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[Ck_tile] smoothquant (#1617)

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* 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>

[ROCm/composable_kernel commit: fbd654545a]
This commit is contained in:
rocking
2024-11-01 13:51:56 +08:00
committed by GitHub
parent 04610407b0
commit 4faf3ab587
62 changed files with 1758 additions and 219 deletions
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5
example/ck_tile/02_layernorm2d/script/perf_test.sh
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@@ -1,6 +1,5 @@
# run from top of ck folder
EXE=build/bin/tile_example_layernorm2d_fwd
#!/bin/sh
EXE="$(find . -name tile_example_layernorm2d_fwd -type f | head -n 1)"
$EXE -m=1 -n=1 -e=1e-12 -v=1 -prec_i=bf16 -repeat=1000
$EXE -m=700 -n=80 -e=1e-12 -v=1 -prec_i=bf16 -repeat=1000

3
example/ck_tile/02_layernorm2d/script/smoke_test.sh
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@@ -1,6 +1,5 @@
#!/bin/sh
# call from top of CK folder
EXE=./build/bin/tile_example_layernorm2d_fwd
EXE="$(find . -name tile_example_layernorm2d_fwd -type f | head -n 1)"
for fquant in "" "-fquant=1 -prec_o=int8"; do
for pr_i in "fp16" "bf16" ; do

2
example/ck_tile/10_rmsnorm2d/example_rmsnorm2d_fwd.cpp
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@@ -69,7 +69,7 @@ bool run(const ck_tile::ArgParser& arg_parser)
using WarpTile = ck_tile::sequence<1, 64>;
using Vector = ck_tile::sequence<1, 1>;
using Shape = ck_tile::Rmsnorm2dShape<BlockTile, BlockWarps, WarpTile, Vector>;
using Shape = ck_tile::Generic2dBlockShape<BlockTile, BlockWarps, WarpTile, Vector>;
using Problem = ck_tile::Rmsnorm2dFwdPipelineProblem<XDataType,
GammaDataType,
ComputeDataType,

9
example/ck_tile/10_rmsnorm2d/instances/rmsnorm2d_fwd_api.cpp
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@@ -28,7 +28,6 @@ float rmsnorm2d_fwd_b16_(rmsnorm2d_fwd_traits /*t*/,
rmsnorm2d_fwd_args a,
const ck_tile::stream_config& s)
{
#if 1
float r = -1;
// clang-format off
// rm rn tm tn vn pd rms 2p
@@ -128,16 +127,12 @@ float rmsnorm2d_fwd_b16_(rmsnorm2d_fwd_traits /*t*/,
r = rmsnorm2d_fwd_<trait_<data_type, 1, 4, 1, 1024, 1, true, false, true>>(s, a);
}
return r;
#else
return rmsnorm2d_fwd_<trait_<data_type, 1, 1, 1, 256, 4, true, false, false>>(s, a);
#endif
// clang-format on
}
float rmsnorm2d_fwd(rmsnorm2d_fwd_traits t, rmsnorm2d_fwd_args a, const ck_tile::stream_config& s)
{
float r = -1;
if(t.data_type.compare("fp16") == 0)
{
return rmsnorm2d_fwd_b16_<ck_tile::fp16_t>(t, a, s);
@@ -146,8 +141,6 @@ float rmsnorm2d_fwd(rmsnorm2d_fwd_traits t, rmsnorm2d_fwd_args a, const ck_tile:
{
return rmsnorm2d_fwd_b16_<ck_tile::bf16_t>(t, a, s);
}
if(r < 0)
else
throw std::runtime_error("Without supported instances!");
return r;
}

2
example/ck_tile/10_rmsnorm2d/rmsnorm2d_fwd.hpp
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@@ -97,7 +97,7 @@ struct rmsnorm2d_fwd_traits_
using WarpTile = ck_tile::sequence<Warp_M, Warp_N>;
using Vector = ck_tile::sequence<1, Vector_N_>;
using Shape = ck_tile::Rmsnorm2dShape<BlockTile, BlockWarps, WarpTile, Vector>;
using Shape = ck_tile::Generic2dBlockShape<BlockTile, BlockWarps, WarpTile, Vector>;
static constexpr bool kPadN = kPadN_;
static constexpr bool kSaveInvRms = kSaveInvRms_;

5
example/ck_tile/10_rmsnorm2d/script/perf_test.sh
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@@ -1,6 +1,5 @@
# run from top of ck folder
EXE=build/bin/tile_rmsnorm2d_fwd
#!/bin/sh
EXE="$(find . -name tile_rmsnorm2d_fwd -type f | head -n 1)"
$EXE -m=1 -n=1 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=80 -e=1e-12 -v=1 -prec=bf16 -repeat=1000

3
example/ck_tile/10_rmsnorm2d/script/smoke_test.sh
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@@ -1,6 +1,5 @@
#!/bin/sh
# call from top of CK folder
EXE=./build/bin/tile_rmsnorm2d_fwd
EXE="$(find . -name tile_rmsnorm2d_fwd -type f | head -n 1)"
for pr_i in "fp16" "bf16" ; do
$EXE -prec=$pr_i -m=99 -n=13

6
example/ck_tile/11_add_rmsnorm2d_rdquant/add_rmsnorm2d_rdquant_fwd.hpp
View File

@@ -18,7 +18,7 @@ struct AddRmsnormRdquantTypeConfig<ck_tile::half_t>
using BDataType = ck_tile::half_t;
using GammaDataType = ck_tile::half_t;
using XDataType = ck_tile::half_t;
using YScaleDataType = ck_tile::half_t;
using YScaleDataType = float;
using QYDataType = ck_tile::int8_t;
using ComputeDataType = float;
};
@@ -30,7 +30,7 @@ struct AddRmsnormRdquantTypeConfig<ck_tile::bf16_t>
using BDataType = ck_tile::bf16_t;
using GammaDataType = ck_tile::bf16_t;
using XDataType = ck_tile::bf16_t;
using YScaleDataType = ck_tile::bf16_t;
using YScaleDataType = float;
using QYDataType = ck_tile::int8_t;
using ComputeDataType = float;
};
@@ -101,7 +101,7 @@ struct add_rmsnorm2d_rdquant_fwd_traits_
using WarpTile = ck_tile::sequence<Warp_M, Warp_N>;
using Vector = ck_tile::sequence<1, Vector_N_>;
using Shape = ck_tile::AddRmsnorm2dRdquantShape<BlockTile, BlockWarps, WarpTile, Vector>;
using Shape = ck_tile::Generic2dBlockShape<BlockTile, BlockWarps, WarpTile, Vector>;
static constexpr bool kPadN = kPadN_;
static constexpr bool kSaveX = kSaveX_;

8
example/ck_tile/11_add_rmsnorm2d_rdquant/example_add_rmsnorm2d_rdquant_fwd.cpp
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@@ -66,7 +66,7 @@ bool run(const ck_tile::ArgParser& arg_parser)
using BDataType = DataType;
using GammaDataType = DataType;
using XDataType = DataType;
using YScaleDataType = DataType;
using YScaleDataType = float;
using QYDataType = ck_tile::int8_t;
using ComputeDataType = float;
@@ -99,12 +99,12 @@ bool run(const ck_tile::ArgParser& arg_parser)
constexpr bool kThreePass = true;
using BlockWarps = ck_tile::sequence<2, 2>;
using BlockTile = ck_tile::sequence<2, 128>;
using BlockWarps = ck_tile::sequence<4, 1>;
using BlockTile = ck_tile::sequence<4, 128>;
using WarpTile = ck_tile::sequence<1, 64>;
using Vector = ck_tile::sequence<1, 1>;
using Shape = ck_tile::AddRmsnorm2dRdquantShape<BlockTile, BlockWarps, WarpTile, Vector>;
using Shape = ck_tile::Generic2dBlockShape<BlockTile, BlockWarps, WarpTile, Vector>;
using Problem = ck_tile::AddRmsnorm2dRdquantFwdPipelineProblem<ADataType,
BDataType,
GammaDataType,

9
example/ck_tile/11_add_rmsnorm2d_rdquant/instances/add_rmsnorm2d_rdquant_fwd_api.cpp
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@@ -28,7 +28,6 @@ float add_rmsnorm2d_rdquant_fwd_b16_(add_rmsnorm2d_rdquant_fwd_traits /*t*/,
add_rmsnorm2d_rdquant_fwd_args a,
const ck_tile::stream_config& s)
{
#if 1
float r = -1;
// clang-format off
// rm rn tm tn vn pd x 3p
@@ -128,9 +127,6 @@ float add_rmsnorm2d_rdquant_fwd_b16_(add_rmsnorm2d_rdquant_fwd_traits /*t*/,
r = add_rmsnorm2d_rdquant_fwd_<trait_<data_type, 1, 4, 1, 1024, 1, true, true, true>>(s, a);
}
return r;
#else
return add_rmsnorm2d_rdquant_fwd_<trait_<data_type, 1, 1, 2, 128, 8, true, true, false>>(s, a);
#endif
// clang-format on
}
@@ -139,7 +135,6 @@ float add_rmsnorm2d_rdquant_fwd(add_rmsnorm2d_rdquant_fwd_traits t,
const ck_tile::stream_config& s)
{
float r = -1;
// Only support instance of save_x == true for now
assert(t.save_x);
if(t.data_type.compare("fp16") == 0)
@@ -150,8 +145,6 @@ float add_rmsnorm2d_rdquant_fwd(add_rmsnorm2d_rdquant_fwd_traits t,
{
return add_rmsnorm2d_rdquant_fwd_b16_<ck_tile::bf16_t>(t, a, s);
}
if(r < 0)
else
throw std::runtime_error("Without supported instances!");
return r;
}

5
example/ck_tile/11_add_rmsnorm2d_rdquant/script/perf_test.sh
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@@ -1,6 +1,5 @@
# run from top of ck folder
EXE=build/bin/tile_add_rmsnorm2d_rdquant_fwd
#!/bin/sh
EXE="$(find . -name tile_add_rmsnorm2d_rdquant_fwd -type f | head -n 1)"
$EXE -m=1 -n=1 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=80 -e=1e-12 -v=1 -prec=bf16 -repeat=1000

