mirror of
https://github.com/ROCm/composable_kernel.git
synced 2026-05-03 05:01:25 +00:00
[CK_TILE] Implement Row/Col quant grouped gemm (#2786)
* Add cshuffle epilogue test * add the poc implementation to the epilogue and tests * refactor cshuffle epilogue * WIP: adding tensor/tile usage to scale_tile * fix usage of tile_elementwise_inout * add gemm_quant_kernel for generalizing gemm quant kernel * Add problem specific to different quants, add QuantType to Traits * Add quant_type to quant_kernel template parameters * Create aq/bq_block_windows and views depending on QuantType * Use tile windows as inputs in cshuffle epilogue * Fix some issues in epilogue * initial new example code for new general gemm quant kernel test * Fix issues in kernel * Add verification check for rowcol Quantmode * use AccDataType instead of AQ in pipeline * fix aquant preshuffle * fix formatting * some cleanup * remove gemm_aquant_basic.cpp * remove gemm_aquant_kernel.hpp * fix tests for the renamed quant kernel * fix formatting * clean example files * fix some merge conflicts * fix preshufflequant rename issue * updating * fix some templates after merging with develop * fix test preshuffle parameter * fix formatting * updating kernels * change update user * test username * update quant_grouped_gemm example * update example * Unify bquant kernel to the common quant kernel * remove bquant kernel also from common header * fix formatting * clean up commented code * update grouped_gemm_quant example * fix formatting config hpp * fix merge mistake * Non-const for movable windows * fix formatting * update tileloop pipleline * Fix grammar in README Co-authored-by: spolifroni-amd <Sandra.Polifroni@amd.com> * Remove #include<bit> and clean up example * fix strides * Add some descriptions for move_windows * fix tensor print bug * update quant_grouped_gemm example * remove useless code * cleanup code * clean up code & format code * fix compile & running bug in grouped_gemm example --------- Co-authored-by: Sami Remes <samremes@amd.com> Co-authored-by: Mohsen Saffari <mohsen.saffari@amd.com> Co-authored-by: liyingli <liyingli@amd.com> Co-authored-by: kyle-256 <Kyle.Zhao@amd.com> Co-authored-by: spolifroni-amd <Sandra.Polifroni@amd.com>
This commit is contained in:
kyle-256
@@ -769,12 +769,11 @@ struct QuantGemmKernel
|
||||
CK_TILE_DEVICE static auto
|
||||
MakeGemmTileWindows(const PadView& views, const index_t i_m, const index_t i_n)
|
||||
{
|
||||
const auto& a_pad_view = views.at(I0);
|
||||
const auto& aq_pad_view = views.at(I1);
|
||||
const auto& b_pad_view = views.at(I2);
|
||||
const auto& bq_pad_view = views.at(I3);
|
||||
const auto& c_pad_view = views.at(I4);
|
||||
|
||||
const auto& a_pad_view = views.at(I0);
|
||||
const auto& aq_pad_view = views.at(I1);
|
||||
const auto& b_pad_view = views.at(I2);
|
||||
const auto& bq_pad_view = views.at(I3);
|
||||
const auto& c_pad_view = views.at(I4);
|
||||
const auto& a_block_window = [&]() {
|
||||
if constexpr(std::is_same_v<ALayout, tensor_layout::gemm::RowMajor>)
|
||||
{
|
||||
|
||||
@@ -0,0 +1,433 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2024-2025, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#pragma once
|
||||
|
||||
#include "ck_tile/core/numeric/math.hpp"
|
||||
#include "ck_tile/core/utility/literals.hpp"
|
||||
#include "ck_tile/core/utility/type_traits.hpp"
|
||||
#include "ck_tile/host/stream_utils.hpp"
|
||||
#include "ck_tile/ops/gemm/pipeline/gemm_pipeline_ag_bg_cr_comp_v3.hpp"
|
||||
#include "ck_tile/ops/gemm/pipeline/gemm_pipeline_ag_bg_cr_scheduler.hpp"
|
||||
#include "ck_tile/ops/gemm_group_quant/kernel/gemm_quant_kernel.hpp"
|
||||
#include "ck_tile/host.hpp"
|
||||
|
||||
#include <hip/hip_runtime.h>
|
||||
|
||||
namespace ck_tile {
|
||||
|
||||
/// @brief The Grouped GEMM kernel host arguments.
