smoothquant_kernel.hpp Source File

smoothquant_kernel.hpp Source File#

Composable Kernel: smoothquant_kernel.hpp Source File
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
 
#pragma once
 
#include "ck_tile/core.hpp"
#include "ck_tile/ops/common.hpp"
 
namespace ck_tile {
 
// host side args
struct SmoothquantHostArgs
{
    const void* p_x;       // [m ,n], input, fp16/bf16
    const void* p_smscale; // [1, n], input, columnwise scale, fp32
 
    void* p_yscale; // [m, 1], output, rowwise quant scale (amax / 127) of (p_x * p_smscale)
    void* p_qy;     // [m, n], output, p_x * p_smscale / p_yscale
 
    index_t m;
    index_t n;
    index_t x_stride; // input row_stride
    index_t y_stride; // output row_stride
};
 
// TODO: Extract some type to wrapper class
template <typename Pipeline_>
struct Smoothquant
{
    using Pipeline = remove_cvref_t<Pipeline_>;
    using Problem  = typename Pipeline::Problem;
 
    using XDataType           = remove_cvref_t<typename Problem::XDataType>;
    using SmoothScaleDataType = remove_cvref_t<typename Problem::SmoothScaleDataType>;
    using ComputeDataType     = remove_cvref_t<typename Problem::ComputeDataType>;
    using YScaleDataType      = remove_cvref_t<typename Problem::YScaleDataType>;
    using QYDataType          = remove_cvref_t<typename Problem::QYDataType>;
 
    static constexpr index_t Block_M = Problem::BlockShape::Block_M;
    static constexpr index_t Block_N = Problem::BlockShape::Block_N;
    static constexpr bool kPadM      = false; // always no need to pad along M
    static constexpr bool kPadN      = Problem::kPadN;
    static constexpr bool kTwoPass   = Problem::kTwoPass;
 
    static constexpr index_t ThreadPerWarp_N = Problem::BlockShape::ThreadPerWarp_N;
    static constexpr index_t Vector_N        = Problem::BlockShape::Vector_N;
    static constexpr index_t Repeat_N        = Problem::BlockShape::Repeat_N;
    static constexpr index_t kBlockSize      = Problem::BlockShape::BlockSize;
 
    static constexpr auto I0 = number<0>{};
    static constexpr auto I1 = number<1>{};
 
    struct Kargs
    {
        const void* p_x;
        const void* p_smscale;
 
        void* p_yscale;
        void* p_qy;
 
        index_t m;
        index_t n;
        index_t x_stride; // input row_stride
        index_t y_stride; // out row_stride
    };
    using Hargs = SmoothquantHostArgs;
 
    CK_TILE_HOST static constexpr Kargs MakeKargs(const Hargs& hargs)
    {
        return Kargs{hargs.p_x,
                     hargs.p_smscale,
                     hargs.p_yscale,
                     hargs.p_qy,
                     hargs.m,
                     hargs.n,
                     hargs.x_stride,
                     hargs.y_stride};
    }
 
    CK_TILE_HOST static constexpr auto GridSize(const Hargs& hargs)
    {
        return dim3(integer_divide_ceil(hargs.m, Block_M));
    }
 
    CK_TILE_HOST static constexpr auto BlockSize()
    {
        return is_wave32() ? Problem::BlockShape::template GetBlockSize<true>()
                           : Problem::BlockShape::template GetBlockSize<false>();
    }
 
    // clang-format off
    template <typename T> struct t2s;
    template <> struct t2s<float> { static constexpr const char * name = "fp32"; };
    template <> struct t2s<ck_tile::fp16_t> { static constexpr const char * name = "fp16"; };
    template <> struct t2s<ck_tile::bf16_t> { static constexpr const char * name = "bf16"; };
    template <> struct t2s<ck_tile::fp8_t> { static constexpr const char * name = "fp8"; };
    template <> struct t2s<ck_tile::bf8_t> { static constexpr const char * name = "bf8"; };
    // clang-format on
 
