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Commit a7ae4f8e authored by Astha Rai's avatar Astha Rai
Browse files

Merge branch 'codegen_hiprtc' of github.com:ROCm/composable_kernel into codegen_hiprtc

parents a6055c3c 781005a5
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include/ck_tile/ops/layernorm2d/pipeline/layernorm2d_fwd_pipeline_one_pass.hpp
View file @ a7ae4f8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
......@@ -64,7 +64,7 @@ struct Layernorm2dFwdPipelineOnePass
typename YResidualWindow,
typename MeanWindow,
typename InvStdWindow,
typename XScaleWindow,
typename SmoothScaleWindow,
typename YScaleWindow,
typename Epilogue>
CK_TILE_DEVICE auto operator()(const XWindow& x_window_,
......@@ -76,7 +76,7 @@ struct Layernorm2dFwdPipelineOnePass
const YResidualWindow& y_residual_window_,
MeanWindow& mean_window,
InvStdWindow& inv_std_window,
const XScaleWindow& x_scale_window_,
const SmoothScaleWindow& sm_scale_window_,
YScaleWindow& y_scale_window,
ComputeDataType epsilon,
ck_tile::index_t row_size,
......@@ -190,7 +190,7 @@ struct Layernorm2dFwdPipelineOnePass
if constexpr(kFusedQuant == Layernorm2dFusedQuantEnum::DYNAMIC_QUANT ||
kFusedQuant == Layernorm2dFusedQuantEnum::SMOOTH_DYNAMIC_QUANT)
{
Epilogue{}(y_window_, x_scale_window_, y_scale_window, ln, smem);
Epilogue{}(y_window_, sm_scale_window_, y_scale_window, ln, smem);
}
else
Epilogue{}(y_window_, ln);
......
include/ck_tile/ops/layernorm2d/pipeline/layernorm2d_fwd_pipeline_problem.hpp
View file @ a7ae4f8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
......@@ -15,23 +15,23 @@ template <typename XDataType_,
typename YDataType_,
typename MeanDataType_,
typename InvStdDataType_,
typename XScaleDataType_,
typename SmoothScaleDataType_,
typename YScaleDataType_,
typename BlockShape_,
typename Traits_>
struct Layernorm2dFwdPipelineProblem
{
using XDataType = remove_cvref_t<XDataType_>;
using XBiasDataType = remove_cvref_t<XBiasDataType_>;
using GammaDataType = remove_cvref_t<GammaDataType_>;
using BetaDataType = remove_cvref_t<BetaDataType_>;
using ComputeDataType = remove_cvref_t<ComputeDataType_>;
using YDataType = remove_cvref_t<YDataType_>;
using MeanDataType = remove_cvref_t<MeanDataType_>;
using InvStdDataType = remove_cvref_t<InvStdDataType_>;
using XScaleDataType = remove_cvref_t<XScaleDataType_>;
using YScaleDataType = remove_cvref_t<YScaleDataType_>;
using BlockShape = remove_cvref_t<BlockShape_>;
using XDataType = remove_cvref_t<XDataType_>;
using XBiasDataType = remove_cvref_t<XBiasDataType_>;
using GammaDataType = remove_cvref_t<GammaDataType_>;
using BetaDataType = remove_cvref_t<BetaDataType_>;
using ComputeDataType = remove_cvref_t<ComputeDataType_>;
using YDataType = remove_cvref_t<YDataType_>;
using MeanDataType = remove_cvref_t<MeanDataType_>;
using InvStdDataType = remove_cvref_t<InvStdDataType_>;
using SmoothScaleDataType = remove_cvref_t<SmoothScaleDataType_>;
using YScaleDataType = remove_cvref_t<YScaleDataType_>;
using BlockShape = remove_cvref_t<BlockShape_>;
static constexpr bool kNeedCrossLaneSync = BlockShape::ThreadPerWarp_N > 1;
static constexpr bool kNeedCrossWarpSync = BlockShape::WarpPerBlock_N > 1;
......
include/ck_tile/ops/layernorm2d/pipeline/layernorm2d_fwd_pipeline_two_pass.hpp
View file @ a7ae4f8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
......@@ -63,7 +63,7 @@ struct Layernorm2dFwdPipelineTwoPass
typename YResidualWindow,
typename MeanWindow,
typename InvStdWindow,
typename XScaleWindow,
typename SmoothScaleWindow,
typename YScaleWindow,
typename Epilogue>
CK_TILE_DEVICE auto operator()(const XWindow& x_window_,
......@@ -75,7 +75,7 @@ struct Layernorm2dFwdPipelineTwoPass
const YResidualWindow& y_residual_window_,
MeanWindow& mean_window,
InvStdWindow& inv_std_window,
const XScaleWindow& /*x_scale_window*/,
const SmoothScaleWindow& /*sm_scale_window*/,
YScaleWindow& /*y_scale_window*/,
ComputeDataType epsilon,
ck_tile::index_t row_size,
......
include/ck_tile/ops/rmsnorm2d.hpp
View file @ a7ae4f8e
......@@ -8,5 +8,6 @@
#include "ck_tile/ops/rmsnorm2d/pipeline/rmsnorm2d_fwd_pipeline_one_pass.hpp"
#include "ck_tile/ops/rmsnorm2d/pipeline/rmsnorm2d_fwd_pipeline_problem.hpp"
#include "ck_tile/ops/rmsnorm2d/pipeline/rmsnorm2d_fwd_pipeline_two_pass.hpp"
#include "ck_tile/ops/rmsnorm2d/pipeline/rmsnorm2d_fwd_traits.hpp"
#include "ck_tile/ops/common/generic_2d_block_shape.hpp"
#include "ck_tile/ops/common/tensor_layout.hpp"
include/ck_tile/ops/rmsnorm2d/kernel/rmsnorm2d_fwd_kernel.hpp
View file @ a7ae4f8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "ck_tile/core.hpp"
#include "ck_tile/ops/common.hpp"
#include "ck_tile/ops/rmsnorm2d/pipeline/rmsnorm2d_fwd_traits.hpp"
namespace ck_tile {
// host side args
struct Rmsnorm2dFwdHostArgs
{
const void* p_x; // [m ,n], input, fp16/bf16
const void* p_gamma; // [1, n], gamma, prec same as input
const void* p_x; // [m ,n], input, fp16/bf16
const void* p_x_residual; // [m ,n], shortcut input, prec same as input, nullptr if not used
const void* p_sm_scale; // [1 ,n], smooth scale input, fp32, nullptr if not used
const void* p_gamma; // [1, n], gamma, prec same as input
void* p_y; // [m, n], output, fp16/bf16
void* p_invRms; // [m, 1], output inv-rms, prec same as input, nullptr if not used
void* p_y; // [m, n], output, fp16/bf16
void* p_y_residual; // [m, n], shortcut output, prec same as input, nullptr if not used
void* p_y_scale; // [m, 1], output a dynamic quant per row, nullptr if not used
void* p_invRms; // [m, 1], output inv-rms, prec same as input, nullptr if not used
float epsilon;
index_t m;
index_t n;
index_t stride; // row_stride
index_t x_stride; // x row_stride
index_t xr_stride; // x residule row stride
index_t y_stride; // y row stride
index_t yr_stride; // y residule row stride
};
// TODO: Extract some type to wrapper class
template <typename Pipeline_>
template <typename Pipeline_, typename Epilogue_>
struct Rmsnorm2dFwd
{
using Pipeline = remove_cvref_t<Pipeline_>;
using Epilogue = remove_cvref_t<Epilogue_>;
using Problem = typename Pipeline::Problem;
using XDataType = remove_cvref_t<typename Problem::XDataType>;
using GammaDataType = remove_cvref_t<typename Problem::GammaDataType>;
using ComputeDataType = remove_cvref_t<typename Problem::ComputeDataType>;
using YDataType = remove_cvref_t<typename Problem::YDataType>;
using InvRmsDataType = remove_cvref_t<typename Problem::InvRmsDataType>;
using XDataType = remove_cvref_t<typename Problem::XDataType>;
using GammaDataType = remove_cvref_t<typename Problem::GammaDataType>;
using ComputeDataType = remove_cvref_t<typename Problem::ComputeDataType>;
using YDataType = remove_cvref_t<typename Problem::YDataType>;
using InvRmsDataType = remove_cvref_t<typename Problem::InvRmsDataType>;