|
||||
///
|
||||
/// @par Overview
|
||||
/// This structure is passed to @ref GroupedGemmKernel "GroupedGemmKernel" when creating kernel
|
||||
/// arguments object. It contain all necessary information required to build proper kernel
|
||||
/// argument and launch kernel on GPU. This structure defines the GEMM problem configuration by
|
||||
/// stating all required information like M,N,K sizes and respective strides.
|
||||
struct QuantGroupedGemmHostArgs
|
||||
{
|
||||
CK_TILE_HOST QuantGroupedGemmHostArgs(const void* a_ptr_,
|
||||
const void* b_ptr_,
|
||||
void* e_ptr_,
|
||||
const void* aq_ptr_,
|
||||
const void* bq_ptr_,
|
||||
index_t k_batch_,
|
||||
index_t M_,
|
||||
index_t N_,
|
||||
index_t K_,
|
||||
index_t QK_A_,
|
||||
index_t QK_B_,
|
||||
index_t stride_A_,
|
||||
index_t stride_B_,
|
||||
index_t stride_E_,
|
||||
index_t stride_AQ_,
|
||||
index_t stride_BQ_)
|
||||
: a_ptr(a_ptr_),
|
||||
b_ptr(b_ptr_),
|
||||
aq_ptr(aq_ptr_),
|
||||
bq_ptr(bq_ptr_),
|
||||
e_ptr(e_ptr_),
|
||||
M(M_),
|
||||
N(N_),
|
||||
K(K_),
|
||||
QK_A(QK_A_),
|
||||
QK_B(QK_B_),
|
||||
stride_A(stride_A_),
|
||||
stride_B(stride_B_),
|
||||
stride_AQ(stride_AQ_),
|
||||
stride_BQ(stride_BQ_),
|
||||
stride_E(stride_E_),
|
||||
k_batch(k_batch_)
|
||||
{
|
||||
}
|
||||
|
||||
const void* a_ptr;
|
||||
const void* b_ptr;
|
||||
const void* aq_ptr;
|
||||
const void* bq_ptr;
|
||||
union
|
||||
{
|
||||
void* e_ptr;
|
||||
void* c_ptr;
|
||||
};
|
||||
|
||||
index_t M;
|
||||
index_t N;
|
||||
index_t K;
|
||||
index_t QK_A;
|
||||
index_t QK_B;
|
||||
index_t stride_A;
|
||||
index_t stride_B;
|
||||
index_t stride_AQ;
|
||||
index_t stride_BQ;
|
||||
|
||||
union
|
||||
{
|
||||
index_t stride_E;
|
||||
index_t stride_C;
|
||||
};
|
||||
|
||||
index_t k_batch;
|
||||
};
|
||||
|
||||
using QuantGroupedGemmKernelArgs = QuantGemmKernelArgs;
|
||||
|
||||
struct QuantGemmTransKernelArg
|
||||
{
|
||||
QuantGroupedGemmKernelArgs group_karg;
|
||||
ck_tile::index_t block_start;
|
||||
ck_tile::index_t block_end;
|
||||
|
||||
QuantGemmTransKernelArg() = delete;
|
||||
QuantGemmTransKernelArg(QuantGroupedGemmKernelArgs&& karg, index_t bl_start, index_t bl_end)
|
||||
: group_karg{karg}, block_start{bl_start}, block_end{bl_end}
|
||||
{
|
||||
}
|
||||
|
||||
QuantGemmTransKernelArg(QuantGroupedGemmKernelArgs&& karg)
|
||||
: group_karg{karg}, block_start{0}, block_end{0}
|
||||
{
|
||||
}
|
||||
};
|
||||
|
||||
template <typename TilePartitioner_,
|
||||
typename GemmPipeline_,
|
||||
typename EpiloguePipeline_,
|
||||
QuantType QuantType_>
|
||||
struct QuantGroupedGemmKernel
|
||||
{
|
||||
/// @brief Inject the UniversalGemmKernel base class to support execution of all necessary
|
||||
/// functions.