    // in byte
    CK_TILE_HOST_DEVICE static constexpr index_t GetSmemSize() { return Pipeline::GetSmemSize(); }
 
    CK_TILE_HOST static std::string GetName()
    {
        // clang-format off
        using S_ = typename Problem::BlockShape;
        auto surfix = [&] () {
            std::string n;
            if (kPadN) n += "_pn";
            if (kTwoPass) n += "_2p";
            return n; }();
 
        #define _SS_  std::string
        #define _TS_  std::to_string
        return _SS_("smoothquant_fwd_") + _SS_(t2s<XDataType>::name) + "_" +
             _TS_(S_::Block_M) + "x" + _TS_(S_::Block_N) + "_" + _TS_(S_::WarpPerBlock_M) + "x" + _TS_(S_::WarpPerBlock_N) + "_" +
             _TS_(S_::Warp_M) + "x" + _TS_(S_::Warp_N) + "_" + _TS_(S_::Vector_M) + "x" + _TS_(S_::Vector_N) + "_" +
             _SS_(Pipeline::name) + surfix;
        #undef _SS_
        #undef _TS_
        // clang-format on
    }
 
    CK_TILE_DEVICE void operator()(Kargs kargs) const
    {
        const auto iM = get_block_id() * Block_M;
 
        const auto x_window = [&]() {
            const auto tmp_ = make_naive_tensor_view<address_space_enum::global>(
                static_cast<const XDataType*>(kargs.p_x),
                make_tuple(kargs.m, kargs.n),
                make_tuple(kargs.x_stride, 1),
                number<Vector_N>{},
                number<1>{});
 
            const auto tmp2_ = pad_tensor_view(
                tmp_, make_tuple(number<Block_M>{}, number<Block_N>{}), sequence<kPadM, kPadN>{});
            return make_tile_window(
                tmp2_, make_tuple(number<Block_M>{}, number<Block_N>{}), {iM, 0});
        }();
 
        const auto smscale_window = [&]() {
            const auto tmp_ = make_naive_tensor_view<address_space_enum::global>(
                static_cast<const SmoothScaleDataType*>(kargs.p_smscale),
                make_tuple(kargs.n),
                make_tuple(1),
                number<Vector_N>{},
                number<1>{});
 
            const auto tmp2_ =
                pad_tensor_view(tmp_, make_tuple(number<Block_N>{}), sequence<kPadN>{});
 
            return make_tile_window(tmp2_, make_tuple(number<Block_N>{}), {0});
        }();
 
        auto yscale_window = [&]() {
            const auto tmp_ = make_naive_tensor_view<address_space_enum::global>(
                static_cast<YScaleDataType*>(kargs.p_yscale),
                make_tuple(kargs.m),
                make_tuple(1),
                number<1>{});
 
            const auto tmp2_ =
                pad_tensor_view(tmp_, make_tuple(number<Block_M>{}), sequence<kPadM>{});
 
            return make_tile_window(tmp2_, make_tuple(number<Block_M>{}), {iM});
        }();
 
        auto qy_window = [&]() {
            auto tmp_ = make_naive_tensor_view<address_space_enum::global>(
                static_cast<QYDataType*>(kargs.p_qy),
                make_tuple(kargs.m, kargs.n),
                make_tuple(kargs.y_stride, 1),
                number<Vector_N>{},
                number<1>{});
 
            auto tmp2_ = pad_tensor_view(
                tmp_, make_tuple(number<Block_M>{}, number<Block_N>{}), sequence<kPadM, kPadN>{});
            return make_tile_window(
                tmp2_, make_tuple(number<Block_M>{}, number<Block_N>{}), {iM, 0});
        }();
 
        __shared__ char smem[GetSmemSize()];
 
        Pipeline{}(x_window, smscale_window, yscale_window, qy_window, kargs.n, smem);
    }
};
 
} // namespace ck_tile