using SmoothScaleDataType = remove_cvref_t<typename Problem::SmoothScaleDataType>;
using YScaleDataType = remove_cvref_t<typename Problem::YScaleDataType>;
// for simplicity, shortcut input/output type is same as X
using XResidualDataType = XDataType;
using YResidualDataType = XDataType;
static constexpr bool kHasGamma = !std::is_same_v<GammaDataType, null_type>;
static constexpr bool kSaveInvRms = Problem::kSaveInvRms;
static constexpr bool kSaveInvRms = Problem::Traits::kSaveInvRms;
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 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::Traits::kPadN;
static constexpr bool kTwoPass = Problem::Traits::kTwoPass;
static constexpr auto kFusedAdd = Problem::Traits::kFusedAdd;
static constexpr auto kFusedQuant = Problem::Traits::kFusedQuant;
static constexpr index_t ThreadPerWarp_N = Problem::BlockShape::ThreadPerWarp_N;
static constexpr index_t Vector_N = Problem::BlockShape::Vector_N;
......@@ -56,29 +73,43 @@ struct Rmsnorm2dFwd
struct Kargs
{
const void* p_x;
const void* p_x_residual;
const void* p_sm_scale;
const void* p_gamma;
void* p_y;
void* p_y_residual;
void* p_y_scale;
void* p_invRms;
float epsilon;
index_t m;
index_t n;
index_t stride; // row_stride
index_t x_stride; // x row_stride
index_t xr_stride; // x residule row stride
index_t y_stride; // y row stride
index_t yr_stride; // y residule row stride
};
using Hargs = Rmsnorm2dFwdHostArgs;
CK_TILE_HOST static constexpr Kargs MakeKargs(const Hargs& hargs)
{
return Kargs{hargs.p_x,
hargs.p_x_residual,
hargs.p_sm_scale,
hargs.p_gamma,
hargs.p_y,
hargs.p_y_residual,
hargs.p_y_scale,
hargs.p_invRms,
hargs.epsilon,
hargs.m,
hargs.n,
hargs.stride};
hargs.x_stride,
hargs.xr_stride,
hargs.y_stride,
hargs.yr_stride};
}
CK_TILE_HOST static constexpr auto GridSize(const Hargs& hargs)
......@@ -95,6 +126,7 @@ struct Rmsnorm2dFwd
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"; };
template <> struct t2s<ck_tile::int8_t> { static constexpr const char * name = "int8"; };
// clang-format on
// in byte
......@@ -102,24 +134,41 @@ struct Rmsnorm2dFwd
CK_TILE_HOST static std::string GetName()
{
#define _SS_ std::string
#define _TS_ std::to_string
// clang-format off
using S_ = typename Problem::BlockShape;
auto surfix = [&] () {
std::string n;
if (kFusedAdd != Rmsnorm2dFusedAddEnum::NO_ADD) n += _SS_("_") + Rmsnorm2dFusedAddEnumName<kFusedAdd>::name;
if (kFusedQuant != Rmsnorm2dFusedQuantEnum::NO_SWEEP) n += _SS_("_") + Rmsnorm2dFusedQuantEnumName<kFusedQuant>::name;
if (kPadN) n += "_pn";
if (kSaveInvRms) n += "_rms";
if (kTwoPass) n += "_2p";
return n; }();
#define _SS_ std::string
#define _TS_ std::to_string
return _SS_("rmsnorm2d_fwd_") + _SS_(t2s<XDataType>::name) + "_" +
auto prec_str = [&] () {
std::string base_str = _SS_(t2s<XDataType>::name);
if (!std::is_same_v<XDataType, YDataType>) {
base_str += _SS_("_") + _SS_(t2s<YDataType>::name);
}
if (kFusedQuant == Rmsnorm2dFusedQuantEnum::SMOOTH_DYNAMIC_QUANT) {
base_str += _SS_("_sx") + _SS_(t2s<SmoothScaleDataType>::name);
base_str += _SS_("_sy") + _SS_(t2s<YScaleDataType>::name);
}
if (kFusedQuant == Rmsnorm2dFusedQuantEnum::DYNAMIC_QUANT) {
base_str += _SS_("_sy") + _SS_(t2s<YScaleDataType>::name);
}
return base_str;
}();
return _SS_("rmsnorm2d_fwd_") + _SS_(prec_str) + "_" +
_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
#undef _SS_
#undef _TS_
}
CK_TILE_DEVICE void operator()(Kargs kargs) const
......@@ -130,7 +179,7 @@ struct Rmsnorm2dFwd
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.stride, 1),
make_tuple(kargs.x_stride, 1),
number<Vector_N>{},
number<1>{});
......@@ -140,6 +189,29 @@ struct Rmsnorm2dFwd
tmp2_, make_tuple(number<Block_M>{}, number<Block_N>{}), {iM, 0});
}();
const auto x_residual_window = [&]() {
if constexpr(kFusedAdd == Rmsnorm2dFusedAddEnum::PRE_ADD ||
kFusedAdd == Rmsnorm2dFusedAddEnum::PRE_ADD_STORE)
{
const auto tmp_ = make_naive_tensor_view<address_space_enum::global>(
static_cast<const XResidualDataType*>(kargs.p_x_residual),
make_tuple(kargs.m, kargs.n),
make_tuple(kargs.xr_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});
}
else
{
return make_null_tile_window(make_tuple(number<Block_M>{}, number<Block_N>{}));
}
}();
const auto gamma_window = [&]() {
const auto tmp_ = make_naive_tensor_view<address_space_enum::global>(
static_cast<const GammaDataType*>(kargs.p_gamma),
......@@ -158,7 +230,7 @@ struct Rmsnorm2dFwd
auto tmp_ = make_naive_tensor_view<address_space_enum::global>(
static_cast<YDataType*>(kargs.p_y),
make_tuple(kargs.m, kargs.n),
make_tuple(kargs.stride, 1),
make_tuple(kargs.y_stride, 1),
number<Vector_N>{},
number<1>{});
......@@ -168,6 +240,28 @@ struct Rmsnorm2dFwd
tmp2_, make_tuple(number<Block_M>{}, number<Block_N>{}), {iM, 0});
}();
auto y_residual_window = [&]() {
if constexpr(kFusedAdd == Rmsnorm2dFusedAddEnum::PRE_ADD_STORE)
{
auto tmp_ = make_naive_tensor_view<address_space_enum::global>(
static_cast<YResidualDataType*>(kargs.p_y_residual),
make_tuple(kargs.m, kargs.n),
make_tuple(kargs.yr_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});
}
else
{
return make_null_tile_window(make_tuple(number<Block_M>{}, number<Block_N>{}));
}
}();
auto inv_rms_window = [&]() {
if constexpr(kSaveInvRms)
{
......@@ -187,15 +281,62 @@ struct Rmsnorm2dFwd
return make_null_tile_window(make_tuple(number<Block_M>{}));
}();
auto sm_scale_window = [&]() {
if constexpr(kFusedQuant == Rmsnorm2dFusedQuantEnum::SMOOTH_DYNAMIC_QUANT)
{
const auto win_ = [&]() {
const auto tmp_0_ = make_naive_tensor_view_packed<address_space_enum::global>(
static_cast<const SmoothScaleDataType*>(kargs.p_sm_scale),
make_tuple(kargs.n),
number<Vector_N>{});
return pad_tensor_view(tmp_0_,
make_tuple(number<Block_N>{}),
sequence<false>{}); // sm_scale no need pad
}();
return make_tile_window(win_, make_tuple(number<Block_N>{}), {0});
}
else
{
return make_null_tile_window(make_tuple(number<Block_N>{}));
}
}();
auto y_scale_window = [&]() {
if constexpr(kFusedQuant == Rmsnorm2dFusedQuantEnum::SMOOTH_DYNAMIC_QUANT ||
kFusedQuant == Rmsnorm2dFusedQuantEnum::DYNAMIC_QUANT)
{
const auto win_ = [&]() {
const auto tmp_0_ = make_naive_tensor_view_packed<address_space_enum::global>(
static_cast<YScaleDataType*>(kargs.p_y_scale),
make_tuple(kargs.m),
number<1>{});
return pad_tensor_view(
tmp_0_, make_tuple(number<Block_M>{}), sequence<kPadM>{});
}();
return make_tile_window(win_, make_tuple(number<Block_M>{}), {iM});
}
else
{
return make_null_tile_window(make_tuple(number<Block_M>{}));
}
}();
__shared__ char smem[GetSmemSize()];
Pipeline{}(x_window,
x_residual_window,
gamma_window,
y_window,
y_residual_window,
inv_rms_window,
sm_scale_window,
y_scale_window,
static_cast<const ComputeDataType>(kargs.epsilon),
kargs.n,
smem);
smem,
Epilogue{});
}
};
......