3
example/ck_tile/11_add_rmsnorm2d_rdquant/script/smoke_test.sh
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@@ -1,6 +1,5 @@
#!/bin/sh
# call from top of CK folder
EXE=./build/bin/tile_add_rmsnorm2d_rdquant_fwd
EXE="$(find . -name tile_add_rmsnorm2d_rdquant_fwd -type f | head -n 1)"
for pr_i in "fp16" "bf16" ; do
$EXE -prec=$pr_i -m=99 -n=13

24
example/ck_tile/12_smoothquant/CMakeLists.txt Normal file
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@@ -0,0 +1,24 @@
function (add_smoothquant_example TARGET_NAME MAIN_SRC)
message("adding ${TARGET_NAME}")
# not using add_example_executable() to add target, since we don't want this to have
# to be included in "make all/install/check"
add_executable(${TARGET_NAME} EXCLUDE_FROM_ALL ${MAIN_SRC})
target_include_directories(${TARGET_NAME} PRIVATE ${CMAKE_CURRENT_LIST_DIR})
foreach(source IN LISTS ARGN)
list(APPEND INSTANCE_SRCS ${source})
endforeach()
target_sources(${TARGET_NAME} PRIVATE ${INSTANCE_SRCS})
set(COMPILE_OPTIONS)
# NOTE: we turn off undefined-func-template to let source compile without explicit declare function specializations
list(APPEND COMPILE_OPTIONS -Wno-undefined-func-template -Wno-float-equal)
target_compile_options(${TARGET_NAME} PRIVATE ${COMPILE_OPTIONS})
endfunction(add_smoothquant_example TARGET_NAME MAIN_SRC)
file(GLOB INSTANCE_SRCS instances/*.cpp)
add_smoothquant_example(tile_smoothquant smoothquant.cpp ${INSTANCE_SRCS})
add_smoothquant_example(tile_example_smoothquant example_smoothquant.cpp)

21
example/ck_tile/12_smoothquant/README.md Normal file
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@@ -0,0 +1,21 @@
# smoothquant
This folder contains example for smoothquant using ck_tile tile-programming implementation.
## build
```
# in the root of ck_tile
mkdir build && cd build
sh ../script/cmake-ck-dev.sh ../ <arch> # you can replace this <arch> to gfx90a, gfx942...
make tile_smoothquant -j
```
This will result in an executable `build/bin/tile_smoothquant`
## cmdline
```
args:
-m m dimension (default:3328)
-n m dimension (default:4096)
-v cpu validation or not (default:1)
-prec precision (default:fp16)
```

237
example/ck_tile/12_smoothquant/example_smoothquant.cpp Normal file
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@@ -0,0 +1,237 @@
#include "ck_tile/host.hpp"
#include "ck_tile/core.hpp"
#include "ck_tile/host/kernel_launch.hpp"
#include "ck_tile/ops/smoothquant.hpp"
#include <cstring>
// different threshold for different dtype
template <typename DataType>
auto get_elimit()
{
double rtol = 1e-5;
double atol = 1e-5;
return ck_tile::make_tuple(rtol, atol);
}
template <>
auto get_elimit<ck_tile::bf16_t>()
{
double rtol = 1e-5;
double atol = 1e-5;
return ck_tile::make_tuple(rtol, atol);
}
template <>
auto get_elimit<ck_tile::int8_t>()
{
// due to rounding, int8 quantization might have 1 abs error
double rtol = 1;
double atol = 1;
return ck_tile::make_tuple(rtol, atol);
}
auto create_args(int argc, char* argv[])
{
ck_tile::ArgParser arg_parser;
arg_parser.insert("m", "3328", "m dimension")
.insert("n", "4096", "n dimension")
.insert("stride", "-1", "stride per row, if -1 then equal to n")
.insert("e", "1e-5", "epsilon")
.insert("v", "1", "cpu validation or not")
.insert("prec", "fp16", "precision")
.insert("warmup", "0", "cold iter")
.insert("repeat", "1", "hot iter");
bool result = arg_parser.parse(argc, argv);
return std::make_tuple(result, arg_parser);
}
template <typename DataType>
bool run(const ck_tile::ArgParser& arg_parser)
{
ck_tile::index_t m = arg_parser.get_int("m");
ck_tile::index_t n = arg_parser.get_int("n");
ck_tile::index_t stride = arg_parser.get_int("stride");
if(stride < 0)
stride = n;
std::string data_type = arg_parser.get_str("prec");
int do_validation = arg_parser.get_int("v");
int warmup = arg_parser.get_int("warmup");
int repeat = arg_parser.get_int("repeat");
assert(stride >= n);
using XDataType = DataType;
using XScaleDataType = float;
using YScaleDataType = float;
using QYDataType = ck_tile::int8_t;
using ComputeDataType = float;
// host verify
ck_tile::HostTensor<XDataType> x_host({m, n}, {stride, 1});
ck_tile::HostTensor<XScaleDataType> xscale_host({n});
ck_tile::HostTensor<YScaleDataType> yscale_host_ref({m}, {1});
ck_tile::HostTensor<YScaleDataType> yscale_host_dev({m}, {1});
ck_tile::HostTensor<QYDataType> qy_host_ref({m, n}, {stride, 1});
ck_tile::HostTensor<QYDataType> qy_host_dev({m, n}, {stride, 1});
ck_tile::FillUniformDistribution<XDataType>{-.5f, .5f}(x_host);
ck_tile::FillUniformDistribution<XScaleDataType>{1e-3, .5f}(xscale_host);
ck_tile::DeviceMem x_buf(x_host.get_element_space_size_in_bytes());
ck_tile::DeviceMem xscale_buf(xscale_host.get_element_space_size_in_bytes());
ck_tile::DeviceMem yscale_buf(yscale_host_dev.get_element_space_size_in_bytes());
ck_tile::DeviceMem qy_buf(qy_host_dev.get_element_space_size_in_bytes());
x_buf.ToDevice(x_host.data());
xscale_buf.ToDevice(xscale_host.data());
constexpr bool kTwoPass = true;
using BlockWarps = ck_tile::sequence<2, 2>;
using BlockTile = ck_tile::sequence<2, 128>;
using WarpTile = ck_tile::sequence<1, 64>;
using Vector = ck_tile::sequence<1, 1>;
using Shape = ck_tile::Generic2dBlockShape<BlockTile, BlockWarps, WarpTile, Vector>;
using Problem = ck_tile::SmoothquantPipelineProblem<XDataType,
XScaleDataType,
ComputeDataType,
YScaleDataType,
QYDataType,
Shape,
true,
kTwoPass>;
using OnePassPipeline = ck_tile::SmoothquantPipelineOnePass<Problem>;
using TwoPassPipeline = ck_tile::SmoothquantPipelineTwoPass<Problem>;
using Pipeline = std::conditional_t<kTwoPass, TwoPassPipeline, OnePassPipeline>;
using Kernel = ck_tile::Smoothquant<Pipeline>;
ck_tile::SmoothquantHostArgs args{x_buf.GetDeviceBuffer(),
xscale_buf.GetDeviceBuffer(),
yscale_buf.GetDeviceBuffer(),
qy_buf.GetDeviceBuffer(),
m,
n,
stride};
auto kargs = Kernel::MakeKargs(args);
const dim3 grids = Kernel::GridSize(args);
constexpr dim3 blocks = Kernel::BlockSize();
constexpr ck_tile::index_t kBlockPerCu = 1;
auto s = ck_tile::stream_config{nullptr, true, 1, warmup, repeat};
ck_tile::launch_kernel(
s, ck_tile::make_kernel<blocks.x, kBlockPerCu>(Kernel{}, grids, blocks, 0, kargs));
bool pass = true;
if(do_validation)
{
using YDataType = ComputeDataType;
ck_tile::HostTensor<ComputeDataType> y_host({m, n}, {stride, 1});
// smooth outlier
{
auto f = [&](auto n_) {
auto v_xscale = ck_tile::type_convert<ComputeDataType>(xscale_host(n_));
for(int m_ = 0; m_ < m; ++m_)
{
auto v_x = ck_tile::type_convert<ComputeDataType>(x_host(m_, n_));
y_host(m_, n_) = v_x * v_xscale;
}
};
ck_tile::make_ParallelTensorFunctor(f, xscale_host.get_element_space_size())(
std::thread::hardware_concurrency());
}
// yscale
{
ck_tile::HostTensor<YDataType> y_rowwise_amax_host({m});
using ReduceAmax = ck_tile::ReduceOp::AbsMax;
ck_tile::reference_reduce<ComputeDataType, ComputeDataType, YDataType>(
y_host, y_rowwise_amax_host, ReduceAmax{});
auto op = [](const auto& v0) {
return v0 /
ck_tile::type_convert<ComputeDataType>(ck_tile::numeric<QYDataType>::max());
};
ck_tile::reference_unary_elementwise<YDataType, YScaleDataType, ComputeDataType>(
y_rowwise_amax_host, yscale_host_ref, op);
yscale_buf.FromDevice(yscale_host_dev.mData.data());
auto [rtol, atol] = get_elimit<YScaleDataType>();
pass &= ck_tile::check_err(yscale_host_dev,
yscale_host_ref,
std::string("yscale Error: Incorrect results!"),
rtol,
atol);
}
// rowwise quantization
{
ck_tile::reference_rowwise_quantization2d<YDataType, YScaleDataType, QYDataType>(
y_host, yscale_host_ref, qy_host_ref);
qy_buf.FromDevice(qy_host_dev.data());
auto [rtol, atol] = get_elimit<QYDataType>();
if(stride == n)
{
pass = ck_tile::check_err(qy_host_dev,
qy_host_ref,
std::string("qy Error: Incorrect results!"),
rtol,
atol);
}
else
{
for(int i_r = 0; i_r < m; i_r++)
{
std::vector<QYDataType> qy_host_dev_row(qy_host_dev.begin() + i_r * stride,
qy_host_dev.begin() + i_r * stride + n);
std::vector<QYDataType> qy_host_ref_row(qy_host_ref.begin() + i_r * stride,
qy_host_ref.begin() + i_r * stride + n);
pass &= ck_tile::check_err(qy_host_dev_row,
qy_host_ref_row,
std::string("qy[") + std::to_string(i_r) +
std::string("] Error: Incorrect results!"),
rtol,
atol);
}
}
}
std::cout << "[" << data_type << "]"
<< " m:" << m << ", n:" << n << ", stride:" << stride
<< ", valid:" << (pass ? "y" : "n") << std::flush << std::endl;
}
return pass;
}
int main(int argc, char* argv[])
{
auto [result, arg_parser] = create_args(argc, argv);
if(!result)
return -1;
const std::string data_type = arg_parser.get_str("prec");
if(data_type == "fp16")
{
return run<ck_tile::half_t>(arg_parser) ? 0 : -2;
}
/*else if(data_type == "bf16")
{
return run<ck_tile::bf16_t>(arg_parser) ? 0 : -2;
}*/
return -3;
}