|
||||
using Base = QuantGemmKernel<TilePartitioner_, GemmPipeline_, EpiloguePipeline_, QuantType_>;
|
||||
|
||||
using TilePartitioner = remove_cvref_t<TilePartitioner_>;
|
||||
using GemmPipeline = remove_cvref_t<GemmPipeline_>;
|
||||
using EpiloguePipeline = remove_cvref_t<EpiloguePipeline_>;
|
||||
|
||||
//// @brief Specify the layout configurations for A, B, C/E
|
||||
using ALayout = remove_cvref_t<typename GemmPipeline::ALayout>;
|
||||
using BLayout = remove_cvref_t<typename GemmPipeline::BLayout>;
|
||||
using CLayout = remove_cvref_t<typename GemmPipeline::CLayout>;
|
||||
|
||||
/// @brief Specify the data type configurations for A, B, C/E
|
||||
using ADataType = remove_cvref_t<typename GemmPipeline::ADataType>;
|
||||
using BDataType = remove_cvref_t<typename GemmPipeline::BDataType>;
|
||||
using CDataType = remove_cvref_t<typename EpiloguePipeline::ODataType>;
|
||||
using AccDataType = remove_cvref_t<typename EpiloguePipeline::AccDataType>;
|
||||
|
||||
using AQDataType =
|
||||
remove_cvref_t<typename detail::get_aq_data_type_or<GemmPipeline, AccDataType>::type>;
|
||||
using BQDataType =
|
||||
remove_cvref_t<typename detail::get_bq_data_type_or<GemmPipeline, AccDataType>::type>;
|
||||
|
||||
static constexpr auto kQuantType = QuantType_;
|
||||
|
||||
/// @brief ALayout and ADataType are expected to be scalars, not a tuple.
|
||||
static_assert(
|
||||
!is_detected<is_tuple, ALayout>::value && !is_detected<is_tuple, ADataType>::value,
|
||||
"ALayout and ADataType must be scalars. Multiple parameters are not currently supported.");
|
||||
|
||||
/// @brief BLayout and BDataType are expected to be scalars, not a tuple.
|
||||
static_assert(
|
||||
!is_detected<is_tuple, BLayout>::value && !is_detected<is_tuple, BDataType>::value,
|
||||
"BLayout and BDataType must be scalars. Multiple parameters are not currently supported.");
|
||||
|
||||
/// @brief C/ELayout and C/EDataType are expected to be scalars, not a tuple.
