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https://github.com/ROCm/composable_kernel.git
synced 2026-05-02 12:41:26 +00:00
[Ck_tile] smoothquant (#1617)
* fix compile error * fix typo of padding * Add smoothquant op * Add smoothquant instance library * refine type * add test script * Re-generate smoothquant.hpp * Always use 'current year' in copyright * use Generic2dBlockShape instead * Add vector = 8 instance back * Find exe path automatically * Simplify the api condition * Remove debugging code * update year * Add blank line between function declaration * explicitly cast return value to dim3 * refine return value * Fix default warmup and repeat value * Add comment * refactor sommthquant cmake * Add README * Fix typo --------- Co-authored-by: Po Yen, Chen <PoYen.Chen@amd.com>
This commit is contained in:
rocking
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
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#pragma once
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#include "ck_tile/core.hpp"
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#include "ck_tile/ops/reduce/block/block_reduce2d_problem.hpp"
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#include "ck_tile/ops/reduce/block/block_reduce2d.hpp"
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namespace ck_tile {
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struct SmoothquantPipelineDefaultPolicy
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{
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template <typename Problem>
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CK_TILE_DEVICE static constexpr auto MakeXBlockTileDistribution()
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{
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using S = typename Problem::BlockShape;
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return make_static_tile_distribution(
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tile_distribution_encoding<
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sequence<>,
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tuple<sequence<S::Repeat_M, S::WarpPerBlock_M, S::ThreadPerWarp_M, S::Vector_M>,
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sequence<S::Repeat_N, S::WarpPerBlock_N, S::ThreadPerWarp_N, S::Vector_N>>,
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tuple<sequence<1, 2>, sequence<1, 2>>,
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tuple<sequence<1, 1>, sequence<2, 2>>,
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sequence<1, 1, 2, 2>,
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sequence<0, 3, 0, 3>>{});
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}
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template <typename Problem>
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CK_TILE_DEVICE static constexpr auto MakeXScaleBlockTileDistribution()
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{
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using S = typename Problem::BlockShape;
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return make_static_tile_distribution(
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tile_distribution_encoding<
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sequence<S::WarpPerBlock_M, S::ThreadPerWarp_M>,
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tuple<sequence<S::Repeat_N, S::WarpPerBlock_N, S::ThreadPerWarp_N, S::Vector_N>>,
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tuple<sequence<0, 1>, sequence<0, 1>>,
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tuple<sequence<0, 1>, sequence<1, 2>>,
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sequence<1, 1>,
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sequence<0, 3>>{});
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}
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template <typename Problem>
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CK_TILE_HOST_DEVICE static constexpr auto GetBlockReduce2d()
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{
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using P_ = BlockReduce2dProblem<typename Problem::ComputeDataType,
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typename Problem::ComputeDataType,
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typename Problem::BlockShape>;
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return BlockReduce2d<P_>{};
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}
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template <typename Problem>
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CK_TILE_HOST_DEVICE static constexpr auto GetBlockReduce2dSync()
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{
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using P_ = BlockReduce2dProblem<typename Problem::ComputeDataType,
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typename Problem::ComputeDataType,
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typename Problem::BlockShape>;
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return BlockReduce2dSync<P_>{};
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}
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template <typename Problem>
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CK_TILE_HOST_DEVICE static constexpr auto GetBlockReduce2dCrossWarpSync()
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{
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using P_ = BlockReduce2dProblem<typename Problem::ComputeDataType,
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typename Problem::ComputeDataType,
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typename Problem::BlockShape>;
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return BlockReduce2dCrossWarpSync<P_>{};
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}
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template <typename Problem>
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CK_TILE_HOST_DEVICE static constexpr index_t GetSmemSize()
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{
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if constexpr(Problem::kNeedCrossWarpSync)
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{
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using P_ = BlockReduce2dProblem<typename Problem::XDataType,
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typename Problem::ComputeDataType,
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typename Problem::BlockShape>;
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using block_reduce2d = BlockReduce2d<P_>;
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using x_block_tile =
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decltype(make_static_distributed_tensor<typename Problem::XDataType>(