include/ck_tile/ops/rmsnorm2d/pipeline/rmsnorm2d_fwd_pipeline_default_policy.hpp
View file @ a7ae4f8e
......@@ -45,7 +45,7 @@ struct Rmsnorm2dFwdPipelineDefaultPolicy
template <typename Problem>
CK_TILE_HOST_DEVICE static constexpr auto GetBlockReduce2d()
{
using P_ = BlockReduce2dProblem<typename Problem::XDataType,
using P_ = BlockReduce2dProblem<typename Problem::ComputeDataType,
typename Problem::ComputeDataType,
typename Problem::BlockShape>;
return BlockReduce2d<P_>{};
......@@ -54,7 +54,7 @@ struct Rmsnorm2dFwdPipelineDefaultPolicy
template <typename Problem>
CK_TILE_HOST_DEVICE static constexpr auto GetBlockReduce2dSync()
{
using P_ = BlockReduce2dProblem<typename Problem::XDataType,
using P_ = BlockReduce2dProblem<typename Problem::ComputeDataType,
typename Problem::ComputeDataType,
typename Problem::BlockShape>;
return BlockReduce2dSync<P_>{};
......@@ -63,7 +63,7 @@ struct Rmsnorm2dFwdPipelineDefaultPolicy
template <typename Problem>
CK_TILE_HOST_DEVICE static constexpr auto GetBlockReduce2dCrossWarpSync()
{
using P_ = BlockReduce2dProblem<typename Problem::XDataType,
using P_ = BlockReduce2dProblem<typename Problem::ComputeDataType,
typename Problem::ComputeDataType,
typename Problem::BlockShape>;
return BlockReduce2dCrossWarpSync<P_>{};
......@@ -74,13 +74,13 @@ struct Rmsnorm2dFwdPipelineDefaultPolicy
{
if constexpr(Problem::kNeedCrossWarpSync)
{
using P_ = BlockReduce2dProblem<typename Problem::XDataType,
using P_ = BlockReduce2dProblem<typename Problem::ComputeDataType,
typename Problem::ComputeDataType,
typename Problem::BlockShape>;
using block_reduce2d = BlockReduce2d<P_>;
using x_block_tile =
decltype(make_static_distributed_tensor<typename Problem::XDataType>(
decltype(make_static_distributed_tensor<typename Problem::ComputeDataType>(
MakeXBlockTileDistribution<Problem>()));
using y_block_tile = decltype(block_reduce2d::template MakeYBlockTile<x_block_tile>());
......
include/ck_tile/ops/rmsnorm2d/pipeline/rmsnorm2d_fwd_pipeline_one_pass.hpp
View file @ a7ae4f8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
......@@ -22,12 +22,17 @@ struct Rmsnorm2dFwdPipelineOnePass
using YDataType = ck_tile::remove_cvref_t<typename Problem::YDataType>;
using InvRmsDataType = ck_tile::remove_cvref_t<typename Problem::InvRmsDataType>;
using XResidualDataType = XDataType;
using YResidualDataType = XDataType;
static constexpr bool kHasGamma = !std::is_same_v<GammaDataType, ck_tile::null_type>;
static constexpr bool kSaveInvRms = Problem::kSaveInvRms;
static constexpr bool kSaveInvRms = Problem::Traits::kSaveInvRms;
static constexpr bool kNeedCrossWarpSync = Problem::kNeedCrossWarpSync;
static constexpr bool kPadM = false; // TODO - BlockRmsnorm2dFwdProblem::kPadM
static constexpr bool kPadN = Problem::kPadN;
static constexpr bool kPadN = Problem::Traits::kPadN;
static constexpr auto kFusedAdd = Problem::Traits::kFusedAdd;
static constexpr auto kFusedQuant = Problem::Traits::kFusedQuant;
static constexpr const char* name = []() {
if constexpr(kNeedCrossWarpSync)
......@@ -41,19 +46,36 @@ struct Rmsnorm2dFwdPipelineOnePass
return Policy::template GetSmemSize<Problem>();
}
template <typename XWindow, typename GammaWindow, typename YWindow, typename InvRmsWindow>
template <typename XWindow,
typename XResidualWindow,
typename GammaWindow,
typename YWindow,
typename YResidualWindow,
typename InvRmsWindow,
typename SmoothScaleWindow,
typename YScaleWindow,
typename Epilogue>
CK_TILE_DEVICE auto operator()(const XWindow& x_window_,
const XResidualWindow& x_residual_window_,
const GammaWindow& gamma_window_,
YWindow& y_window,
YWindow& y_window_,
const YResidualWindow& y_residual_window_,
InvRmsWindow& inv_rms_window,
const SmoothScaleWindow& sm_scale_window_,
YScaleWindow& y_scale_window_,
ComputeDataType epsilon,
ck_tile::index_t row_size,
void* smem) const
void* smem,
Epilogue) const
{
const auto x_window =
make_tile_window(x_window_, Policy::template MakeXBlockTileDistribution<Problem>());
const auto gamma_window = make_tile_window(
gamma_window_, Policy::template MakeGammaBlockTileDistribution<Problem>());
const auto x_residual_window = make_tile_window(
x_residual_window_, Policy::template MakeXBlockTileDistribution<Problem>());
auto y_residual_window = make_tile_window(
y_residual_window_, Policy::template MakeXBlockTileDistribution<Problem>());
auto reduce_square_sum_func = ReduceOp::SquareAdd{};
auto reduce_sum_func = ReduceOp::Add{};
......@@ -62,13 +84,31 @@ struct Rmsnorm2dFwdPipelineOnePass
auto block_reduce2d_cross_warp_sync =
Policy::template GetBlockReduce2dCrossWarpSync<Problem>();
const auto x = load_tile(x_window);
auto x = load_tile(x_window);
auto x_resi = load_tile(x_residual_window);
// load gamma (TODO: support no gamma?)