|
||||
static_assert(!is_detected<is_tuple, CLayout>::value &&
|
||||
!is_detected<is_tuple, CDataType>::value,
|
||||
"C/ELayout and C/EDataType must be scalars.");
|
||||
|
||||
using OffsetTile1DPartitioner = OffsettedTile1DPartitioner<TilePartitioner>;
|
||||
using Kernel =
|
||||
QuantGroupedGemmKernel<TilePartitioner, GemmPipeline, EpiloguePipeline, kQuantType>;
|
||||
|
||||
static constexpr index_t kBlockSize = GemmPipeline::BlockSize;
|
||||
static constexpr bool UsePersistentKernel = GemmPipeline::UsePersistentKernel;
|
||||
static_assert(UsePersistentKernel == true, "UsePersistentKernel must be true");
|
||||
|
||||
[[nodiscard]] CK_TILE_HOST static const std::string GetName()
|
||||
{
|
||||
// clang-format off
|
||||
using P_ = GemmPipeline;
|
||||
|
||||
return concat('_', "gemm_grouped", gemm_prec_str<ADataType, BDataType>(),
|
||||
concat('x', P_::MPerBlock, P_::NPerBlock, P_::KPerBlock),
|
||||
concat('x', P_::GetVectorSizeA(), P_::GetVectorSizeB(), P_::GetVectorSizeC()),
|
||||
concat('x', P_::kPadM, P_::kPadN, P_::kPadK),
|
||||
(UsePersistentKernel ? "Persistent" : "NonPersistent"));
|
||||
// clang-format on
|
||||
}
|
||||
|
||||
CK_TILE_HOST static auto
|
||||
GetWorkSpaceSize(const std::vector<QuantGroupedGemmHostArgs>& gemm_descs) -> std::size_t
|
||||
{
|
||||
return gemm_descs.size() * sizeof(QuantGemmTransKernelArg);
|
||||
}
|
||||
|
||||
CK_TILE_HOST static auto GetWorkSpaceSize(index_t group_count) -> std::size_t
|
||||
{
|
||||
return group_count * sizeof(QuantGemmTransKernelArg);
|
||||
}
|
||||
|
||||
CK_TILE_HOST static auto BlockSize() -> dim3
|
||||
{
|
||||
if(is_wave32())
|
||||
{
|
||||
return dim3(kBlockSize / 2);
|
||||
}
|
||||
else
|
||||
{
|
||||
return dim3(kBlockSize);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Get the maximum occupancy grid size for the persistent kernel on the current device.
|
||||
* @return The maximum occupancy grid size.
|
||||
* @note This function queries the maximum occupancy of the kernel using
|
||||
* `hipOccupancyMaxActiveBlocksPerMultiprocessor`.
|
||||
*/
|
||||
CK_TILE_HOST static auto MaxOccupancyGridSize(const stream_config& s) -> dim3
|
||||
{
|
||||
using ConstantPointer = const void CK_CONSTANT_ADDRESS_SPACE*;
|
||||
const auto kernel_func = kentry<1, Kernel, ConstantPointer, index_t>;
|
||||
int occupancy;
|
||||
HIP_CHECK_ERROR(
|
||||
hipOccupancyMaxActiveBlocksPerMultiprocessor(&occupancy, kernel_func, kBlockSize, 0));
|
||||
const int grid_size = get_available_compute_units(s) * occupancy;
|
||||
return dim3(grid_size, 1, 1);
|
||||
}
|
||||
|
||||
CK_TILE_HOST static auto GridSize(const std::vector<QuantGroupedGemmHostArgs>& gemm_descs)
|
||||
{
|
||||
index_t grid_size = 0;
|
||||
for(const auto& it_desc : gemm_descs)
|
||||
{
|
||||
const auto local_grid_size = TilePartitioner::GridSize(it_desc.M, it_desc.N);
|
||||
grid_size += local_grid_size * it_desc.k_batch;
|
||||
}
|
||||
return dim3(grid_size, 1, 1);
|
||||
}
|
||||
|
||||
CK_TILE_HOST static auto MakeKargs(const std::vector<QuantGroupedGemmHostArgs>& gemm_descs)
|
||||
-> std::vector<QuantGemmTransKernelArg>
|
||||
{
|
||||
std::vector<QuantGemmTransKernelArg> gemm_kernel_args_;
|
||||
index_t group_count = ck_tile::type_convert<ck_tile::index_t>(gemm_descs.size());
|
||||
index_t grid_size = 0;
