137 lines
5.5 KiB
Plaintext
137 lines
5.5 KiB
Plaintext
/***************************************************************************************************
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* Copyright (c) 2023 - 2023 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 "cute/numeric/math.hpp"
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namespace example
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{
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// Naive grid-stride loop implementation of gather
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template<typename Element, typename Func>
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__global__ void
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gather_kernel(Element const * __restrict__ input,
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Element * __restrict__ output,
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Func func,
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int num_elems_input,
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int num_elems_output,
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cutlass::FastDivmod stride_divmod)
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{
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Element const * input_b = input + blockIdx.z * num_elems_input;
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Element * output_b = output + blockIdx.z * num_elems_output;
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int tidx = threadIdx.x + blockIdx.x * blockDim.x;
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for (int k = tidx; k < num_elems_output; k += blockDim.x * gridDim.x) {
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int i,j;
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stride_divmod(j, i, k);
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output_b[k] = input_b[i + func(j) * stride_divmod.divisor];
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}
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}
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// Gather elements along strided dimension of the tensor according to given indices
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template<typename Element, typename Func>
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void
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gather(Element const * input,
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Element * output,
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Func func,
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int batch_size,
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int num_elems_input,
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int num_elems_output,
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int stride,
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cutlass::KernelHardwareInfo const& hw_info)
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{
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// Upcast to uint128_t data type
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int factor = 128 / cutlass::sizeof_bits<Element>::value;
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assert(stride % factor == 0);
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int stride_upcast = stride/factor;
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int num_elems_input_upcast = num_elems_input / factor;
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int num_elems_output_upcast = num_elems_output / factor;
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cutlass::FastDivmod stride_divmod(stride_upcast);
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dim3 blocks(hw_info.sm_count, 1, batch_size);
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gather_kernel<<<blocks, 1024>>>(reinterpret_cast<cute::uint128_t const *>(input),
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reinterpret_cast<cute::uint128_t *>(output),
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func,
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num_elems_input_upcast,
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num_elems_output_upcast,
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stride_divmod);
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}
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// Naive grid-stride loop implementation of scatter
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template<typename Element, typename Func>
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__global__ void
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scatter_kernel(Element const * __restrict__ input,
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Element * __restrict__ output,
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Func func,
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int num_elems_input,
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int num_elems_output,
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cutlass::FastDivmod stride_divmod)
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{
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Element const * input_b = input + blockIdx.z * num_elems_input;
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Element * output_b = output + blockIdx.z * num_elems_output;
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int tidx = threadIdx.x + blockIdx.x * blockDim.x;
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for (int k = tidx; k < num_elems_input; k += blockDim.x * gridDim.x) {
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int i,j;
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stride_divmod(j, i, k);
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output_b[i + func(j) * stride_divmod.divisor] = input_b[k];
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}
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}
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// Gather elements along strided dimension of the tensor according to given indices
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template<typename Element, typename Func>
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void
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scatter(Element const * input,
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Element * output,
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Func func,
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int batch_size,
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int num_elems_input,
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int num_elems_output,
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int stride,
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cutlass::KernelHardwareInfo const& hw_info)
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{
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// Upcast to uint128_t data type
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int factor = 128 / cutlass::sizeof_bits<Element>::value;
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assert(stride % factor == 0);
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int stride_upcast = stride/factor;
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int num_elems_input_upcast = num_elems_input / factor;
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int num_elems_output_upcast = num_elems_output / factor;
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cutlass::FastDivmod stride_divmod(stride_upcast);
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dim3 blocks(hw_info.sm_count, 1, batch_size);
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scatter_kernel<<<blocks, 1024>>>(reinterpret_cast<cute::uint128_t const *>(input),
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reinterpret_cast<cute::uint128_t *>(output),
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func,
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num_elems_input_upcast,
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num_elems_output_upcast,
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stride_divmod);
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}
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} // namespace example
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