&&>(target).data(), apply(target.layout()));
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return thr_tensor(coord_, repeat<rank_v<TargetTensor>>(_));
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}
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};
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template <class SliceCoord>
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CUTE_HOST_DEVICE static
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auto
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get_slice(SliceCoord const& coord)
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{
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return TV_Partitioner<SliceCoord>{coord};
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}
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};
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template <class Layout_TV,
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class Tiler_MN>
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CUTE_HOST_DEVICE
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auto
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make_tiler_impl(Layout_TV const&,
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Tiler_MN const&)
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{
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return TV_Tiler<Layout_TV, Tiler_MN>{};
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}
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}
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