|
||||
gemm_kernel_args_.reserve(group_count);
|
||||
|
||||
for(std::size_t i = 0; i < gemm_descs.size(); ++i)
|
||||
{
|
||||
const index_t M = gemm_descs[i].M;
|
||||
const index_t N = gemm_descs[i].N;
|
||||
const index_t K = gemm_descs[i].K;
|
||||
|
||||
if(M == 0 || N == 0 || K == 0)
|
||||
{
|
||||
continue;
|
||||
}
|
||||
|
||||
const index_t stride_a = gemm_descs[i].stride_A;
|
||||
const index_t stride_b = gemm_descs[i].stride_B;
|
||||
const index_t stride_e = gemm_descs[i].stride_C;
|
||||
|
||||
const index_t grid_size_grp = TilePartitioner::GridSize(M, N) * gemm_descs[i].k_batch;
|
||||
|
||||
const index_t block_start = grid_size;
|
||||
const index_t block_end = grid_size + grid_size_grp;
|
||||
|
||||
grid_size += grid_size_grp;
|
||||
|
||||
auto karg =
|
||||
QuantGroupedGemmKernelArgs{type_convert<const ADataType*>(gemm_descs[i].a_ptr),
|
||||
type_convert<const BDataType*>(gemm_descs[i].b_ptr),
|
||||
type_convert<CDataType*>(gemm_descs[i].e_ptr),
|
||||
type_convert<const AQDataType*>(gemm_descs[i].aq_ptr),
|
||||
type_convert<const BQDataType*>(gemm_descs[i].bq_ptr),
|
||||
gemm_descs[i].k_batch,
|
||||
M,
|
||||
N,
|
||||
K,
|
||||
gemm_descs[i].QK_A,
|
||||
gemm_descs[i].QK_B,
|
||||
stride_a,
|
||||
stride_b,
|
||||
stride_e,
|
||||
gemm_descs[i].stride_AQ,
|
||||
gemm_descs[i].stride_BQ};
|
||||
|
||||
gemm_kernel_args_.emplace_back(std::move(karg), block_start, block_end);
|
||||
}
|
||||
|
||||
return gemm_kernel_args_;
|
||||
}
|
||||
|
||||
CK_TILE_HOST static bool IsSupportedArgument(const std::vector<QuantGemmTransKernelArg>& kargs)
|
||||
{
|
||||
for(const auto& karg : kargs)
|
||||
{
|
||||
if(!Base::IsSupportedArgument(karg.group_karg))
|
||||
{
|
||||
return false;
|
||||
}
|
||||
}
|
||||
return true;
|
||||
}
|
||||
|
||||
CK_TILE_HOST_DEVICE static constexpr auto GetSmemSize() -> index_t
|
||||
{
|
||||
return max(GemmPipeline::GetSmemSize(), EpiloguePipeline::GetSmemSize());
|
||||
}
|
||||
|
||||
CK_TILE_DEVICE void Run(const QuantGroupedGemmKernelArgs& kargs,
|
||||
const tuple<index_t, index_t>& block_idx_2d,
|
||||
const index_t block_idx_z) const
|
||||
{
|
||||
const auto [iM, iN] = block_idx_2d;
|
||||
|
||||
const index_t i_m = __builtin_amdgcn_readfirstlane(iM * TilePartitioner::MPerBlock);
|
||||
const index_t i_n = __builtin_amdgcn_readfirstlane(iN * TilePartitioner::NPerBlock);
|
||||
|
||||
const typename Base::SplitKBatchOffset splitk_batch_offset(kargs, block_idx_z);
|
||||
|
||||
// options
|
||||
const ADataType* a_ptr = static_cast<const ADataType*>(kargs.a_ptr);
|
||||
const BDataType* b_ptr = static_cast<const BDataType*>(kargs.b_ptr);
|
||||
const AQDataType* aq_ptr = static_cast<const AQDataType*>(kargs.aq_ptr);
|
||||
const BQDataType* bq_ptr = static_cast<const BQDataType*>(kargs.bq_ptr);
|
||||
CDataType* c_ptr = static_cast<CDataType*>(kargs.c_ptr);
|
||||
|
||||
static_assert(GemmPipeline::DoubleSmemBuffer == false,
|
||||
"DoubleSmemBuffer needs to be false");
|
||||
// allocate LDS
|
||||
__shared__ char smem_ptr_0[GetSmemSize()];
|
||||
|
||||
RunGemmWithPipelineSelection(
|
||||
a_ptr, b_ptr, aq_ptr, bq_ptr, c_ptr, smem_ptr_0, kargs, splitk_batch_offset, i_m, i_n);
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Runs single GEMM problem cooperatively by whole workgroup.