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MakeXBlockTileDistribution<Problem>()));
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using y_block_tile = decltype(block_reduce2d::template MakeYBlockTile<x_block_tile>());
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return GetBlockReduce2dCrossWarpSync<Problem>().template GetSmemSize<y_block_tile>();
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}
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else
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{
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return 1; // zero size arrays are an extension
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}
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}
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};
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} // namespace ck_tile
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
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#pragma once
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#include "ck_tile/core.hpp"
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#include "ck_tile/ops/rmsnorm2d/pipeline/rmsnorm2d_fwd_pipeline_default_policy.hpp"
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#include <string>
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#include <type_traits>
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namespace ck_tile {
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template <typename Problem_, typename Policy_ = SmoothquantPipelineDefaultPolicy>
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struct SmoothquantPipelineOnePass
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{
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using Problem = ck_tile::remove_cvref_t<Problem_>;
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using Policy = ck_tile::remove_cvref_t<Policy_>;
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using XDataType = ck_tile::remove_cvref_t<typename Problem::XDataType>;
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using XScaleDataType = ck_tile::remove_cvref_t<typename Problem::XScaleDataType>;
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using ComputeDataType = ck_tile::remove_cvref_t<typename Problem::ComputeDataType>;
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using QYDataType = ck_tile::remove_cvref_t<typename Problem::QYDataType>;
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using YScaleDataType = ck_tile::remove_cvref_t<typename Problem::YScaleDataType>;
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static constexpr bool kNeedCrossWarpSync = Problem::kNeedCrossWarpSync;
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static constexpr bool kPadM = false; // TODO - BlockSmoothquantProblem::kPadM
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static constexpr bool kPadN = Problem::kPadN;
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static constexpr const char* name = []() {
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if constexpr(kNeedCrossWarpSync)
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return "bpr_op"; // block per row
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else
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return "wpr_op"; // warp per row
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}();
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CK_TILE_HOST_DEVICE static constexpr index_t GetSmemSize()
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{
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return Policy::template GetSmemSize<Problem>();
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}
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template <typename XWindow, typename XScaleWindow, typename QYWindow, typename YScaleWindow>
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CK_TILE_DEVICE auto operator()(const XWindow& x_window_,
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const XScaleWindow& xscale_window_,
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YScaleWindow& yscale_window,
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QYWindow& qy_window,
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ck_tile::index_t,
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void* smem) const
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{
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auto x_window =
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make_tile_window(x_window_, Policy::template MakeXBlockTileDistribution<Problem>());
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auto xscale_window = make_tile_window(
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xscale_window_, Policy::template MakeXScaleBlockTileDistribution<Problem>());
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auto reduce_absmax_func = ReduceOp::AbsMax{};
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auto reduce_max_func = ReduceOp::Max{};
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auto block_reduce2d = Policy::template GetBlockReduce2d<Problem>();
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auto block_reduce2d_sync = Policy::template GetBlockReduce2dSync<Problem>();
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auto block_reduce2d_cross_warp_sync =
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Policy::template GetBlockReduce2dCrossWarpSync<Problem>();
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const auto x = load_tile(x_window);
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const auto xscale = load_tile(xscale_window);
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auto y = tile_elementwise_in(
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[&](const auto& a, const auto& b) {
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return type_convert<ComputeDataType>(a) * type_convert<ComputeDataType>(b);
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},
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x,
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xscale);
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// compute absmax, cross-lane->cross-warp
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auto absmax = block_reduce2d(
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y, reduce_absmax_func.GetIdentityValue<ComputeDataType>(), reduce_absmax_func);
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block_reduce2d_sync(absmax, reduce_max_func);
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block_reduce2d_cross_warp_sync(absmax, smem, reduce_max_func);
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// ex: yscale = absmax / 127 if int8
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auto yscale = tile_elementwise_in(
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[&](const auto& v_) {