const auto gamma = load_tile(gamma_window);
auto acc = cast_tile<ComputeDataType>(x);
if constexpr(kFusedAdd == Rmsnorm2dFusedAddEnum::PRE_ADD ||
kFusedAdd == Rmsnorm2dFusedAddEnum::PRE_ADD_STORE)
{
sweep_tile(x_resi, [&](auto idx) {
// compute x = x_resi + x
acc(idx) = type_convert<ComputeDataType>(x_resi(idx)) + acc(idx);
});
if constexpr(kFusedAdd == Rmsnorm2dFusedAddEnum::PRE_ADD_STORE)
{
store_tile(y_residual_window, cast_tile<YResidualDataType>(acc));
}
}
// compute mean square each-thread->cross-lane->cross-warp
auto square_sum = block_reduce2d(
x, reduce_square_sum_func.GetIdentityValue<ComputeDataType>(), reduce_square_sum_func);
auto square_sum = block_reduce2d(acc,
reduce_square_sum_func.GetIdentityValue<ComputeDataType>(),
reduce_square_sum_func);
block_reduce2d_sync(square_sum, reduce_sum_func);
block_reduce2d_cross_warp_sync(square_sum, smem, reduce_sum_func);
......@@ -83,19 +123,30 @@ struct Rmsnorm2dFwdPipelineOnePass
store_tile(inv_rms_window, cast_tile<InvRmsDataType>(inv_rms));
// rmsnorm computation
auto y = make_static_distributed_tensor<YDataType>(x.get_tile_distribution());
sweep_tile(y, [&, inv_rms_ = inv_rms](auto idx) {
auto rmsn = make_static_distributed_tensor<ComputeDataType>(x.get_tile_distribution());
sweep_tile(rmsn, [&, inv_rms_ = inv_rms](auto idx) {
constexpr auto i_idx = make_tuple(idx[number<0>{}]);
constexpr auto j_idx = make_tuple(idx[number<1>{}]);
const auto gamma_ = type_convert<ComputeDataType>(gamma[j_idx]);
const auto x_ = type_convert<ComputeDataType>(x[idx]);
auto y_ = x_ * inv_rms_[i_idx] * gamma_;
auto rmsn_ = acc[idx] * inv_rms_[i_idx] * gamma_;
y(idx) = type_convert<YDataType>(y_);
rmsn(idx) = rmsn_;
});
store_tile(y_window, y);
if constexpr(kFusedQuant == Rmsnorm2dFusedQuantEnum::SMOOTH_DYNAMIC_QUANT)
{
Epilogue{}(y_window_, sm_scale_window_, y_scale_window_, rmsn, smem);
}
else if constexpr(kFusedQuant == Rmsnorm2dFusedQuantEnum::DYNAMIC_QUANT)
{
Epilogue{}(y_window_, y_scale_window_, rmsn, smem);
}
else
{
Epilogue{}(y_window_, rmsn);
}
}
};
} // namespace ck_tile
include/ck_tile/ops/rmsnorm2d/pipeline/rmsnorm2d_fwd_pipeline_problem.hpp
View file @ a7ae4f8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
......@@ -12,25 +12,25 @@ template <typename XDataType_,
typename ComputeDataType_,
typename YDataType_,
typename InvRmsDataType_,
typename SmoothScaleDataType_,
typename YScaleDataType_,
typename BlockShape_,
bool kPadN_,
bool kSaveInvRms_,
bool kTwoPass_>
typename Traits_>
struct Rmsnorm2dFwdPipelineProblem
{
using XDataType = remove_cvref_t<XDataType_>;
using GammaDataType = remove_cvref_t<GammaDataType_>;
using ComputeDataType = remove_cvref_t<ComputeDataType_>;
using YDataType = remove_cvref_t<YDataType_>;
using InvRmsDataType = remove_cvref_t<InvRmsDataType_>;
using BlockShape = remove_cvref_t<BlockShape_>;
using XDataType = remove_cvref_t<XDataType_>;
using GammaDataType = remove_cvref_t<GammaDataType_>;
using ComputeDataType = remove_cvref_t<ComputeDataType_>;
using YDataType = remove_cvref_t<YDataType_>;
using InvRmsDataType = remove_cvref_t<InvRmsDataType_>;
using SmoothScaleDataType = remove_cvref_t<SmoothScaleDataType_>;
using YScaleDataType = remove_cvref_t<YScaleDataType_>;
using BlockShape = remove_cvref_t<BlockShape_>;
static constexpr bool kNeedCrossLaneSync = BlockShape::ThreadPerWarp_N > 1;
static constexpr bool kNeedCrossWarpSync = BlockShape::WarpPerBlock_N > 1;
static constexpr bool kPadN = kPadN_;
static constexpr bool kSaveInvRms = kSaveInvRms_;
static constexpr bool kTwoPass = kTwoPass_;
using Traits = remove_cvref_t<Traits_>;
};
} // namespace ck_tile
include/ck_tile/ops/rmsnorm2d/pipeline/rmsnorm2d_fwd_pipeline_two_pass.hpp
View file @ a7ae4f8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
......@@ -22,12 +22,17 @@ struct Rmsnorm2dFwdPipelineTwoPass
using YDataType = ck_tile::remove_cvref_t<typename Problem::YDataType>;
using InvRmsDataType = ck_tile::remove_cvref_t<typename Problem::InvRmsDataType>;
using XResidualDataType = XDataType;
using YResidualDataType = XDataType;
static constexpr bool kHasGamma = !std::is_same_v<GammaDataType, ck_tile::null_type>;
static constexpr bool kSaveInvRms = Problem::kSaveInvRms;
static constexpr bool kSaveInvRms = Problem::Traits::kSaveInvRms;
static constexpr bool kNeedCrossWarpSync = Problem::kNeedCrossWarpSync;
static constexpr bool kPadM = false; // TODO - BlockRmsnorm2dFwdProblem::kPadM
static constexpr bool kPadN = Problem::kPadN;
static constexpr bool kPadN = Problem::Traits::kPadN;
static constexpr auto kFusedAdd = Problem::Traits::kFusedAdd;
static constexpr auto kFusedQuant = Problem::Traits::kFusedQuant;
static constexpr const char* name = []() {
if constexpr(kNeedCrossWarpSync)
......@@ -41,19 +46,36 @@ struct Rmsnorm2dFwdPipelineTwoPass
return Policy::template GetSmemSize<Problem>();
}
template <typename XWindow, typename GammaWindow, typename YWindow, typename InvRmsWindow>
template <typename XWindow,
typename XResidualWindow,
typename GammaWindow,
typename YWindow,
typename YResidualWindow,
typename InvRmsWindow,
typename SmoothScaleWindow,
typename YScaleWindow,
typename Epilogue>
CK_TILE_DEVICE auto operator()(const XWindow& x_window_,
const XResidualWindow& x_residual_window_,
const GammaWindow& gamma_window_,
YWindow& y_window,
const YResidualWindow& y_residual_window_,
InvRmsWindow& inv_rms_window,
const SmoothScaleWindow& /*sm_scale_window_*/,
YScaleWindow& /*y_scale_window*/,
ComputeDataType epsilon,
ck_tile::index_t row_size,
void* smem) const
void* smem,
Epilogue) const
{
auto x_window =
make_tile_window(x_window_, Policy::template MakeXBlockTileDistribution<Problem>());
auto gamma_window = make_tile_window(
gamma_window_, Policy::template MakeGammaBlockTileDistribution<Problem>());
auto x_residual_window = make_tile_window(
x_residual_window_, Policy::template MakeXBlockTileDistribution<Problem>());
auto y_residual_window = make_tile_window(
y_residual_window_, Policy::template MakeXBlockTileDistribution<Problem>());
// Problem::BlockShape
static constexpr index_t Block_N = Problem::BlockShape::Block_N;
......@@ -67,15 +89,34 @@ struct Rmsnorm2dFwdPipelineTwoPass
auto block_reduce2d_cross_warp_sync =
Policy::template GetBlockReduce2dCrossWarpSync<Problem>();
using XTensorType = decltype(load_tile(x_window));
auto square_sum = block_reduce2d.template MakeYBlockTile<XTensorType>();
using ComputeTensorType = decltype(cast_tile<ComputeDataType>(load_tile(x_window)));
auto square_sum = block_reduce2d.template MakeYBlockTile<ComputeTensorType>();
set_tile(square_sum, reduce_square_sum_func.GetIdentityValue<ComputeDataType>());
for(int iN = __builtin_amdgcn_readfirstlane(0); iN < num_n_tile_iteration; ++iN)
{
const auto x = load_tile(x_window);
block_reduce2d(x, square_sum, reduce_square_sum_func);
auto x = load_tile(x_window);
auto x_resi = load_tile(x_residual_window);
move_tile_window(x_window, {0, Block_N});
move_tile_window(x_residual_window, {0, Block_N});
auto acc = cast_tile<ComputeDataType>(x);
if constexpr(kFusedAdd == Rmsnorm2dFusedAddEnum::PRE_ADD ||
kFusedAdd == Rmsnorm2dFusedAddEnum::PRE_ADD_STORE)
{
sweep_tile(x_resi, [&](auto idx) {
// compute x = x_resi + x
acc(idx) = type_convert<ComputeDataType>(x_resi(idx)) + acc(idx);
});
if constexpr(kFusedAdd == Rmsnorm2dFusedAddEnum::PRE_ADD_STORE)
{
store_tile(y_residual_window, cast_tile<YResidualDataType>(acc));
move_tile_window(y_residual_window, {0, Block_N});
}
}
block_reduce2d(acc, square_sum, reduce_square_sum_func);
}
block_reduce2d_sync(square_sum, reduce_sum_func);
......@@ -96,33 +137,47 @@ struct Rmsnorm2dFwdPipelineTwoPass
row_size % Block_N == 0 ? row_size - Block_N : row_size - row_size % Block_N;
move_tile_window(x_window, {0, -Block_N});
move_tile_window(x_residual_window, {0, -Block_N});
move_tile_window(gamma_window, {stride_to_right_most_window});
move_tile_window(y_window, {0, stride_to_right_most_window});
// rmsnorm computation
for(int iN = __builtin_amdgcn_readfirstlane(0); iN < num_n_tile_iteration; ++iN)
{
const auto x = load_tile(x_window);
// load gamma/beta (TODO: support no gamma/beta?)