|
||||
*
|
||||
* @note The GEMM pipeline is selected in-kernel based on the number of K-loops
|
||||
* and the tail-number. This is needed for the persistent tile-loop when
|
||||
* we didn't have access to the K dimension on the host.
|
||||
*
|
||||
* @param a_ptr input A pointer
|
||||
* @param b_ptr input B pointer
|
||||
* @param aq_ptr input AQ pointer
|
||||
* @param bq_ptr input BQ pointer
|
||||
* @param c_ptr output C pointer
|
||||
* @param smem_ptr_0 The start memory pointer of the shared memory block.
|
||||
* @param kargs GEMM kernel arguments
|
||||
* @param splitk_batch_offset splitk_batch_offset Utility structure used to calculate k
|
||||
* batch.
|
||||
* @param block_idx_m The GEMM's output M dimension tile index processed by this workgroup.
|
||||
* @param block_idx_n The GEMM's output N dimension tile index processed by this workgroup.
|
||||
*
|
||||
*/
|
||||
CK_TILE_DEVICE static void
|
||||
RunGemmWithPipelineSelection(const ADataType* a_ptr,
|
||||
const BDataType* b_ptr,
|
||||
const AQDataType* aq_ptr,
|
||||
const BQDataType* bq_ptr,
|
||||
CDataType* c_ptr,
|
||||
void* smem_ptr_0,
|
||||
const QuantGroupedGemmKernelArgs& kargs,
|
||||
const typename Base::SplitKBatchOffset& splitk_batch_offset,
|
||||
const index_t block_idx_m,
|
||||
const index_t block_idx_n)
|
||||
{
|
||||
// Create Gemm tensor views, pad views and tile windows
|
||||
const auto& gemm_tensor_views_tuple =
|
||||
Base::template MakeGemmTensorViews<EpiloguePipeline::MemoryOperation>(
|
||||
a_ptr, b_ptr, aq_ptr, bq_ptr, c_ptr, kargs, splitk_batch_offset);
|
||||
|
||||
const auto& gemm_pad_views = Base::MakeGemmPadViews(gemm_tensor_views_tuple);
|
||||
auto gemm_tile_windows =
|
||||
Base::MakeGemmTileWindows(gemm_pad_views, block_idx_m, block_idx_n);
|
||||
const auto& a_block_window = gemm_tile_windows.at(Base::I0);
|
||||
const auto& b_block_window = gemm_tile_windows.at(Base::I2);
|
||||
|
||||
// Get hot-loop and tail configuration
|
||||
const index_t num_loop = __builtin_amdgcn_readfirstlane(
|
||||
TilePartitioner::GetLoopNum(splitk_batch_offset.splitted_k));
|
||||
const bool has_hot_loop = GemmPipeline::BlockHasHotloop(num_loop);
|
||||
const TailNumber tail_num = GemmPipeline::GetBlockLoopTailNum(num_loop);
|
||||
|
||||
// Run GEMM pipeline
|
||||
const auto& c_block_tile = GemmPipeline{}.template operator()(
|
||||
a_block_window, b_block_window, num_loop, has_hot_loop, tail_num, smem_ptr_0);
|
||||
// Run Epilogue Pipeline
|
||||
auto& c_block_window = gemm_tile_windows.at(Base::I4);
|
||||
if constexpr(kQuantType == QuantType::RowColQuant)
|
||||
{
|
||||
const auto& aq_block_window = gemm_tile_windows.at(Base::I1);
|
||||
const auto& bq_block_window = gemm_tile_windows.at(Base::I3);
|
||||
EpiloguePipeline{}.template
|
||||
operator()<decltype(c_block_window), decltype(c_block_tile), decltype(c_block_window)>(
|
||||
c_block_window,
|
||||
c_block_tile,
|
||||
c_block_window,
|
||||