22
example/ck_tile/12_smoothquant/instances/smoothquant_bf16_n1024_instance.cpp Normal file
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@@ -0,0 +1,22 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "smoothquant_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd 2p
#if 0
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 2, 4, 64, 8, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 4, 4, 64, 4, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 8, 4, 64, 2, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 16, 4, 64, 1, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 1, 1, 256, 4, true, false>>(const S&, A);
#endif
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 1, 2, 128, 8, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 2, 2, 128, 4, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 4, 2, 128, 2, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 4, 1, 256, 1, true, false>>(const S&, A);
// clang-format on

13
example/ck_tile/12_smoothquant/instances/smoothquant_bf16_n1536_instance.cpp Normal file
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@@ -0,0 +1,13 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "smoothquant_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd 2p
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 3, 4, 64, 8, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 3, 2, 128, 4, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 3, 1, 256, 2, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 6, 1, 256, 1, true, false>>(const S&, A);
// clang-format on

14
example/ck_tile/12_smoothquant/instances/smoothquant_bf16_n2048_instance.cpp Normal file
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@@ -0,0 +1,14 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "smoothquant_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd 2p
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 1, 1, 256, 8, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 2, 1, 256, 4, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 4, 1, 256, 2, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 8, 1, 256, 1, true, false>>(const S&, A);
// clang-format on

12
example/ck_tile/12_smoothquant/instances/smoothquant_bf16_n256_instance.cpp Normal file
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@@ -0,0 +1,12 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "smoothquant_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd 2p
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 1, 4, 64, 4, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 2, 4, 64, 2, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 4, 4, 64, 1, true, false>>(const S&, A);
// clang-format on

14
example/ck_tile/12_smoothquant/instances/smoothquant_bf16_n3072_instance.cpp Normal file
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@@ -0,0 +1,14 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "smoothquant_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd 2p
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 3, 1, 128, 8, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 3, 1, 256, 4, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 6, 1, 256, 2, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 3, 1, 1024, 1, true, false>>(const S&, A);
// clang-format on

14
example/ck_tile/12_smoothquant/instances/smoothquant_bf16_n4096_instance.cpp Normal file
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@@ -0,0 +1,14 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "smoothquant_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd 2p
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 2, 1, 256, 8, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 4, 1, 256, 4, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 2, 1, 1024, 2, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 4, 1, 1024, 1, true, false>>(const S&, A);
// clang-format on

14
example/ck_tile/12_smoothquant/instances/smoothquant_bf16_n4096_tp_instance.cpp Normal file
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@@ -0,0 +1,14 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "smoothquant_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd 2p
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 2, 1, 256, 8, true, true>>(const S&, A);
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 4, 1, 256, 4, true, true>>(const S&, A);
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 2, 1, 1024, 2, true, true>>(const S&, A);
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 4, 1, 1024, 1, true, true>>(const S&, A);
// clang-format on

13
example/ck_tile/12_smoothquant/instances/smoothquant_bf16_n512_instance.cpp Normal file
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@@ -0,0 +1,13 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "smoothquant_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd 2p
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 1, 4, 64, 8, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 2, 4, 64, 4, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 4, 4, 64, 2, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 8, 4, 64, 1, true, false>>(const S&, A);
// clang-format on

12
example/ck_tile/12_smoothquant/instances/smoothquant_bf16_n64_n128_instance.cpp Normal file
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@@ -0,0 +1,12 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "smoothquant_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd 2p
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 1, 4, 64, 1, true , false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 1, 4, 64, 2, true , false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 2, 4, 64, 1, true , false>>(const S&, A);
// clang-format on

12
example/ck_tile/12_smoothquant/instances/smoothquant_bf16_n768_instance.cpp Normal file
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@@ -0,0 +1,12 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "smoothquant_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd 2p
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 3, 4, 64, 4, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 6, 4, 64, 2, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::bf16_t, 1, 12, 4, 64, 1, true, false>>(const S&, A);
// clang-format on

22
example/ck_tile/12_smoothquant/instances/smoothquant_fp16_n1024_instance.cpp Normal file
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@@ -0,0 +1,22 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "smoothquant_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd 2p
#if 0
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 2, 4, 64, 8, true ,false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 4, 4, 64, 4, true ,false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 8, 4, 64, 2, true ,false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 16, 4, 64, 1, true ,false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 1, 1, 256, 4, true ,false>>(const S&, A);
#endif
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 1, 2, 128, 8, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 2, 2, 128, 4, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 4, 2, 128, 2, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 4, 1, 256, 1, true, false>>(const S&, A);
// clang-format on

13
example/ck_tile/12_smoothquant/instances/smoothquant_fp16_n1536_instance.cpp Normal file
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@@ -0,0 +1,13 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "smoothquant_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd 2p
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 3, 4, 64, 8, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 3, 2, 128, 4, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 3, 1, 256, 2, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 6, 1, 256, 1, true, false>>(const S&, A);
// clang-format on

14
example/ck_tile/12_smoothquant/instances/smoothquant_fp16_n2048_instance.cpp Normal file
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@@ -0,0 +1,14 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "smoothquant_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd 2p
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 1, 1, 256, 8, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 2, 1, 256, 4, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 4, 1, 256, 2, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 8, 1, 256, 1, true, false>>(const S&, A);
// clang-format on

12
example/ck_tile/12_smoothquant/instances/smoothquant_fp16_n256_instance.cpp Normal file
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@@ -0,0 +1,12 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "smoothquant_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd 2p
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 1, 4, 64, 4, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 2, 4, 64, 2, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 4, 4, 64, 1, true, false>>(const S&, A);
// clang-format on

14
example/ck_tile/12_smoothquant/instances/smoothquant_fp16_n3072_instance.cpp Normal file
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@@ -0,0 +1,14 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "smoothquant_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd 2p
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 3, 1, 128, 8,true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 3, 1, 256, 4,true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 6, 1, 256, 2,true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 3, 1, 1024, 1,true, false>>(const S&, A);
// clang-format on

14
example/ck_tile/12_smoothquant/instances/smoothquant_fp16_n4096_instance.cpp Normal file
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@@ -0,0 +1,14 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "smoothquant_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd 2p
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 2, 1, 256, 8, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 4, 1, 256, 4, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 2, 1, 1024, 2, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 4, 1, 1024, 1, true, false>>(const S&, A);
// clang-format on

14
example/ck_tile/12_smoothquant/instances/smoothquant_fp16_n4096_tp_instance.cpp Normal file
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@@ -0,0 +1,14 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "smoothquant_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd 2p
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 2, 1, 256, 8, true, true>>(const S&, A);
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 4, 1, 256, 4, true, true>>(const S&, A);
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 2, 1, 1024, 2, true, true>>(const S&, A);
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 4, 1, 1024, 1, true, true>>(const S&, A);
// clang-format on

13
example/ck_tile/12_smoothquant/instances/smoothquant_fp16_n512_instance.cpp Normal file
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@@ -0,0 +1,13 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "smoothquant_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd 2p
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 1, 4, 64, 8, true , false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 2, 4, 64, 4, true , false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 4, 4, 64, 2, true , false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 8, 4, 64, 1, true , false>>(const S&, A);
// clang-format on

12
example/ck_tile/12_smoothquant/instances/smoothquant_fp16_n64_n128_instance.cpp Normal file
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@@ -0,0 +1,12 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "smoothquant_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd 2p
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 1, 4, 64, 1, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 1, 4, 64, 2, true, false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 2, 4, 64, 1, true, false>>(const S&, A);
// clang-format on

12
example/ck_tile/12_smoothquant/instances/smoothquant_fp16_n768_instance.cpp Normal file
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@@ -0,0 +1,12 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "smoothquant_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd 2p
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 3, 4, 64, 4, true , false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 6, 4, 64, 2, true , false>>(const S&, A);
template float smoothquant_<trait_<ck_tile::fp16_t, 1, 12, 4, 64, 1, true , false>>(const S&, A);
// clang-format on