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return v_ / type_convert<ComputeDataType>(numeric<QYDataType>::max());
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},
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absmax);
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store_tile(yscale_window, cast_tile<YScaleDataType>(yscale));
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// quantize y to qy
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auto qy = make_static_distributed_tensor<QYDataType>(y.get_tile_distribution());
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sweep_tile(qy, [&](auto idx) {
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constexpr auto i_idx = make_tuple(idx[number<0>{}]);
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auto qy_ = y[idx] / yscale[i_idx];
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qy(idx) = saturates<QYDataType>{}(qy_);
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});
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store_tile(qy_window, qy);
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}
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};
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} // namespace ck_tile
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
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#pragma once
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#include "ck_tile/core/utility/type_traits.hpp"
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namespace ck_tile {
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// Y = X * XScale, QY = RowwiseDynamicQuant(Y) = SaturateCast(Y / YScale)
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template <typename XDataType_,
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typename XScaleDataType_,
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typename ComputeDataType_,
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typename YScaleDataType_,
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typename QYDataType_,
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typename BlockShape_,
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bool kPadN_,
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bool kTwoPass_>
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struct SmoothquantPipelineProblem
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{
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using XDataType = remove_cvref_t<XDataType_>;
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using XScaleDataType = remove_cvref_t<XScaleDataType_>;
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using ComputeDataType = remove_cvref_t<ComputeDataType_>;
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using YScaleDataType = remove_cvref_t<YScaleDataType_>;
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using QYDataType = remove_cvref_t<QYDataType_>;
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using BlockShape = remove_cvref_t<BlockShape_>;
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static constexpr bool kNeedCrossLaneSync = BlockShape::ThreadPerWarp_N > 1;
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static constexpr bool kNeedCrossWarpSync = BlockShape::WarpPerBlock_N > 1;
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static constexpr bool kPadN = kPadN_;
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static constexpr bool kTwoPass = kTwoPass_;
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};
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} // namespace ck_tile
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
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#pragma once
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#include "ck_tile/core.hpp"
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#include "ck_tile/ops/rmsnorm2d/pipeline/rmsnorm2d_fwd_pipeline_default_policy.hpp"
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#include <string>
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#include <type_traits>
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namespace ck_tile {
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template <typename Problem_, typename Policy_ = SmoothquantPipelineDefaultPolicy>
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struct SmoothquantPipelineTwoPass
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{
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using Problem = ck_tile::remove_cvref_t<Problem_>;
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using Policy = ck_tile::remove_cvref_t<Policy_>;
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using XDataType = ck_tile::remove_cvref_t<typename Problem::XDataType>;
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using XScaleDataType = ck_tile::remove_cvref_t<typename Problem::XScaleDataType>;
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using ComputeDataType = ck_tile::remove_cvref_t<typename Problem::ComputeDataType>;
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using QYDataType = ck_tile::remove_cvref_t<typename Problem::QYDataType>;
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using YScaleDataType = ck_tile::remove_cvref_t<typename Problem::YScaleDataType>;
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static constexpr bool kNeedCrossWarpSync = Problem::kNeedCrossWarpSync;
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static constexpr bool kPadM = false; // TODO - BlockSmoothquantProblem::kPadM
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static constexpr bool kPadN = Problem::kPadN;
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static constexpr const char* name = []() {
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if constexpr(kNeedCrossWarpSync)
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return "bpr_tp"; // block per row
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else
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return "wpr_tp"; // warp per row
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}();
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CK_TILE_HOST_DEVICE static constexpr index_t GetSmemSize()
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{
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return Policy::template GetSmemSize<Problem>();
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}
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template <typename XWindow, typename XScaleWindow, typename QYWindow, typename YScaleWindow>
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CK_TILE_DEVICE auto operator()(const XWindow& x_window_,
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const XScaleWindow& xscale_window_,
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YScaleWindow& yscale_window,
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QYWindow& qy_window,