auto x = load_tile(x_window);
auto x_resi = load_tile(x_residual_window);
auto acc = cast_tile<ComputeDataType>(x);
if constexpr(kFusedAdd == Rmsnorm2dFusedAddEnum::PRE_ADD_STORE ||
kFusedAdd == Rmsnorm2dFusedAddEnum::PRE_ADD)
{
sweep_tile(x_resi, [&](auto idx) {
// compute x = x_resi + x
acc(idx) = type_convert<ComputeDataType>(x_resi(idx)) + acc(idx);
});
}
// load gamma (TODO: support no gamma?)
const auto gamma = load_tile(gamma_window);
auto y = make_static_distributed_tensor<YDataType>(x.get_tile_distribution());
sweep_tile(y, [&, inv_rms_ = inv_rms](auto idx) {
// rmsnorm computation
auto rmsn = make_static_distributed_tensor<ComputeDataType>(x.get_tile_distribution());
sweep_tile(rmsn, [&, inv_rms_ = inv_rms](auto idx) {
constexpr auto i_idx = make_tuple(idx[number<0>{}]);
constexpr auto j_idx = make_tuple(idx[number<1>{}]);
const auto gamma_ = type_convert<ComputeDataType>(gamma[j_idx]);
const auto x_ = type_convert<ComputeDataType>(x[idx]);
auto y_ = x_ * inv_rms_[i_idx] * gamma_;
auto rmsn_ = acc(idx) * inv_rms_[i_idx] * gamma_;
y(idx) = type_convert<YDataType>(y_);
rmsn(idx) = rmsn_;
});
store_tile(y_window, y);
static_assert(kFusedQuant == Rmsnorm2dFusedQuantEnum::NO_SWEEP);
Epilogue{}(y_window, rmsn);
move_tile_window(x_window, {0, -Block_N});
move_tile_window(x_residual_window, {0, -Block_N});
move_tile_window(gamma_window, {-Block_N});
move_tile_window(y_window, {0, -Block_N});
}
......
include/ck_tile/ops/rmsnorm2d/pipeline/rmsnorm2d_fwd_traits.hpp 0 → 100644
View file @ a7ae4f8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "ck_tile/core/utility/type_traits.hpp"
namespace ck_tile {
enum class Rmsnorm2dFusedAddEnum
{
NO_ADD = 0,
// fused add before RMSNorm and store result to global
PRE_ADD_STORE = 1,
// fused add before RMSNorm, but not store result
PRE_ADD = 2,
};
// clang-format off
template<Rmsnorm2dFusedAddEnum> struct Rmsnorm2dFusedAddEnumName;
template<> struct Rmsnorm2dFusedAddEnumName<Rmsnorm2dFusedAddEnum::NO_ADD> { static constexpr const char * name = "no"; };
template<> struct Rmsnorm2dFusedAddEnumName<Rmsnorm2dFusedAddEnum::PRE_ADD_STORE> { static constexpr const char * name = "pras"; };
template<> struct Rmsnorm2dFusedAddEnumName<Rmsnorm2dFusedAddEnum::PRE_ADD> { static constexpr const char * name = "pra"; };
// clang-format on
enum class Rmsnorm2dFusedQuantEnum
{
NO_SWEEP = 0,
SMOOTH_DYNAMIC_QUANT = 1, // smooth oulier + rowwise quant, need input x-scale and store y_scale
DYNAMIC_QUANT = 2, // rowwise quant, store out a y-scale
};
// clang-format off
template<Rmsnorm2dFusedQuantEnum> struct Rmsnorm2dFusedQuantEnumName;
template<> struct Rmsnorm2dFusedQuantEnumName<Rmsnorm2dFusedQuantEnum::NO_SWEEP> { static constexpr const char * name = "no"; };
template<> struct Rmsnorm2dFusedQuantEnumName<Rmsnorm2dFusedQuantEnum::DYNAMIC_QUANT> { static constexpr const char * name = "dqt"; };
template<> struct Rmsnorm2dFusedQuantEnumName<Rmsnorm2dFusedQuantEnum::SMOOTH_DYNAMIC_QUANT> { static constexpr const char * name = "smdqt"; };
// clang-format on
template <bool kPadN_,
bool kSaveInvRms_,
bool kTwoPass_,
Rmsnorm2dFusedAddEnum kFusedAdd_,
Rmsnorm2dFusedQuantEnum kFusedQuant_>
struct Rmsnorm2dFwdTraits
{
static constexpr bool kPadN = kPadN_;
static constexpr bool kSaveInvRms = kSaveInvRms_;
static constexpr bool kTwoPass = kTwoPass_;
static constexpr Rmsnorm2dFusedAddEnum kFusedAdd = kFusedAdd_;
static constexpr Rmsnorm2dFusedQuantEnum kFusedQuant = kFusedQuant_;
};
} // namespace ck_tile
include/ck_tile/ops/smoothquant/kernel/moe_smoothquant_kernel.hpp
View file @ a7ae4f8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
......@@ -12,7 +12,7 @@ namespace ck_tile {
struct MoeSmoothquantHostArgs
{
const void* p_x; // [tokens ,hidden_size], input, fp16/bf16
const void* p_xscale; // [experts, hidden_size], input, columnwise scale, fp32
const void* p_smscale; // [experts, hidden_size], input, columnwise scale, fp32
const void* p_topk_ids; // [tokens, topk]
void* p_yscale; // [topk * tokens, 1], output, rowwise quant scale
......@@ -33,11 +33,11 @@ struct MoeSmoothquant
using Pipeline = remove_cvref_t<Pipeline_>;
using Problem = typename Pipeline::Problem;
using XDataType = remove_cvref_t<typename Problem::XDataType>;
using XScaleDataType = remove_cvref_t<typename Problem::XScaleDataType>;
using ComputeDataType = remove_cvref_t<typename Problem::ComputeDataType>;
using YScaleDataType = remove_cvref_t<typename Problem::YScaleDataType>;
using QYDataType = remove_cvref_t<typename Problem::QYDataType>;
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;
......@@ -57,7 +57,7 @@ struct MoeSmoothquant
struct Kargs
{
const void* p_x; // [tokens ,hidden_size], input, fp16/bf16
const void* p_xscale; // [experts, hidden_size], input, columnwise scale, fp32
const void* p_smscale; // [experts, hidden_size], input, columnwise scale, fp32
const void* p_topk_ids; // [tokens, topk]
void* p_yscale; // [topk, tokens, 1], output, rowwise quant scale
......@@ -75,7 +75,7 @@ struct MoeSmoothquant
CK_TILE_HOST static constexpr Kargs MakeKargs(const Hargs& hargs)
{
return Kargs{hargs.p_x,
hargs.p_xscale,
hargs.p_smscale,
hargs.p_topk_ids,
hargs.p_yscale,
hargs.p_qy,
......@@ -101,6 +101,7 @@ struct MoeSmoothquant
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"; };
template <> struct t2s<ck_tile::int8_t> { static constexpr const char * name = "i8"; };
// clang-format on
// in byte
......@@ -118,7 +119,7 @@ struct MoeSmoothquant
#define _SS_ std::string
#define _TS_ std::to_string
return _SS_("moe_smoothquant_") + _SS_(t2s<XDataType>::name) + "_" +
return _SS_("moe_smoothquant_") + _SS_(t2s<XDataType>::name) + "_" + _SS_(t2s<QYDataType>::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;
......@@ -153,9 +154,10 @@ struct MoeSmoothquant
}();
// [experts, hidden_size],
const auto xscale_window = [&]() {
const auto smscale_window = [&]() {
const auto tmp_ = make_naive_tensor_view<address_space_enum::global>(
static_cast<const XScaleDataType*>(kargs.p_xscale) + i_expert * kargs.hidden_size,
static_cast<const SmoothScaleDataType*>(kargs.p_smscale) +