143
example/ck_tile/12_smoothquant/instances/smoothquant_fwd_api.cpp Normal file
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@@ -0,0 +1,143 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include <ck_tile/core.hpp>
#include "smoothquant.hpp"
template <typename DataType_,
ck_tile::index_t Repeat_M_, // each thread repeat along M
ck_tile::index_t Repeat_N_, // each thread repeat along N
ck_tile::index_t ThreadPerBlock_M_, // num threads along M
ck_tile::index_t ThreadPerBlock_N_, // num threads along N
ck_tile::index_t Vector_N_, // vector size along N
bool kPadN_,
bool kTwoPass_>
using trait_ = smoothquant_traits_<DataType_,
Repeat_M_,
Repeat_N_,
ThreadPerBlock_M_,
ThreadPerBlock_N_,
Vector_N_,
kPadN_,
kTwoPass_>;
template <typename data_type>
float smoothquant_dispatch(smoothquant_traits /*t*/,
smoothquant_args a,
const ck_tile::stream_config& s)
{
float r = -1;
// clang-format off
// rm rn tm tn vn pd 2p
if(a.n <= 64) {
r = smoothquant_<trait_<data_type, 1, 1, 4, 64, 1, true, false>>(s, a);
}
else if(a.n <= 128) {
if (a.n % 2 == 0)
r = smoothquant_<trait_<data_type, 1, 1, 4, 64, 2, true, false>>(s, a);
else
r = smoothquant_<trait_<data_type, 1, 2, 4, 64, 1, true, false>>(s, a);
}
else if(a.n <= 256) {
if (a.n % 4 == 0)
r = smoothquant_<trait_<data_type, 1, 1, 4, 64, 4, true, false>>(s, a);
else if (a.n % 2 == 0)
r = smoothquant_<trait_<data_type, 1, 2, 4, 64, 2, true, false>>(s, a);
else
r = smoothquant_<trait_<data_type, 1, 4, 4, 64, 1, true, false>>(s, a);
}
else if(a.n <= 512) {
if (a.n % 8 == 0)
r = smoothquant_<trait_<data_type, 1, 1, 4, 64, 8, true, false>>(s, a);
else if (a.n % 4 == 0)
r = smoothquant_<trait_<data_type, 1, 2, 4, 64, 4, true, false>>(s, a);
else if (a.n % 2 == 0)
r = smoothquant_<trait_<data_type, 1, 4, 4, 64, 2, true, false>>(s, a);
else
r = smoothquant_<trait_<data_type, 1, 8, 4, 64, 1, true, false>>(s, a);
}
else if(a.n <= 768) {
if (a.n % 4 == 0)
r = smoothquant_<trait_<data_type, 1, 3, 4, 64, 4, true, false>>(s, a);
else if (a.n % 2 == 0)
r = smoothquant_<trait_<data_type, 1, 6, 4, 64, 2, true, false>>(s, a);
else
r = smoothquant_<trait_<data_type, 1,12, 4, 64, 1, true, false>>(s, a);
}
else if(a.n <= 1024) {
if (a.n % 8 == 0)
r = smoothquant_<trait_<data_type, 1, 1, 2, 128, 8, true, false>>(s, a);
else if (a.n % 4 == 0)
r = smoothquant_<trait_<data_type, 1, 2, 2, 128, 4, true, false>>(s, a);
else if (a.n % 2 == 0)
r = smoothquant_<trait_<data_type, 1, 4, 2, 128, 2, true, false>>(s, a);
else
r = smoothquant_<trait_<data_type, 1, 4, 1, 256, 1, true, false>>(s, a);
}
else if(a.n <= 1536) {
if (a.n % 8 == 0)
r = smoothquant_<trait_<data_type, 1, 3, 4, 64, 8, true, false>>(s, a);
else if (a.n % 4 == 0)
r = smoothquant_<trait_<data_type, 1, 3, 2, 128, 4, true, false>>(s, a);
else if (a.n % 2 == 0)
r = smoothquant_<trait_<data_type, 1, 3, 1, 256, 2, true, false>>(s, a);
else
r = smoothquant_<trait_<data_type, 1, 6, 1, 256, 1, true, false>>(s, a);
}
else if(a.n <= 2048) {
if (a.n % 8 == 0)
r = smoothquant_<trait_<data_type, 1, 1, 1, 256, 8, true, false>>(s, a);
else if (a.n % 4 == 0)
r = smoothquant_<trait_<data_type, 1, 2, 1, 256, 4, true, false>>(s, a);
else if (a.n % 2 == 0)
r = smoothquant_<trait_<data_type, 1, 4, 1, 256, 2, true, false>>(s, a);
else
r = smoothquant_<trait_<data_type, 1, 8, 1, 256, 1, true, false>>(s, a);
}
else if(a.n <= 3072) {
if (a.n % 8 == 0)
r = smoothquant_<trait_<data_type, 1, 3, 1, 128, 8, true, false>>(s, a);
else if (a.n % 4 == 0)
r = smoothquant_<trait_<data_type, 1, 3, 1, 256, 4, true, false>>(s, a);
else if (a.n % 2 == 0)
r = smoothquant_<trait_<data_type, 1, 6, 1, 256, 2, true, false>>(s, a);
else
r = smoothquant_<trait_<data_type, 1, 3, 1, 1024, 1, true, false>>(s, a);
}
else if(a.n <= 4096) {
if (a.n % 8 == 0)
r = smoothquant_<trait_<data_type, 1, 2, 1, 256, 8, true, false>>(s, a);
else if (a.n % 4 == 0)
r = smoothquant_<trait_<data_type, 1, 4, 1, 256, 4, true, false>>(s, a);
else if (a.n % 2 == 0)
r = smoothquant_<trait_<data_type, 1, 2, 1, 1024, 2, true, false>>(s, a);
else
r = smoothquant_<trait_<data_type, 1, 4, 1, 1024, 1, true, false>>(s, a);
}
else if(a.n > 4096) {
if (a.n % 8 == 0)
r = smoothquant_<trait_<data_type, 1, 2, 1, 256, 8, true, true>>(s, a);
else if (a.n % 4 == 0)
r = smoothquant_<trait_<data_type, 1, 4, 1, 256, 4, true, true>>(s, a);
else if (a.n % 2 == 0)
r = smoothquant_<trait_<data_type, 1, 2, 1, 1024, 2, true, true>>(s, a);
else
r = smoothquant_<trait_<data_type, 1, 4, 1, 1024, 1, true, true>>(s, a);
}
return r;
// clang-format on
}
float smoothquant(smoothquant_traits t, smoothquant_args a, const ck_tile::stream_config& s)
{
if(t.data_type.compare("fp16") == 0)
{
return smoothquant_dispatch<ck_tile::fp16_t>(t, a, s);
}
else if(t.data_type.compare("bf16") == 0)
{
return smoothquant_dispatch<ck_tile::bf16_t>(t, a, s);
}
else
throw std::runtime_error("Without supported instances!");
}

62
example/ck_tile/12_smoothquant/instances/smoothquant_instance_common.hpp Normal file
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@@ -0,0 +1,62 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include <ck_tile/core.hpp>
#include "smoothquant.hpp"
#include <iostream>
#pragma once
using S = ck_tile::stream_config;
using A = smoothquant_args;
template <typename DataType_,
ck_tile::index_t Repeat_M_, // each thread repeat along M
ck_tile::index_t Repeat_N_, // each thread repeat along N
ck_tile::index_t ThreadPerBlock_M_, // num threads along M
ck_tile::index_t ThreadPerBlock_N_, // num threads along N
ck_tile::index_t Vector_N_, // vector size along N
bool kPadN_,
bool kTwoPass_>
using trait_ = smoothquant_traits_<DataType_,
Repeat_M_,
Repeat_N_,
ThreadPerBlock_M_,
ThreadPerBlock_N_,
Vector_N_,
kPadN_,
kTwoPass_>;
template <typename Traits_>
float smoothquant_(const S& s, A a)
{
using DataType = typename Traits_::DataType;
using PipelineProblem = ck_tile::SmoothquantPipelineProblem<
typename SmoothquantTypeConfig<DataType>::XDataType,
typename SmoothquantTypeConfig<DataType>::XScaleDataType,
typename SmoothquantTypeConfig<DataType>::ComputeDataType,
typename SmoothquantTypeConfig<DataType>::YScaleDataType,
typename SmoothquantTypeConfig<DataType>::QYDataType,
typename Traits_::Shape,
Traits_::kPadN,
Traits_::kTwoPass>;
using OnePassPipeline = ck_tile::SmoothquantPipelineOnePass<PipelineProblem>;
using TwoPassPipeline = ck_tile::SmoothquantPipelineTwoPass<PipelineProblem>;
using Pipeline = std::conditional_t<Traits_::kTwoPass, TwoPassPipeline, OnePassPipeline>;
using Kernel = ck_tile::Smoothquant<Pipeline>;
const dim3 grids = Kernel::GridSize(a);
constexpr dim3 blocks = Kernel::BlockSize();
constexpr ck_tile::index_t kBlockPerCu = 1;
auto kargs = Kernel::MakeKargs(a);
if(s.log_level_ > 0)
std::cout << ", " << Kernel::GetName() << std::flush;
return ck_tile::launch_kernel(
s, ck_tile::make_kernel<blocks.x, kBlockPerCu>(Kernel{}, grids, blocks, 0, kargs));
}

37
example/ck_tile/12_smoothquant/script/perf_test.sh Executable file
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@@ -0,0 +1,37 @@
EXE="$(find . -name tile_smoothquant -type f | head -n 1)"
$EXE -m=1 -n=1 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=80 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=128 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=144 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=168 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=184 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=256 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=288 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=344 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=376 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=448 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=512 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=924 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=1024 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=1078 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=1996 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=4080 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
$EXE -m=700 -n=80 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
$EXE -m=700 -n=128 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
$EXE -m=700 -n=144 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
$EXE -m=700 -n=168 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
$EXE -m=700 -n=184 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
$EXE -m=700 -n=256 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
$EXE -m=700 -n=288 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
$EXE -m=700 -n=344 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
$EXE -m=700 -n=376 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
$EXE -m=700 -n=448 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
$EXE -m=700 -n=512 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
$EXE -m=700 -n=924 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
$EXE -m=700 -n=1024 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
$EXE -m=700 -n=1078 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
$EXE -m=700 -n=1996 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
$EXE -m=700 -n=4080 -e=1e-12 -v=1 -prec=fp16 -repeat=1000

30
example/ck_tile/12_smoothquant/script/smoke_test.sh Executable file
View File

@@ -0,0 +1,30 @@
#!/bin/sh
EXE="$(find . -name tile_smoothquant -type f | head -n 1)"
for pr_i in "fp16" "bf16" ; do
$EXE -prec=$pr_i -m=99 -n=13
$EXE -prec=$pr_i -m=17 -n=16
$EXE -prec=$pr_i -m=1 -n=100
$EXE -prec=$pr_i -m=4 -n=128
$EXE -prec=$pr_i -m=80 -n=127
$EXE -prec=$pr_i -m=22 -n=255 -stride=256
$EXE -prec=$pr_i -m=7 -n=599
$EXE -prec=$pr_i -m=19 -n=512
$EXE -prec=$pr_i -m=33 -n=313 -stride=1000
$EXE -prec=$pr_i -m=11 -n=510
$EXE -prec=$pr_i -m=171 -n=676 -stride=818
$EXE -prec=$pr_i -m=91 -n=636
$EXE -prec=$pr_i -m=12 -n=768 -stride=800
$EXE -prec=$pr_i -m=100 -n=766 -stride=812
$EXE -prec=$pr_i -m=31 -n=1024
$EXE -prec=$pr_i -m=64 -n=1000 -stride=1004
$EXE -prec=$pr_i -m=8 -n=1501
$EXE -prec=$pr_i -m=3 -n=1826
$EXE -prec=$pr_i -m=5 -n=2040
$EXE -prec=$pr_i -m=7 -n=2734
$EXE -prec=$pr_i -m=1 -n=3182
$EXE -prec=$pr_i -m=9 -n=4096
$EXE -prec=$pr_i -m=3 -n=8192
$EXE -prec=$pr_i -m=1 -n=10547
$EXE -prec=$pr_i -m=3 -n=17134
done