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ck_tile::index_t row_size,
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void* smem) const
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{
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auto x_window =
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make_tile_window(x_window_, Policy::template MakeXBlockTileDistribution<Problem>());
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auto xscale_window = make_tile_window(
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xscale_window_, Policy::template MakeXScaleBlockTileDistribution<Problem>());
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static constexpr index_t Block_N = Problem::BlockShape::Block_N;
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index_t num_n_tile_iteration =
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__builtin_amdgcn_readfirstlane(integer_divide_ceil(row_size, Block_N));
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auto reduce_absmax_func = ReduceOp::AbsMax{};
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auto reduce_max_func = ReduceOp::Max{};
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auto block_reduce2d = Policy::template GetBlockReduce2d<Problem>();
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auto block_reduce2d_sync = Policy::template GetBlockReduce2dSync<Problem>();
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auto block_reduce2d_cross_warp_sync =
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Policy::template GetBlockReduce2dCrossWarpSync<Problem>();
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using XTensorType = decltype(cast_tile<ComputeDataType>(load_tile(x_window)));
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auto absmax = block_reduce2d.template MakeYBlockTile<XTensorType>();
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set_tile(absmax, reduce_absmax_func.GetIdentityValue<ComputeDataType>());
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for(int iN = __builtin_amdgcn_readfirstlane(0); iN < num_n_tile_iteration; ++iN)
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{
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const auto x = load_tile(x_window);
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const auto xscale = load_tile(xscale_window);
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const auto y = tile_elementwise_in(
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[&](const auto& a, const auto& b) {
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return type_convert<ComputeDataType>(a) * type_convert<ComputeDataType>(b);
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},
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x,
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xscale);
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block_reduce2d(y, absmax, reduce_absmax_func);
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move_tile_window(x_window, {0, Block_N});
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move_tile_window(xscale_window, {Block_N});
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}
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// compute absmax, cross-lane->cross-warp
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block_reduce2d_sync(absmax, reduce_max_func);
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block_reduce2d_cross_warp_sync(absmax, smem, reduce_max_func);
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// ex: yscale = absmax / 127 if int8
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auto yscale = tile_elementwise_in(
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[&](const auto& v_) {
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return v_ / type_convert<ComputeDataType>(numeric<QYDataType>::max());
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},
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absmax);
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store_tile(yscale_window, cast_tile<YScaleDataType>(yscale));
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// reverse read x to reuse cache
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ck_tile::index_t stride_to_right_most_window =
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row_size % Block_N == 0 ? row_size - Block_N : row_size - row_size % Block_N;
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move_tile_window(x_window, {0, -Block_N});
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move_tile_window(xscale_window, {-Block_N});
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move_tile_window(qy_window, {0, stride_to_right_most_window});
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// recompute y and quantize y to qy
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for(int iN = __builtin_amdgcn_readfirstlane(0); iN < num_n_tile_iteration; ++iN)
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{
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const auto x = load_tile(x_window);
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const auto xscale = load_tile(xscale_window);
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const auto y = tile_elementwise_in(
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[&](const auto& a, const auto& b) {
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return type_convert<ComputeDataType>(a) * type_convert<ComputeDataType>(b);
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},
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x,
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xscale);
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auto qy = make_static_distributed_tensor<QYDataType>(y.get_tile_distribution());
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sweep_tile(qy, [&](auto idx) {
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constexpr auto i_idx = make_tuple(idx[number<0>{}]);
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auto qy_ = y[idx] / yscale[i_idx];
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qy(idx) = saturates<QYDataType>{}(qy_);
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});
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store_tile(qy_window, qy);
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move_tile_window(x_window, {0, -Block_N});
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move_tile_window(xscale_window, {0, -Block_N});
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move_tile_window(qy_window, {0, -Block_N});
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}
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}
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};
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} // namespace ck_tile
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