i_expert * kargs.hidden_size,
make_tuple(kargs.hidden_size),
make_tuple(1),
number<Vector_N>{},
......@@ -198,7 +200,7 @@ struct MoeSmoothquant
__shared__ char smem[GetSmemSize()];
Pipeline{}(x_window, xscale_window, yscale_window, qy_window, kargs.hidden_size, smem);
Pipeline{}(x_window, smscale_window, yscale_window, qy_window, kargs.hidden_size, smem);
}
};
......
include/ck_tile/ops/smoothquant/kernel/smoothquant_kernel.hpp
View file @ a7ae4f8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
......@@ -11,11 +11,11 @@ namespace ck_tile {
// host side args
struct SmoothquantHostArgs
{
const void* p_x; // [m ,n], input, fp16/bf16
const void* p_xscale; // [1, n], input, columnwise scale, fp32
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_xscale)
void* p_qy; // [m, n], output, p_x * p_xscale / p_yscale
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;
......@@ -30,11 +30,11 @@ struct Smoothquant
using Pipeline = remove_cvref_t<Pipeline_>;
using Problem = typename Pipeline::Problem;
using XDataType = remove_cvref_t<typename Problem::XDataType>;
using XScaleDataType = remove_cvref_t<typename Problem::XScaleDataType>;
using ComputeDataType = remove_cvref_t<typename Problem::ComputeDataType>;
using YScaleDataType = remove_cvref_t<typename Problem::YScaleDataType>;
using QYDataType = remove_cvref_t<typename Problem::QYDataType>;
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;
......@@ -52,7 +52,7 @@ struct Smoothquant
struct Kargs
{
const void* p_x;
const void* p_xscale;
const void* p_smscale;
void* p_yscale;
void* p_qy;
......@@ -67,7 +67,7 @@ struct Smoothquant
CK_TILE_HOST static constexpr Kargs MakeKargs(const Hargs& hargs)
{
return Kargs{hargs.p_x,
hargs.p_xscale,
hargs.p_smscale,
hargs.p_yscale,
hargs.p_qy,
hargs.m,
......@@ -134,9 +134,9 @@ struct Smoothquant
tmp2_, make_tuple(number<Block_M>{}, number<Block_N>{}), {iM, 0});
}();
const auto xscale_window = [&]() {
const auto smscale_window = [&]() {
const auto tmp_ = make_naive_tensor_view<address_space_enum::global>(
static_cast<const XScaleDataType*>(kargs.p_xscale),
static_cast<const SmoothScaleDataType*>(kargs.p_smscale),
make_tuple(kargs.n),
make_tuple(1),
number<Vector_N>{},
......@@ -177,7 +177,7 @@ struct Smoothquant
__shared__ char smem[GetSmemSize()];
Pipeline{}(x_window, xscale_window, yscale_window, qy_window, kargs.n, smem);
Pipeline{}(x_window, smscale_window, yscale_window, qy_window, kargs.n, smem);
}
};
......
include/ck_tile/ops/smoothquant/pipeline/smoothquant_pipeline_default_policy.hpp
View file @ a7ae4f8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
......@@ -28,7 +28,7 @@ struct SmoothquantPipelineDefaultPolicy
}
template <typename Problem>
CK_TILE_DEVICE static constexpr auto MakeXScaleBlockTileDistribution()
CK_TILE_DEVICE static constexpr auto MakeSmoothScaleBlockTileDistribution()
{
using S = typename Problem::BlockShape;
......
include/ck_tile/ops/smoothquant/pipeline/smoothquant_pipeline_one_pass.hpp
View file @ a7ae4f8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
......@@ -16,11 +16,11 @@ struct SmoothquantPipelineOnePass
using Problem = ck_tile::remove_cvref_t<Problem_>;
using Policy = ck_tile::remove_cvref_t<Policy_>;
using XDataType = ck_tile::remove_cvref_t<typename Problem::XDataType>;
using XScaleDataType = ck_tile::remove_cvref_t<typename Problem::XScaleDataType>;
using ComputeDataType = ck_tile::remove_cvref_t<typename Problem::ComputeDataType>;
using QYDataType = ck_tile::remove_cvref_t<typename Problem::QYDataType>;
using YScaleDataType = ck_tile::remove_cvref_t<typename Problem::YScaleDataType>;
using XDataType = ck_tile::remove_cvref_t<typename Problem::XDataType>;
using SmoothScaleDataType = ck_tile::remove_cvref_t<typename Problem::SmoothScaleDataType>;
using ComputeDataType = ck_tile::remove_cvref_t<typename Problem::ComputeDataType>;
using QYDataType = ck_tile::remove_cvref_t<typename Problem::QYDataType>;
using YScaleDataType = ck_tile::remove_cvref_t<typename Problem::YScaleDataType>;
static constexpr bool kNeedCrossWarpSync = Problem::kNeedCrossWarpSync;
static constexpr bool kPadM = false; // TODO - BlockSmoothquantProblem::kPadM
......@@ -39,9 +39,12 @@ struct SmoothquantPipelineOnePass
return Policy::template GetSmemSize<Problem>();
}
template <typename XWindow, typename XScaleWindow, typename QYWindow, typename YScaleWindow>
template <typename XWindow,
typename SmoothScaleWindow,
typename QYWindow,
typename YScaleWindow>
CK_TILE_DEVICE auto operator()(const XWindow& x_window_,
const XScaleWindow& xscale_window_,
const SmoothScaleWindow& smscale_window_,
YScaleWindow& yscale_window,
QYWindow& qy_window,
ck_tile::index_t,
......@@ -49,8 +52,8 @@ struct SmoothquantPipelineOnePass
{
auto x_window =
make_tile_window(x_window_, Policy::template MakeXBlockTileDistribution<Problem>());
auto xscale_window = make_tile_window(
xscale_window_, Policy::template MakeXScaleBlockTileDistribution<Problem>());
auto smscale_window = make_tile_window(
smscale_window_, Policy::template MakeSmoothScaleBlockTileDistribution<Problem>());
auto reduce_absmax_func = ReduceOp::AbsMax{};
auto reduce_absmax3_func = [](auto acc_, auto v_0_, auto v_1_) {
......@@ -67,14 +70,14 @@ struct SmoothquantPipelineOnePass
auto block_reduce2d_cross_warp_sync =
Policy::template GetBlockReduce2dCrossWarpSync<Problem>();
const auto x = load_tile(x_window);
const auto xscale = load_tile(xscale_window);
auto y = tile_elementwise_in(
const auto x = load_tile(x_window);
const auto smscale = load_tile(smscale_window);
auto y = tile_elementwise_in(
[&](const auto& a, const auto& b) {
return type_convert<ComputeDataType>(a) * type_convert<ComputeDataType>(b);
},
x,
xscale);
smscale);
// compute absmax, cross-lane->cross-warp
auto absmax = [&]() {
......@@ -110,7 +113,7 @@ struct SmoothquantPipelineOnePass
sweep_tile(qy, [&](auto idx) {
constexpr auto i_idx = make_tuple(idx[number<0>{}]);
auto qy_ = y[idx] / yscale[i_idx];
qy(idx) = saturates<QYDataType>{}(qy_);
qy(idx) = type_convert<QYDataType>(saturates<QYDataType>{}(qy_));
});
store_tile(qy_window, qy);
}
......