218
example/ck_tile/12_smoothquant/smoothquant.cpp Normal file
View File

@@ -0,0 +1,218 @@
#include "ck_tile/host.hpp"
#include "smoothquant.hpp"
#include <cstring>
// different threshold for different dtype
template <typename DataType>
auto get_elimit()
{
double rtol = 1e-5;
double atol = 1e-5;
return ck_tile::make_tuple(rtol, atol);
}
template <>
auto get_elimit<ck_tile::bf16_t>()
{
double rtol = 1e-5;
double atol = 1e-5;
return ck_tile::make_tuple(rtol, atol);
}
template <>
auto get_elimit<ck_tile::int8_t>()
{
// due to rounding, int8 quantization might have 1 abs error
double rtol = 1;
double atol = 1;
return ck_tile::make_tuple(rtol, atol);
}
auto create_args(int argc, char* argv[])
{
ck_tile::ArgParser arg_parser;
arg_parser.insert("m", "3328", "m dimension")
.insert("n", "4096", "n dimension")
.insert("stride", "-1", "stride per row, if -1 then equal to n")
.insert("v", "1", "cpu validation or not")
.insert("kname", "1", "print kernel name or not")
.insert("prec", "fp16", "precision")
.insert("warmup", "5", "cold iter")
.insert("repeat", "20", "hot iter");
bool result = arg_parser.parse(argc, argv);
return std::make_tuple(result, arg_parser);
}
template <typename DataType>
bool run(const ck_tile::ArgParser& arg_parser)
{
ck_tile::index_t m = arg_parser.get_int("m");
ck_tile::index_t n = arg_parser.get_int("n");
ck_tile::index_t stride = arg_parser.get_int("stride");
if(stride < 0)
stride = n;
std::string data_type = arg_parser.get_str("prec");
int kname = arg_parser.get_int("kname");
int do_validation = arg_parser.get_int("v");
int warmup = arg_parser.get_int("warmup");
int repeat = arg_parser.get_int("repeat");
assert(stride >= n);
using TypeConfig = SmoothquantTypeConfig<DataType>;
using XDataType = typename TypeConfig::XDataType;
using XScaleDataType = typename TypeConfig::XScaleDataType;
using YScaleDataType = typename TypeConfig::YScaleDataType;
using QYDataType = typename TypeConfig::QYDataType;
using ComputeDataType = typename TypeConfig::ComputeDataType;
// host verify
ck_tile::HostTensor<XDataType> x_host({m, n}, {stride, 1});
ck_tile::HostTensor<XScaleDataType> xscale_host({n});
ck_tile::HostTensor<YScaleDataType> yscale_host_ref({m}, {1});
ck_tile::HostTensor<YScaleDataType> yscale_host_dev({m}, {1});
ck_tile::HostTensor<QYDataType> qy_host_ref({m, n}, {stride, 1});
ck_tile::HostTensor<QYDataType> qy_host_dev({m, n}, {stride, 1});
ck_tile::FillUniformDistribution<XDataType>{-.5f, .5f}(x_host);
ck_tile::FillUniformDistribution<XScaleDataType>{1e-3, .5f}(xscale_host);
ck_tile::DeviceMem x_buf(x_host.get_element_space_size_in_bytes());
ck_tile::DeviceMem xscale_buf(xscale_host.get_element_space_size_in_bytes());
ck_tile::DeviceMem yscale_buf(yscale_host_dev.get_element_space_size_in_bytes());
ck_tile::DeviceMem qy_buf(qy_host_dev.get_element_space_size_in_bytes());
x_buf.ToDevice(x_host.data());
xscale_buf.ToDevice(xscale_host.data());
std::cout << "[" << data_type << "]"
<< " m:" << m << ", n:" << n << ", stride:" << stride << std::flush;
smoothquant_traits traits{data_type};
smoothquant_args args{x_buf.GetDeviceBuffer(),
xscale_buf.GetDeviceBuffer(),
yscale_buf.GetDeviceBuffer(),
qy_buf.GetDeviceBuffer(),
m,
n,
stride};
float ave_time = smoothquant(
traits, args, ck_tile::stream_config{nullptr, true, kname ? 1 : 0, warmup, repeat});
std::size_t num_byte = sizeof(XDataType) * m * n + sizeof(XScaleDataType) * n +
sizeof(YScaleDataType) * m + sizeof(QYDataType) * m * n;
float gb_per_sec = num_byte / 1.E6 / ave_time;
std::cout << ", " << ave_time * 1.E3 << " us, " << gb_per_sec << " GB/s" << std::flush;
bool pass = true;
if(do_validation)
{
using YDataType = ComputeDataType;
ck_tile::HostTensor<ComputeDataType> y_host({m, n}, {stride, 1});
// smooth outlier
{
auto f = [&](auto n_) {
auto v_xscale = ck_tile::type_convert<ComputeDataType>(xscale_host(n_));
for(int m_ = 0; m_ < m; ++m_)
{
auto v_x = ck_tile::type_convert<ComputeDataType>(x_host(m_, n_));
y_host(m_, n_) = v_x * v_xscale;
}
};
ck_tile::make_ParallelTensorFunctor(f, xscale_host.get_element_space_size())(
std::thread::hardware_concurrency());
}
// yscale
{
ck_tile::HostTensor<YDataType> y_rowwise_amax_host({m});
using ReduceAmax = ck_tile::ReduceOp::AbsMax;
ck_tile::reference_reduce<ComputeDataType, ComputeDataType, YDataType>(
y_host, y_rowwise_amax_host, ReduceAmax{});
auto op = [](const auto& v0) {
return v0 /
ck_tile::type_convert<ComputeDataType>(ck_tile::numeric<QYDataType>::max());
};
ck_tile::reference_unary_elementwise<YDataType, YScaleDataType, ComputeDataType>(
y_rowwise_amax_host, yscale_host_ref, op);
yscale_buf.FromDevice(yscale_host_dev.mData.data());
auto [rtol, atol] = get_elimit<YScaleDataType>();
pass &= ck_tile::check_err(yscale_host_dev,
yscale_host_ref,
std::string("yscale Error: Incorrect results!"),
rtol,
atol);
}
// rowwise quantization
{
ck_tile::reference_rowwise_quantization2d<YDataType, YScaleDataType, QYDataType>(
y_host, yscale_host_ref, qy_host_ref);
qy_buf.FromDevice(qy_host_dev.data());
auto [rtol, atol] = get_elimit<QYDataType>();
if(stride == n)
{
pass = ck_tile::check_err(qy_host_dev,
qy_host_ref,
std::string("qy Error: Incorrect results!"),
rtol,
atol);
}
else
{
for(int i_r = 0; i_r < m; i_r++)
{
std::vector<QYDataType> qy_host_dev_row(qy_host_dev.begin() + i_r * stride,
qy_host_dev.begin() + i_r * stride + n);
std::vector<QYDataType> qy_host_ref_row(qy_host_ref.begin() + i_r * stride,
qy_host_ref.begin() + i_r * stride + n);
pass &= ck_tile::check_err(qy_host_dev_row,
qy_host_ref_row,
std::string("qy[") + std::to_string(i_r) +
std::string("] Error: Incorrect results!"),
rtol,
atol);
}
}
}
std::cout << ", valid:" << (pass ? "y" : "n") << std::flush << std::endl;
}
return pass;
}
int main(int argc, char* argv[])
{
auto [result, arg_parser] = create_args(argc, argv);
if(!result)
return -1;
const std::string data_type = arg_parser.get_str("prec");
if(data_type == "fp16")
{
return run<ck_tile::half_t>(arg_parser) ? 0 : -2;
}
else if(data_type == "bf16")
{
return run<ck_tile::bf16_t>(arg_parser) ? 0 : -2;
}
return -3;
}