smem_ptr_0,
|
||||
aq_block_window,
|
||||
bq_block_window);
|
||||
}
|
||||
}
|
||||
|
||||
// For persistent kernels
|
||||
template <bool U = UsePersistentKernel,
|
||||
typename = std::enable_if_t<U>,
|
||||
typename = void> // extra template parameter to avoid redefinition
|
||||
CK_TILE_DEVICE void operator()(const void CK_CONSTANT_ADDRESS_SPACE* gemm_descs_const,
|
||||
const index_t group_count) const
|
||||
{
|
||||
const index_t grid_size = ck_tile::get_grid_size();
|
||||
const auto gemm_desc_ptr = reinterpret_cast<const QuantGemmTransKernelArg*>(
|
||||
cast_pointer_to_generic_address_space(gemm_descs_const));
|
||||
index_t block_id = ck_tile::get_block_1d_id(); // initial block_id
|
||||
index_t cum_grid_size = 0;
|
||||
for(index_t group_id = 0; group_id < group_count; ++group_id)
|
||||
{
|
||||
const auto& kargs = gemm_desc_ptr[group_id].group_karg;
|
||||
const auto& k_batch = kargs.k_batch;
|
||||
const auto block_start = cum_grid_size;
|
||||
cum_grid_size += TilePartitioner::GridSize(kargs.M, kargs.N) * k_batch;
|
||||
while(block_id < cum_grid_size)
|
||||
{
|
||||
const auto grid_size_2d = TilePartitioner::GridSize(kargs.M, kargs.N);
|
||||
const auto block_idx_2d = OffsetTile1DPartitioner::GetOffsetedTileIndex(
|
||||
0, kargs.M, kargs.N, (block_id - block_start) % grid_size_2d);
|
||||
Run(kargs, block_idx_2d, (block_id - block_start) / grid_size_2d);
|
||||
block_id = block_id + grid_size; // advance to next block
|
||||
// NOTE: this check is redundant but helps the compiler avoid spilling some VGPR
|
||||
if(block_id >= cum_grid_size)
|
||||
{
|
||||
break; // exit the loop if all blocks are processed
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
} // namespace ck_tile
|
||||
@@ -23,8 +23,10 @@ template <bool kPadM_,
|
||||
typename BLayout_,
|
||||
typename CLayout_,
|
||||
QuantType QuantType_,
|
||||
typename AQLayout_ = ALayout_,
|
||||
typename BQLayout_ = BLayout_>
|
||||
typename AQLayout_ = ALayout_,
|
||||
typename BQLayout_ = BLayout_,
|
||||
bool DoubleSmemBuffer_ = false,
|
||||
bool UsePersistentKernel_ = false>
|
||||
struct TileGemmQuantTraits
|
||||
{
|
||||
static constexpr bool kPadM = kPadM_;
|
||||
@@ -33,7 +35,8 @@ struct TileGemmQuantTraits
|
||||
|
||||
static constexpr QuantType kQuantType = QuantType_;
|
||||
|
||||
static constexpr int _VectorSize = 16;
|
||||
static constexpr int _VectorSize = 16;
|
||||
static constexpr bool DoubleSmemBuffer = DoubleSmemBuffer_;
|
||||
|
||||
using ALayout = ALayout_;
|
||||
using BLayout = BLayout_;
|
||||
@@ -44,6 +47,7 @@ struct TileGemmQuantTraits
|
||||
static constexpr bool TransposeC = false;
|
||||
static constexpr bool UseStructuredSparsity = false;
|
||||
static constexpr index_t NumWaveGroups = 1;
|
||||
static constexpr bool UsePersistentKernel = UsePersistentKernel_;
|
||||
|
||||
static constexpr bool PreshuffleQuant = PreshuffleQuant_;
|
||||
};
|
||||
|
||||
Reference in New Issue
Block a user