include/ck_tile/ops/smoothquant/pipeline/smoothquant_pipeline_problem.hpp
View file @ a7ae4f8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
......@@ -7,9 +7,9 @@
namespace ck_tile {
// Y = X * XScale, QY = RowwiseDynamicQuant(Y) = SaturateCast(Y / YScale)
// Y = X * SmoothScale, QY = RowwiseDynamicQuant(Y) = SaturateCast(Y / YScale)
template <typename XDataType_,
typename XScaleDataType_,
typename SmoothScaleDataType_,
typename ComputeDataType_,
typename YScaleDataType_,
typename QYDataType_,
......@@ -18,12 +18,12 @@ template <typename XDataType_,
bool kTwoPass_>
struct SmoothquantPipelineProblem
{
using XDataType = remove_cvref_t<XDataType_>;
using XScaleDataType = remove_cvref_t<XScaleDataType_>;
using ComputeDataType = remove_cvref_t<ComputeDataType_>;
using YScaleDataType = remove_cvref_t<YScaleDataType_>;
using QYDataType = remove_cvref_t<QYDataType_>;
using BlockShape = remove_cvref_t<BlockShape_>;
using XDataType = remove_cvref_t<XDataType_>;
using SmoothScaleDataType = remove_cvref_t<SmoothScaleDataType_>;
using ComputeDataType = remove_cvref_t<ComputeDataType_>;
using YScaleDataType = remove_cvref_t<YScaleDataType_>;
using QYDataType = remove_cvref_t<QYDataType_>;
using BlockShape = remove_cvref_t<BlockShape_>;
static constexpr bool kNeedCrossLaneSync = BlockShape::ThreadPerWarp_N > 1;
static constexpr bool kNeedCrossWarpSync = BlockShape::WarpPerBlock_N > 1;
......
include/ck_tile/ops/smoothquant/pipeline/smoothquant_pipeline_two_pass.hpp
View file @ a7ae4f8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
......@@ -16,11 +16,11 @@ struct SmoothquantPipelineTwoPass
using Problem = ck_tile::remove_cvref_t<Problem_>;
using Policy = ck_tile::remove_cvref_t<Policy_>;
using XDataType = ck_tile::remove_cvref_t<typename Problem::XDataType>;
using XScaleDataType = ck_tile::remove_cvref_t<typename Problem::XScaleDataType>;
using ComputeDataType = ck_tile::remove_cvref_t<typename Problem::ComputeDataType>;
using QYDataType = ck_tile::remove_cvref_t<typename Problem::QYDataType>;
using YScaleDataType = ck_tile::remove_cvref_t<typename Problem::YScaleDataType>;
using XDataType = ck_tile::remove_cvref_t<typename Problem::XDataType>;
using SmoothScaleDataType = ck_tile::remove_cvref_t<typename Problem::SmoothScaleDataType>;
using ComputeDataType = ck_tile::remove_cvref_t<typename Problem::ComputeDataType>;
using QYDataType = ck_tile::remove_cvref_t<typename Problem::QYDataType>;
using YScaleDataType = ck_tile::remove_cvref_t<typename Problem::YScaleDataType>;
static constexpr bool kNeedCrossWarpSync = Problem::kNeedCrossWarpSync;
static constexpr bool kPadM = false; // TODO - BlockSmoothquantProblem::kPadM
......@@ -39,9 +39,12 @@ struct SmoothquantPipelineTwoPass
return Policy::template GetSmemSize<Problem>();
}
template <typename XWindow, typename XScaleWindow, typename QYWindow, typename YScaleWindow>
template <typename XWindow,
typename SmoothScaleWindow,
typename QYWindow,
typename YScaleWindow>
CK_TILE_DEVICE auto operator()(const XWindow& x_window_,
const XScaleWindow& xscale_window_,
const SmoothScaleWindow& smscale_window_,
YScaleWindow& yscale_window,
QYWindow& qy_window,
ck_tile::index_t row_size,
......@@ -49,8 +52,8 @@ struct SmoothquantPipelineTwoPass
{
auto x_window =
make_tile_window(x_window_, Policy::template MakeXBlockTileDistribution<Problem>());
auto xscale_window = make_tile_window(
xscale_window_, Policy::template MakeXScaleBlockTileDistribution<Problem>());
auto smscale_window = make_tile_window(
smscale_window_, Policy::template MakeSmoothScaleBlockTileDistribution<Problem>());
static constexpr index_t Block_N = Problem::BlockShape::Block_N;
index_t num_n_tile_iteration =
......@@ -76,14 +79,14 @@ struct SmoothquantPipelineTwoPass
for(int iN = __builtin_amdgcn_readfirstlane(0); iN < num_n_tile_iteration; ++iN)
{
const auto x = load_tile(x_window);
const auto xscale = load_tile(xscale_window);
const auto y = tile_elementwise_in(
const auto x = load_tile(x_window);
const auto smscale = load_tile(smscale_window);
const auto y = tile_elementwise_in(
[&](const auto& a, const auto& b) {
return type_convert<ComputeDataType>(a) * type_convert<ComputeDataType>(b);
},
x,
xscale);
smscale);
constexpr auto x_size_per_row =
x.get_tile_distribution().get_ys_to_d_descriptor().get_lengths().at(number<1>{});
......@@ -94,7 +97,7 @@ struct SmoothquantPipelineTwoPass
block_reduce2d(y, absmax, reduce_absmax_func);
move_tile_window(x_window, {0, Block_N});
move_tile_window(xscale_window, {Block_N});
move_tile_window(smscale_window, {Block_N});
}
// compute absmax, cross-lane->cross-warp
......@@ -114,31 +117,31 @@ struct SmoothquantPipelineTwoPass
row_size % Block_N == 0 ? row_size - Block_N : row_size - row_size % Block_N;
move_tile_window(x_window, {0, -Block_N});
move_tile_window(xscale_window, {-Block_N});
move_tile_window(smscale_window, {-Block_N});
move_tile_window(qy_window, {0, stride_to_right_most_window});
// recompute y and quantize y to qy
for(int iN = __builtin_amdgcn_readfirstlane(0); iN < num_n_tile_iteration; ++iN)
{
const auto x = load_tile(x_window);
const auto xscale = load_tile(xscale_window);
const auto y = tile_elementwise_in(
const auto x = load_tile(x_window);
const auto smscale = load_tile(smscale_window);
const auto y = tile_elementwise_in(
[&](const auto& a, const auto& b) {
return type_convert<ComputeDataType>(a) * type_convert<ComputeDataType>(b);
},
x,
xscale);
smscale);
auto qy = make_static_distributed_tensor<QYDataType>(y.get_tile_distribution());
sweep_tile(qy, [&](auto idx) {
constexpr auto i_idx = make_tuple(idx[number<0>{}]);
auto qy_ = y[idx] / yscale[i_idx];
qy(idx) = saturates<QYDataType>{}(qy_);
qy(idx) = type_convert<QYDataType>(saturates<QYDataType>{}(qy_));
});
store_tile(qy_window, qy);
move_tile_window(x_window, {0, -Block_N});
move_tile_window(xscale_window, {0, -Block_N});
move_tile_window(smscale_window, {0, -Block_N});
move_tile_window(qy_window, {0, -Block_N});
}
}
......