114
example/ck_tile/12_smoothquant/smoothquant.hpp Normal file
View File

@@ -0,0 +1,114 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "ck_tile/core.hpp"
#include "ck_tile/host/kernel_launch.hpp"
#include "ck_tile/ops/smoothquant.hpp"
#include <string>
template <typename DataType>
struct SmoothquantTypeConfig;
template <>
struct SmoothquantTypeConfig<ck_tile::half_t>
{
using XDataType = ck_tile::half_t;
using XScaleDataType = float;
using YScaleDataType = float;
using QYDataType = ck_tile::int8_t;
using ComputeDataType = float;
};
template <>
struct SmoothquantTypeConfig<ck_tile::bf16_t>
{
using XDataType = ck_tile::bf16_t;
using XScaleDataType = float;
using YScaleDataType = float;
using QYDataType = ck_tile::int8_t;
using ComputeDataType = float;
};
// runtime args
struct smoothquant_args : public ck_tile::SmoothquantHostArgs
{
};
// this is used to pattern-match internl kernel implementation, not to instantiate kernel
template <typename DataType_,
ck_tile::index_t Repeat_M_, // each thread repeat along M
ck_tile::index_t Repeat_N_, // each thread repeat along N
ck_tile::index_t ThreadPerBlock_M_, // num threads along M
ck_tile::index_t ThreadPerBlock_N_, // num threads along N
ck_tile::index_t Vector_N_, // vector size along N
bool kPadN_,
bool kTwoPass_>
struct smoothquant_traits_
{
using DataType = ck_tile::remove_cvref_t<DataType_>;
static constexpr bool is_warp_per_row = ThreadPerBlock_N_ <= warpSize;
static_assert((ThreadPerBlock_M_ * ThreadPerBlock_N_) % warpSize == 0);
static constexpr ck_tile::index_t total_warps =
(ThreadPerBlock_M_ * ThreadPerBlock_N_) / warpSize;
// num of warps along m
static constexpr ck_tile::index_t BlockWarps_M = []() {
if constexpr(is_warp_per_row)
{
static_assert(warpSize % ThreadPerBlock_N_ == 0);
return total_warps * (warpSize / ThreadPerBlock_N_);
}
else
{
// static_assert(warpSize % ThreadPerBlock_M_ == 0);
return total_warps / (ThreadPerBlock_N_ / warpSize);
}
}();
// num of warps along n
static constexpr ck_tile::index_t BlockWarps_N = []() {
if constexpr(is_warp_per_row)
{
static_assert(warpSize % ThreadPerBlock_N_ == 0);
return 1;
}
else
{
static_assert(ThreadPerBlock_N_ % warpSize == 0);
return ThreadPerBlock_N_ / warpSize;
}
}();
static constexpr ck_tile::index_t Repeat_M = Repeat_M_;
static constexpr ck_tile::index_t Repeat_N = Repeat_N_;
static constexpr ck_tile::index_t Block_M = Repeat_M_ * ThreadPerBlock_M_;
static constexpr ck_tile::index_t Block_N = Repeat_N_ * ThreadPerBlock_N_ * Vector_N_;
static constexpr ck_tile::index_t Warp_M = ThreadPerBlock_M_ / BlockWarps_M;
static constexpr ck_tile::index_t Warp_N = ThreadPerBlock_N_ / BlockWarps_N * Vector_N_;
using BlockTile = ck_tile::sequence<Block_M, Block_N>;
using BlockWarps = ck_tile::sequence<BlockWarps_M, BlockWarps_N>;
using WarpTile = ck_tile::sequence<Warp_M, Warp_N>;
using Vector = ck_tile::sequence<1, Vector_N_>;
using Shape = ck_tile::Generic2dBlockShape<BlockTile, BlockWarps, WarpTile, Vector>;
static constexpr bool kPadN = kPadN_;
static constexpr bool kTwoPass = kTwoPass_;
};
template <typename Traits_>
float smoothquant_(const ck_tile::stream_config& s, smoothquant_args a);
// This is the public API, will be generated by script
struct smoothquant_traits
{
std::string data_type;
};
float smoothquant(smoothquant_traits, smoothquant_args, const ck_tile::stream_config&);

1
example/ck_tile/CMakeLists.txt
View File

@@ -11,3 +11,4 @@ add_subdirectory(06_permute)
add_subdirectory(09_topk_softmax)
add_subdirectory(10_rmsnorm2d)
add_subdirectory(11_add_rmsnorm2d_rdquant)
add_subdirectory(12_smoothquant)

1
include/ck_tile/ops/add_rmsnorm2d_rdquant.hpp
View File

@@ -4,7 +4,6 @@
#pragma once
#include "ck_tile/ops/add_rmsnorm2d_rdquant/kernel/add_rmsnorm2d_rdquant_fwd_kernel.hpp"
#include "ck_tile/ops/add_rmsnorm2d_rdquant/kernel/add_rmsnorm2d_rdquant_fwd_shape.hpp"
#include "ck_tile/ops/add_rmsnorm2d_rdquant/pipeline/add_rmsnorm2d_rdquant_fwd_pipeline_default_policy.hpp"
#include "ck_tile/ops/add_rmsnorm2d_rdquant/pipeline/add_rmsnorm2d_rdquant_fwd_pipeline_one_pass.hpp"
#include "ck_tile/ops/add_rmsnorm2d_rdquant/pipeline/add_rmsnorm2d_rdquant_fwd_pipeline_problem.hpp"

17
include/ck_tile/ops/add_rmsnorm2d_rdquant/kernel/add_rmsnorm2d_rdquant_fwd_kernel.hpp
View File

@@ -9,15 +9,16 @@
namespace ck_tile {
// host side args
// X = A + B, Y = Rmsnorm2d(X), QY = RowwiseDynamicQuant(Y) = SaturateCast(Y / YScale)
struct AddRmsnorm2dRdquantFwdHostArgs
{
const void* p_a;
const void* p_b;
const void* p_gamma;
const void* p_a; // [m ,n], input, fp16/bf16
const void* p_b; // [m ,n], input, fp16/bf16
const void* p_gamma; // [1, n], gamma, prec same as input
void* p_x;
void* p_yscale;
void* p_qy;
void* p_x; // [m, n], output, p_a + p_b, fp16/bf16
void* p_yscale; // [m, 1], output, rowwise quant scale (amax / 127) of reuslt of rmsnorm2d(x)
void* p_qy; // [m, n], output, result of quant tensor of rmsnorm2d(x) int8
float epsilon;
@@ -90,7 +91,7 @@ struct AddRmsnorm2dRdquantFwd
CK_TILE_HOST static constexpr auto GridSize(const Hargs& hargs)
{
return integer_divide_ceil(hargs.m, Block_M);
return dim3(integer_divide_ceil(hargs.m, Block_M));
}
CK_TILE_HOST static constexpr auto BlockSize() { return Problem::BlockShape::BlockSize; }
@@ -170,7 +171,7 @@ struct AddRmsnorm2dRdquantFwd
number<1>{});
const auto tmp2_ =
pad_tensor_view(tmp_, make_tuple(number<Block_N>{}), sequence<kPadM>{});
pad_tensor_view(tmp_, make_tuple(number<Block_N>{}), sequence<kPadN>{});
return make_tile_window(tmp2_, make_tuple(number<Block_N>{}), {0});
}();

78
include/ck_tile/ops/add_rmsnorm2d_rdquant/kernel/add_rmsnorm2d_rdquant_fwd_shape.hpp
View File

@@ -1,78 +0,0 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "ck_tile/core.hpp"
namespace ck_tile {
/*
// clang-format off
4-level descriptor: BlockTile-> WarpPerBlock-> WarpTile-> Vector
Block_N (Warp_N * WarpPerBlock_N * Repeat_N )
+<----------------------< Repeat_N(2)>--------------------->+
| |
+<-- <WarpPerBlock_N(2)> -->+
Warp_N
+--------------+--------------+--------------+--------------+----+----------------+
Warp_M | wrap_0 | wrap_1 | | ^ ^
+--------------+--------------+ | <WarpPerBlock_M(2)> |
| wrap_2 | wrap_3 | | v
+--------------+--------------+--------------+--------------+----+ Block_M
| | |
+ + |
| | | v
+--------------+--------------+--------------+--------------+ +
each Warp-tile (e.g 16 thrd per row)
Vector_N (contiguous pixels each thrd holds along N, or vector size)
+-----------+-----------+-----------+-----------+-----------+
| thrd_0 | thrd_1 | thrd_2 | thrd_3 | ... Vector_M
+-----------+-----------+-----------+-----------+-----------+
| thrd_16 | thrd_17 | thrd_18 | thrd_19 | ...
+-----------+-----------+-----------+-----------+-----------+
// clang-format on
*/
template <typename BlockTile_, // block size, seq<M, N>
typename WarpPerBlock_, // num warps along seq<M, N>
typename WarpTile_, // warp size, seq<M, N>
typename Vector_, // contiguous pixels(vector size) along seq<M, N>
index_t BlockSize_ =
warpSize* reduce_on_sequence(WarpPerBlock_{}, multiplies{}, number<1>{})>
struct AddRmsnorm2dRdquantShape
{
// block size
static constexpr index_t Block_M = BlockTile_::at(number<0>{});
static constexpr index_t Block_N = BlockTile_::at(number<1>{});
// num warps along seq<M, N>, within each block
static constexpr index_t WarpPerBlock_M = WarpPerBlock_::at(number<0>{});
static constexpr index_t WarpPerBlock_N = WarpPerBlock_::at(number<1>{});
// warp size
static constexpr index_t Warp_M = WarpTile_::at(number<0>{});
static constexpr index_t Warp_N = WarpTile_::at(number<1>{});
static_assert(Block_M % (WarpPerBlock_M * Warp_M) == 0);
static_assert(Block_N % (WarpPerBlock_N * Warp_N) == 0);
// repeat of each thread along seq<M, N>
static constexpr index_t Repeat_M = Block_M / (WarpPerBlock_M * Warp_M);
static constexpr index_t Repeat_N = Block_N / (WarpPerBlock_N * Warp_N);
// vector size along seq<M, N>
static constexpr index_t Vector_M = Vector_::at(number<0>{});
static constexpr index_t Vector_N = Vector_::at(number<1>{});
static_assert(Warp_M % Vector_M == 0);
static_assert(Warp_N % Vector_N == 0);
// num of threads along seq<M, N>, within each warp
static constexpr index_t ThreadPerWarp_M = Warp_M / Vector_M;
static constexpr index_t ThreadPerWarp_N = Warp_N / Vector_N;
static constexpr index_t BlockSize = BlockSize_;
};
} // namespace ck_tile

1
include/ck_tile/ops/add_rmsnorm2d_rdquant/pipeline/add_rmsnorm2d_rdquant_fwd_pipeline_default_policy.hpp
View File

@@ -26,6 +26,7 @@ struct AddRmsnorm2dRdquantFwdPipelineDefaultPolicy
sequence<1, 1, 2, 2>,
sequence<0, 3, 0, 3>>{});
}
template <typename Problem>
CK_TILE_DEVICE static constexpr auto MakeGammaBlockTileDistribution()
{

4
include/ck_tile/ops/layernorm2d/kernel/layernorm2d_fwd_kernel.hpp
View File

@@ -117,7 +117,7 @@ struct Layernorm2dFwd
CK_TILE_HOST static constexpr auto GridSize(const Hargs& hargs)
{
return (hargs.m + Block_M - 1) / Block_M;
return dim3(integer_divide_ceil(hargs.m, Block_M));
}
CK_TILE_HOST static constexpr auto BlockSize() { return Problem::BlockShape::BlockSize; }
@@ -165,7 +165,7 @@ struct Layernorm2dFwd
return base_str;
}();
return _SS_("layernorm2d_fwd_") + _SS_(prec_str) + "_" +
return _SS_("layernorm2d_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;

1
include/ck_tile/ops/layernorm2d/pipeline/layernorm2d_fwd_pipeline_default_policy.hpp
View File

@@ -26,6 +26,7 @@ struct Layernorm2dFwdPipelineDefaultPolicy
sequence<1, 1, 2, 2>,
sequence<0, 3, 0, 3>>{});
}
template <typename Problem>
CK_TILE_DEVICE static constexpr auto MakeGammaBetaBlockTileDistribution()
{

2
include/ck_tile/ops/layernorm2d/pipeline/layernorm2d_fwd_pipeline_problem.hpp
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@@ -1,5 +1,5 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once

2
include/ck_tile/ops/layernorm2d/pipeline/layernorm2d_fwd_traits.hpp
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@@ -1,5 +1,5 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once

3
include/ck_tile/ops/reduce/block/block_reduce2d.hpp
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@@ -29,7 +29,8 @@ struct BlockReduce2d
sweep_tile<XDistributedTensor_>(
[&](auto... idx_) {
constexpr auto idx_0 = make_tuple(make_tuple(idx_[number<0>{}]...)[number<0>{}]);
y_tensor(idx_0) = reduce_func(y_tensor(idx_0), x_tensor[idx_]...);
y_tensor(idx_0) = reduce_func(
y_tensor(idx_0), ck_tile::type_convert<ComputeDataType>(x_tensor[idx_])...);
},
ReducePacksPerXDim{});
#if 0

1
include/ck_tile/ops/rmsnorm2d.hpp
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@@ -4,7 +4,6 @@
#pragma once
#include "ck_tile/ops/rmsnorm2d/kernel/rmsnorm2d_fwd_kernel.hpp"
#include "ck_tile/ops/rmsnorm2d/kernel/rmsnorm2d_fwd_shape.hpp"
#include "ck_tile/ops/rmsnorm2d/pipeline/rmsnorm2d_fwd_pipeline_default_policy.hpp"
#include "ck_tile/ops/rmsnorm2d/pipeline/rmsnorm2d_fwd_pipeline_one_pass.hpp"
#include "ck_tile/ops/rmsnorm2d/pipeline/rmsnorm2d_fwd_pipeline_problem.hpp"

12
include/ck_tile/ops/rmsnorm2d/kernel/rmsnorm2d_fwd_kernel.hpp
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@@ -11,11 +11,11 @@ namespace ck_tile {
// host side args
struct Rmsnorm2dFwdHostArgs
{
const void* p_x;
const void* p_gamma;
const void* p_x; // [m ,n], input, fp16/bf16
const void* p_gamma; // [1, n], gamma, prec same as input
void* p_y;
void* p_invRms;
void* p_y; // [m, n], output, fp16/bf16
void* p_invRms; // [m, 1], output inv-rms, prec same as input, nullptr if not used
float epsilon;
@@ -83,7 +83,7 @@ struct Rmsnorm2dFwd
CK_TILE_HOST static constexpr auto GridSize(const Hargs& hargs)
{
return (hargs.m + Block_M - 1) / Block_M;
return dim3(integer_divide_ceil(hargs.m, Block_M));
}
CK_TILE_HOST static constexpr auto BlockSize() { return Problem::BlockShape::BlockSize; }
@@ -149,7 +149,7 @@ struct Rmsnorm2dFwd
number<1>{});
const auto tmp2_ =
pad_tensor_view(tmp_, make_tuple(number<Block_N>{}), sequence<kPadM>{});
pad_tensor_view(tmp_, make_tuple(number<Block_N>{}), sequence<kPadN>{});
return make_tile_window(tmp2_, make_tuple(number<Block_N>{}), {0});
}();

78
include/ck_tile/ops/rmsnorm2d/kernel/rmsnorm2d_fwd_shape.hpp
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@@ -1,78 +0,0 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "ck_tile/core.hpp"
namespace ck_tile {
/*
// clang-format off
4-level descriptor: BlockTile-> WarpPerBlock-> WarpTile-> Vector
Block_N (Warp_N * WarpPerBlock_N * Repeat_N )
+<----------------------< Repeat_N(2)>--------------------->+
| |
+<-- <WarpPerBlock_N(2)> -->+
Warp_N
+--------------+--------------+--------------+--------------+----+----------------+
Warp_M | wrap_0 | wrap_1 | | ^ ^
+--------------+--------------+ | <WarpPerBlock_M(2)> |
| wrap_2 | wrap_3 | | v
+--------------+--------------+--------------+--------------+----+ Block_M
| | |
+ + |
| | | v
+--------------+--------------+--------------+--------------+ +
each Warp-tile (e.g 16 thrd per row)
Vector_N (contiguous pixels each thrd holds along N, or vector size)
+-----------+-----------+-----------+-----------+-----------+
| thrd_0 | thrd_1 | thrd_2 | thrd_3 | ... Vector_M
+-----------+-----------+-----------+-----------+-----------+
| thrd_16 | thrd_17 | thrd_18 | thrd_19 | ...
+-----------+-----------+-----------+-----------+-----------+
// clang-format on
*/
template <typename BlockTile_, // block size, seq<M, N>
typename WarpPerBlock_, // num warps along seq<M, N>
typename WarpTile_, // warp size, seq<M, N>
typename Vector_, // contiguous pixels(vector size) along seq<M, N>
index_t BlockSize_ =
warpSize* reduce_on_sequence(WarpPerBlock_{}, multiplies{}, number<1>{})>
struct Rmsnorm2dShape
{
// block size
static constexpr index_t Block_M = BlockTile_::at(number<0>{});
static constexpr index_t Block_N = BlockTile_::at(number<1>{});
// num warps along seq<M, N>, within each block
static constexpr index_t WarpPerBlock_M = WarpPerBlock_::at(number<0>{});
static constexpr index_t WarpPerBlock_N = WarpPerBlock_::at(number<1>{});
// warp size
static constexpr index_t Warp_M = WarpTile_::at(number<0>{});
static constexpr index_t Warp_N = WarpTile_::at(number<1>{});
static_assert(Block_M % (WarpPerBlock_M * Warp_M) == 0);
static_assert(Block_N % (WarpPerBlock_N * Warp_N) == 0);
// repeat of each thread along seq<M, N>
static constexpr index_t Repeat_M = Block_M / (WarpPerBlock_M * Warp_M);
static constexpr index_t Repeat_N = Block_N / (WarpPerBlock_N * Warp_N);
// vector size along seq<M, N>
static constexpr index_t Vector_M = Vector_::at(number<0>{});
static constexpr index_t Vector_N = Vector_::at(number<1>{});
static_assert(Warp_M % Vector_M == 0);
static_assert(Warp_N % Vector_N == 0);
// num of threads along seq<M, N>, within each warp
static constexpr index_t ThreadPerWarp_M = Warp_M / Vector_M;
static constexpr index_t ThreadPerWarp_N = Warp_N / Vector_N;
static constexpr index_t BlockSize = BlockSize_;
};
} // namespace ck_tile

1
include/ck_tile/ops/rmsnorm2d/pipeline/rmsnorm2d_fwd_pipeline_default_policy.hpp
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@@ -26,6 +26,7 @@ struct Rmsnorm2dFwdPipelineDefaultPolicy
sequence<1, 1, 2, 2>,
sequence<0, 3, 0, 3>>{});
}
template <typename Problem>
CK_TILE_DEVICE static constexpr auto MakeGammaBlockTileDistribution()
{

12
include/ck_tile/ops/smoothquant.hpp Normal file
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@@ -0,0 +1,12 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "ck_tile/ops/smoothquant/kernel/smoothquant_kernel.hpp"
#include "ck_tile/ops/smoothquant/pipeline/smoothquant_pipeline_default_policy.hpp"
#include "ck_tile/ops/smoothquant/pipeline/smoothquant_pipeline_one_pass.hpp"
#include "ck_tile/ops/smoothquant/pipeline/smoothquant_pipeline_problem.hpp"
#include "ck_tile/ops/smoothquant/pipeline/smoothquant_pipeline_two_pass.hpp"
#include "ck_tile/ops/common/generic_2d_block_shape.hpp"
#include "ck_tile/ops/common/tensor_layout.hpp"

176
include/ck_tile/ops/smoothquant/kernel/smoothquant_kernel.hpp Normal file
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@@ -0,0 +1,176 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, 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_xscale; // [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
index_t m;
index_t n;
index_t stride; // 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 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>;
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 auto I0 = number<0>{};
static constexpr auto I1 = number<1>{};
struct Kargs
{
const void* p_x;
const void* p_xscale;
void* p_yscale;
void* p_qy;
index_t m;
index_t n;
index_t stride; // row_stride
};
using Hargs = SmoothquantHostArgs;
CK_TILE_HOST static constexpr Kargs MakeKargs(const Hargs& hargs)
{
return Kargs{
hargs.p_x, hargs.p_xscale, hargs.p_yscale, hargs.p_qy, hargs.m, hargs.n, hargs.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 Problem::BlockShape::BlockSize; }
// 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.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 xscale_window = [&]() {
const auto tmp_ = make_naive_tensor_view<address_space_enum::global>(
static_cast<const XScaleDataType*>(kargs.p_xscale),
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.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, xscale_window, yscale_window, qy_window, kargs.n, smem);
}
};
} // namespace ck_tile