library/include/ck/library/reference_tensor_operation/cpu/reference_fpAintB_gemm.hpp
View file @ a7ae4f8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
......@@ -73,39 +73,9 @@ struct ReferencefpAintBGemm : public device::BaseOperator
ScaleDataType v_scale;
ADataType v_converted_b;
// use PassThrough instead of ConvertBF16RTN for reference calculation
if constexpr(is_same_v<AElementwiseOperation,
ck::tensor_operation::element_wise::ConvertBF16RTN>)
{
ck::tensor_operation::element_wise::PassThrough{}(v_a, arg.a_m_k_(m, k));
}
else
{
arg.a_element_op_(v_a, arg.a_m_k_(m, k));
}
// same for B matrix
if constexpr(is_same_v<BElementwiseOperation,
ck::tensor_operation::element_wise::ConvertBF16RTN>)
{
ck::tensor_operation::element_wise::PassThrough{}(v_b, arg.b_k_n_(k, n));
}
else
{
arg.b_element_op_(v_b, arg.b_k_n_(k, n));
}
// same for scale matrix
if constexpr(is_same_v<BElementwiseOperation,
ck::tensor_operation::element_wise::ConvertBF16RTN>)
{
ck::tensor_operation::element_wise::PassThrough{}(v_scale,
arg.scale_k_n_(k, n));
}
else
{
arg.b_element_op_(v_scale, arg.scale_k_n_(k, n));
}
arg.a_element_op_(v_a, arg.a_m_k_(m, k));
arg.b_element_op_(v_b, arg.b_k_n_(k, n));
arg.b_element_op_(v_scale, arg.scale_k_n_(k, n));
v_converted_b = type_convert<ADataType>(v_b) * v_scale;
v_acc += ck::type_convert<AccDataType>(v_a) *
......
library/include/ck/library/reference_tensor_operation/cpu/reference_gemm.hpp
View file @ a7ae4f8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
......@@ -68,13 +68,7 @@ struct ReferenceGemm : public device::BaseOperator
for(int k = 0; k < K; ++k)
{
// use PassThrough instead of ConvertBF16RTN for reference calculation
if constexpr(is_same_v<AElementwiseOperation,
ck::tensor_operation::element_wise::ConvertBF16RTN>)
{
ck::tensor_operation::element_wise::PassThrough{}(v_a, arg.a_m_k_(m, k));
}
else if constexpr(is_same_v<ADataType, pk_i4_t>)
if constexpr(is_same_v<ADataType, pk_i4_t>)
{
uint8_t i4x2 = arg.a_m_k_(m, k).data;
int8_t i4 = 0;
......@@ -89,13 +83,8 @@ struct ReferenceGemm : public device::BaseOperator
{
arg.a_element_op_(v_a, arg.a_m_k_(m, k));
}
// same for B matrix
if constexpr(is_same_v<BElementwiseOperation,
ck::tensor_operation::element_wise::ConvertBF16RTN>)
{
ck::tensor_operation::element_wise::PassThrough{}(v_b, arg.b_k_n_(k, n));
}
else if constexpr(is_same_v<BDataType, pk_i4_t>)
if constexpr(is_same_v<BDataType, pk_i4_t>)
{
uint8_t i4x2 = arg.b_k_n_(k, n).data;
int8_t i4 = 0;
......
library/include/ck/library/reference_tensor_operation/cpu/reference_gemm_multiple_d.hpp
View file @ a7ae4f8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
......@@ -74,26 +74,8 @@ struct ReferenceGemmMultipleD : public device::BaseOperator
for(int k = 0; k < K; ++k)
{
// use PassThrough instead of ConvertBF16RTN for reference calculation
if constexpr(is_same_v<AElementwiseOperation,
ck::tensor_operation::element_wise::ConvertBF16RTN>)
{
ck::tensor_operation::element_wise::PassThrough{}(v_a, arg.a_m_k_(m, k));
}
else
{
arg.a_element_op_(v_a, arg.a_m_k_(m, k));
}
// same for B matrix
if constexpr(is_same_v<BElementwiseOperation,
ck::tensor_operation::element_wise::ConvertBF16RTN>)
{
ck::tensor_operation::element_wise::PassThrough{}(v_b, arg.b_k_n_(k, n));
}
else
{
arg.b_element_op_(v_b, arg.b_k_n_(k, n));
}
arg.a_element_op_(v_a, arg.a_m_k_(m, k));
arg.b_element_op_(v_b, arg.b_k_n_(k, n));
v_acc +=
ck::type_convert<AccDataType>(v_a) * ck::type_convert<AccDataType>(v_b);
......
library/include/ck/library/tensor_operation_instance/gpu/grouped_gemm_fixed_nk.hpp
View file @ a7ae4f8e
......@@ -126,6 +126,35 @@ void add_device_grouped_gemm_xdl_fixed_nk_bf16_i8_bf16_mk_nk_mn_instances(
PassThrough>>>& instances);
#endif
// bf16_inputA bf16_inputB
#if defined(CK_ENABLE_BF16)
void add_device_grouped_gemm_xdl_fixed_nk_bf16_bf16_bf16_mk_kn_mn_instances(
std::vector<std::unique_ptr<DeviceGroupedGemmFixedNK<Row,
Row,
Empty_Tuple,
Row,
BF16,
BF16,
Empty_Tuple,
BF16,
PassThrough,
PassThrough,
PassThrough>>>& instances);
void add_device_grouped_gemm_xdl_fixed_nk_bf16_bf16_bf16_mk_nk_mn_instances(
std::vector<std::unique_ptr<DeviceGroupedGemmFixedNK<Row,
Col,
Empty_Tuple,
Row,
BF16,
BF16,
Empty_Tuple,
BF16,
PassThrough,
PassThrough,
PassThrough>>>& instances);
#endif // CK_ENABLE_BF16
template <typename ALayout,
typename BLayout,
typename ELayout,
......@@ -227,6 +256,24 @@ struct DeviceOperationInstanceFactory<
}
#endif
// bf16_inputA bf16_inputB
#if defined(CK_ENABLE_BF16)
if constexpr(is_same_v<ADataType, bhalf_t> && is_same_v<BDataType, bhalf_t> &&
is_same_v<EDataType, bhalf_t>)
{
if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
is_same_v<ELayout, Row>)
{
add_device_grouped_gemm_xdl_fixed_nk_bf16_bf16_bf16_mk_kn_mn_instances(op_ptrs);
}
if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Col> &&
is_same_v<ELayout, Row>)
{
add_device_grouped_gemm_xdl_fixed_nk_bf16_bf16_bf16_mk_nk_mn_instances(op_ptrs);
}
}
#endif // CK_ENABLE_BF16
return op_ptrs;
}
};
......
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