95
include/ck_tile/ops/smoothquant/pipeline/smoothquant_pipeline_default_policy.hpp Normal file
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@@ -0,0 +1,95 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "ck_tile/core.hpp"
#include "ck_tile/ops/reduce/block/block_reduce2d_problem.hpp"
#include "ck_tile/ops/reduce/block/block_reduce2d.hpp"
namespace ck_tile {
struct SmoothquantPipelineDefaultPolicy
{
template <typename Problem>
CK_TILE_DEVICE static constexpr auto MakeXBlockTileDistribution()
{
using S = typename Problem::BlockShape;
return make_static_tile_distribution(
tile_distribution_encoding<
sequence<>,
tuple<sequence<S::Repeat_M, S::WarpPerBlock_M, S::ThreadPerWarp_M, S::Vector_M>,
sequence<S::Repeat_N, S::WarpPerBlock_N, S::ThreadPerWarp_N, S::Vector_N>>,
tuple<sequence<1, 2>, sequence<1, 2>>,
tuple<sequence<1, 1>, sequence<2, 2>>,
sequence<1, 1, 2, 2>,
sequence<0, 3, 0, 3>>{});
}
template <typename Problem>
CK_TILE_DEVICE static constexpr auto MakeXScaleBlockTileDistribution()
{
using S = typename Problem::BlockShape;
return make_static_tile_distribution(
tile_distribution_encoding<
sequence<S::WarpPerBlock_M, S::ThreadPerWarp_M>,
tuple<sequence<S::Repeat_N, S::WarpPerBlock_N, S::ThreadPerWarp_N, S::Vector_N>>,
tuple<sequence<0, 1>, sequence<0, 1>>,
tuple<sequence<0, 1>, sequence<1, 2>>,
sequence<1, 1>,
sequence<0, 3>>{});
}
template <typename Problem>
CK_TILE_HOST_DEVICE static constexpr auto GetBlockReduce2d()
{
using P_ = BlockReduce2dProblem<typename Problem::ComputeDataType,
typename Problem::ComputeDataType,
typename Problem::BlockShape>;
return BlockReduce2d<P_>{};
}
template <typename Problem>
CK_TILE_HOST_DEVICE static constexpr auto GetBlockReduce2dSync()
{
using P_ = BlockReduce2dProblem<typename Problem::ComputeDataType,
typename Problem::ComputeDataType,
typename Problem::BlockShape>;
return BlockReduce2dSync<P_>{};
}
template <typename Problem>
CK_TILE_HOST_DEVICE static constexpr auto GetBlockReduce2dCrossWarpSync()
{
using P_ = BlockReduce2dProblem<typename Problem::ComputeDataType,
typename Problem::ComputeDataType,
typename Problem::BlockShape>;
return BlockReduce2dCrossWarpSync<P_>{};
}
template <typename Problem>
CK_TILE_HOST_DEVICE static constexpr index_t GetSmemSize()
{
if constexpr(Problem::kNeedCrossWarpSync)
{
using P_ = BlockReduce2dProblem<typename Problem::XDataType,
typename Problem::ComputeDataType,
typename Problem::BlockShape>;
using block_reduce2d = BlockReduce2d<P_>;
using x_block_tile =
decltype(make_static_distributed_tensor<typename Problem::XDataType>(
MakeXBlockTileDistribution<Problem>()));
using y_block_tile = decltype(block_reduce2d::template MakeYBlockTile<x_block_tile>());
return GetBlockReduce2dCrossWarpSync<Problem>().template GetSmemSize<y_block_tile>();
}
else
{
return 1; // zero size arrays are an extension
}
}
};
} // namespace ck_tile

94
include/ck_tile/ops/smoothquant/pipeline/smoothquant_pipeline_one_pass.hpp Normal file
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@@ -0,0 +1,94 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "ck_tile/core.hpp"
#include "ck_tile/ops/rmsnorm2d/pipeline/rmsnorm2d_fwd_pipeline_default_policy.hpp"
#include <string>
#include <type_traits>
namespace ck_tile {
template <typename Problem_, typename Policy_ = SmoothquantPipelineDefaultPolicy>
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>;
static constexpr bool kNeedCrossWarpSync = Problem::kNeedCrossWarpSync;
static constexpr bool kPadM = false; // TODO - BlockSmoothquantProblem::kPadM
static constexpr bool kPadN = Problem::kPadN;
static constexpr const char* name = []() {
if constexpr(kNeedCrossWarpSync)
return "bpr_op"; // block per row
else
return "wpr_op"; // warp per row
}();
CK_TILE_HOST_DEVICE static constexpr index_t GetSmemSize()
{
return Policy::template GetSmemSize<Problem>();
}
template <typename XWindow, typename XScaleWindow, typename QYWindow, typename YScaleWindow>
CK_TILE_DEVICE auto operator()(const XWindow& x_window_,
const XScaleWindow& xscale_window_,
YScaleWindow& yscale_window,
QYWindow& qy_window,
ck_tile::index_t,
void* smem) const
{
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 reduce_absmax_func = ReduceOp::AbsMax{};
auto reduce_max_func = ReduceOp::Max{};
auto block_reduce2d = Policy::template GetBlockReduce2d<Problem>();
auto block_reduce2d_sync = Policy::template GetBlockReduce2dSync<Problem>();
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& a, const auto& b) {
return type_convert<ComputeDataType>(a) * type_convert<ComputeDataType>(b);
},
x,
xscale);
// compute absmax, cross-lane->cross-warp
auto absmax = block_reduce2d(
y, reduce_absmax_func.GetIdentityValue<ComputeDataType>(), reduce_absmax_func);
block_reduce2d_sync(absmax, reduce_max_func);
block_reduce2d_cross_warp_sync(absmax, smem, reduce_max_func);
// ex: yscale = absmax / 127 if int8
auto yscale = tile_elementwise_in(
[&](const auto& v_) {
return v_ / type_convert<ComputeDataType>(numeric<QYDataType>::max());
},
absmax);
store_tile(yscale_window, cast_tile<YScaleDataType>(yscale));
// quantize y to qy
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_);
});
store_tile(qy_window, qy);
}
};
} // namespace ck_tile

35
include/ck_tile/ops/smoothquant/pipeline/smoothquant_pipeline_problem.hpp Normal file
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@@ -0,0 +1,35 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "ck_tile/core/utility/type_traits.hpp"
namespace ck_tile {
// Y = X * XScale, QY = RowwiseDynamicQuant(Y) = SaturateCast(Y / YScale)
template <typename XDataType_,
typename XScaleDataType_,
typename ComputeDataType_,
typename YScaleDataType_,
typename QYDataType_,
typename BlockShape_,
bool kPadN_,
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_>;
static constexpr bool kNeedCrossLaneSync = BlockShape::ThreadPerWarp_N > 1;
static constexpr bool kNeedCrossWarpSync = BlockShape::WarpPerBlock_N > 1;
static constexpr bool kPadN = kPadN_;
static constexpr bool kTwoPass = kTwoPass_;
};
} // namespace ck_tile

132
include/ck_tile/ops/smoothquant/pipeline/smoothquant_pipeline_two_pass.hpp Normal file
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@@ -0,0 +1,132 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "ck_tile/core.hpp"
#include "ck_tile/ops/rmsnorm2d/pipeline/rmsnorm2d_fwd_pipeline_default_policy.hpp"
#include <string>
#include <type_traits>
namespace ck_tile {
template <typename Problem_, typename Policy_ = SmoothquantPipelineDefaultPolicy>
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>;
static constexpr bool kNeedCrossWarpSync = Problem::kNeedCrossWarpSync;
static constexpr bool kPadM = false; // TODO - BlockSmoothquantProblem::kPadM
static constexpr bool kPadN = Problem::kPadN;
static constexpr const char* name = []() {
if constexpr(kNeedCrossWarpSync)
return "bpr_tp"; // block per row
else
return "wpr_tp"; // warp per row
}();
CK_TILE_HOST_DEVICE static constexpr index_t GetSmemSize()
{
return Policy::template GetSmemSize<Problem>();
}
template <typename XWindow, typename XScaleWindow, typename QYWindow, typename YScaleWindow>
CK_TILE_DEVICE auto operator()(const XWindow& x_window_,
const XScaleWindow& xscale_window_,
YScaleWindow& yscale_window,
QYWindow& qy_window,
ck_tile::index_t row_size,
void* smem) const
{
auto x_window =
make_tile_window(x_window_, Policy::template MakeXBlockTileDistribution<Problem>());
auto xscale_window = make_tile_window(
xscale_window_, Policy::template MakeXScaleBlockTileDistribution<Problem>());
static constexpr index_t Block_N = Problem::BlockShape::Block_N;
index_t num_n_tile_iteration =
__builtin_amdgcn_readfirstlane(integer_divide_ceil(row_size, Block_N));
auto reduce_absmax_func = ReduceOp::AbsMax{};
auto reduce_max_func = ReduceOp::Max{};
auto block_reduce2d = Policy::template GetBlockReduce2d<Problem>();
auto block_reduce2d_sync = Policy::template GetBlockReduce2dSync<Problem>();
auto block_reduce2d_cross_warp_sync =
Policy::template GetBlockReduce2dCrossWarpSync<Problem>();
using XTensorType = decltype(cast_tile<ComputeDataType>(load_tile(x_window)));
auto absmax = block_reduce2d.template MakeYBlockTile<XTensorType>();
set_tile(absmax, reduce_absmax_func.GetIdentityValue<ComputeDataType>());
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& a, const auto& b) {
return type_convert<ComputeDataType>(a) * type_convert<ComputeDataType>(b);
},
x,
xscale);
block_reduce2d(y, absmax, reduce_absmax_func);
move_tile_window(x_window, {0, Block_N});
move_tile_window(xscale_window, {Block_N});
}
// compute absmax, cross-lane->cross-warp
block_reduce2d_sync(absmax, reduce_max_func);
block_reduce2d_cross_warp_sync(absmax, smem, reduce_max_func);
// ex: yscale = absmax / 127 if int8
auto yscale = tile_elementwise_in(
[&](const auto& v_) {
return v_ / type_convert<ComputeDataType>(numeric<QYDataType>::max());
},
absmax);
store_tile(yscale_window, cast_tile<YScaleDataType>(yscale));
// reverse read x to reuse cache
ck_tile::index_t stride_to_right_most_window =
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(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& a, const auto& b) {
return type_convert<ComputeDataType>(a) * type_convert<ComputeDataType>(b);
},
x,
xscale);
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_);
});
store_tile(qy_window, qy);
move_tile_window(x_window, {0, -Block_N});
move_tile_window(xscale_window, {0, -Block_N});
move_tile_window(qy_window, {0, -Block_N});
}
}
};
} // namespace ck_tile

5
include/ck_tile/remod.py
View File

@@ -1,3 +1,4 @@
from datetime import datetime
import pathlib
from pathlib import Path
import subprocess
@@ -8,8 +9,8 @@ NS = 'ck_tile'
OPS = 'ops'
OPS_COMMON = 'common' # common header will be duplicated into ops/* other module
HEADER_COMMON = """// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.\n
HEADER_COMMON = f"""// SPDX-License-Identifier: MIT
// Copyright (c) 2018-{datetime.now().year}, Advanced Micro Devices, Inc. All rights reserved.\n
"""
# aa/bb/cc/file.hpp -> (aa, bb, cc, file.hpp)