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rocking
2024-10-22 21:18:42 +00:00
parent dfb4bf9488
commit 382a2af212
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21
example/ck_tile/06_rmsnorm2d/CMakeLists.txt Normal file
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set(EXAMPLE_RMSNORM2D_FWD "tile_example_rmsnorm2d_fwd")
# not using add_example_executable() to add this target, since we don't want this to have
# to be included in "make all/install/check"
message("adding example ${EXAMPLE_RMSNORM2D_FWD}")
file(GLOB INSTANCE_SRCS instances/*.cpp)
add_executable(${EXAMPLE_RMSNORM2D_FWD} EXCLUDE_FROM_ALL rmsnorm2d_fwd.cpp)
target_include_directories(${EXAMPLE_RMSNORM2D_FWD} PRIVATE ${CMAKE_CURRENT_LIST_DIR})
target_sources(${EXAMPLE_RMSNORM2D_FWD} PRIVATE ${INSTANCE_SRCS})
set(EXAMPLE_RMSNORM2D_FWD_COMPILE_OPTIONS)
# NOTE: we turn off undefined-func-template to let source compile without explicit declare function specializations
list(APPEND EXAMPLE_RMSNORM2D_FWD_COMPILE_OPTIONS -Wno-undefined-func-template -Wno-float-equal)
target_compile_options(${EXAMPLE_RMSNORM2D_FWD} PRIVATE ${EXAMPLE_RMSNORM2D_FWD_COMPILE_OPTIONS})
# TODO: we have to turn off this global prop, otherwise the progress bar generated
# by cmake will print too many files, execvp: /bin/sh: Argument list too long
# however, this property may affect global
# TODO: consider codegen a makefile by us
set_property(GLOBAL PROPERTY RULE_MESSAGES OFF)

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example/ck_tile/06_rmsnorm2d/README.md Normal file
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# Rmsnorm2D forward
This folder contains example for Rmsnorm2D forward 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_example_rmsnorm2d_fwd -j
```
This will result in an executable `build/bin/tile_example_rmsnorm2d_fwd`
## example
```
args:
-m m dimension (default:3328)
-n m dimension (default:4096)
-e epsilon (default:1e-5)
-v cpu validation or not (default:1)
-prec precision (default:fp16)
```

153
example/ck_tile/06_rmsnorm2d/instances/rmsnorm2d_fwd_api.cpp Normal file
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// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include <ck_tile/core.hpp>
#include "rmsnorm2d_fwd.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 kSaveInvRms_,
bool kTwoPass_>
using trait_ = rmsnorm2d_fwd_traits_<DataType_,
Repeat_M_,
Repeat_N_,
ThreadPerBlock_M_,
ThreadPerBlock_N_,
Vector_N_,
kPadN_,
kSaveInvRms_,
kTwoPass_>;
template <typename data_type>
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
if(a.n <= 64) {
r = rmsnorm2d_fwd_<trait_<data_type, 1, 1, 4, 64, 1, true, false, false>>(s, a);
}
else if(a.n <= 128) {
if (a.n % 2 == 0)
r = rmsnorm2d_fwd_<trait_<data_type, 1, 1, 4, 64, 2, true, false, false>>(s, a);
else
r = rmsnorm2d_fwd_<trait_<data_type, 1, 2, 4, 64, 1, true, false, false>>(s, a);
}
else if(a.n <= 256) {
if (a.n % 4 == 0)
r = rmsnorm2d_fwd_<trait_<data_type, 1, 1, 4, 64, 4, true, false, false>>(s, a);
else if (a.n % 2 == 0)
r = rmsnorm2d_fwd_<trait_<data_type, 1, 2, 4, 64, 2, true, false, false>>(s, a);
else
r = rmsnorm2d_fwd_<trait_<data_type, 1, 4, 4, 64, 1, true, false, false>>(s, a);
}
else if(a.n <= 512) {
if (a.n % 8 == 0)
r = rmsnorm2d_fwd_<trait_<data_type, 1, 1, 4, 64, 8, true, false, false>>(s, a);
else if (a.n % 4 == 0)
r = rmsnorm2d_fwd_<trait_<data_type, 1, 2, 4, 64, 4, true, false, false>>(s, a);
else if (a.n % 2 == 0)
r = rmsnorm2d_fwd_<trait_<data_type, 1, 4, 4, 64, 2, true, false, false>>(s, a);
else
r = rmsnorm2d_fwd_<trait_<data_type, 1, 8, 4, 64, 1, true, false, false>>(s, a);
}
else if(a.n <= 768) {
if (a.n % 4 == 0)
r = rmsnorm2d_fwd_<trait_<data_type, 1, 3, 4, 64, 4, true, false, false>>(s, a);
else if (a.n % 2 == 0)
r = rmsnorm2d_fwd_<trait_<data_type, 1, 6, 4, 64, 2, true, false, false>>(s, a);
else
r = rmsnorm2d_fwd_<trait_<data_type, 1,12, 4, 64, 1, true, false, false>>(s, a);
}
else if(a.n <= 1024) {
if (a.n % 8 == 0)
r = rmsnorm2d_fwd_<trait_<data_type, 1, 1, 2, 128, 8, true, false, false>>(s, a);
else if (a.n % 4 == 0)
r = rmsnorm2d_fwd_<trait_<data_type, 1, 2, 2, 128, 4, true, false, false>>(s, a);
else if (a.n % 2 == 0)
r = rmsnorm2d_fwd_<trait_<data_type, 1, 4, 2, 128, 2, true, false, false>>(s, a);
else
r = rmsnorm2d_fwd_<trait_<data_type, 1, 4, 1, 256, 1, true, false, false>>(s, a);
}
else if(a.n <= 1536) {
if (a.n % 8 == 0)
r = rmsnorm2d_fwd_<trait_<data_type, 1, 3, 4, 64, 8, true, false, false>>(s, a);
else if (a.n % 4 == 0)
r = rmsnorm2d_fwd_<trait_<data_type, 1, 3, 2, 128, 4, true, false, false>>(s, a);
else if (a.n % 2 == 0)
r = rmsnorm2d_fwd_<trait_<data_type, 1, 3, 1, 256, 2, true, false, false>>(s, a);
else
r = rmsnorm2d_fwd_<trait_<data_type, 1, 6, 1, 256, 1, true, false, false>>(s, a);
}
else if(a.n <= 2048) {
if (a.n % 8 == 0)
r = rmsnorm2d_fwd_<trait_<data_type, 1, 1, 1, 256, 8, true, false, false>>(s, a);
else if (a.n % 4 == 0)
r = rmsnorm2d_fwd_<trait_<data_type, 1, 2, 1, 256, 4, true, false, false>>(s, a);
else if (a.n % 2 == 0)
r = rmsnorm2d_fwd_<trait_<data_type, 1, 4, 1, 256, 2, true, false, false>>(s, a);
else
r = rmsnorm2d_fwd_<trait_<data_type, 1, 8, 1, 256, 1, true, false, false>>(s, a);
}
else if(a.n <= 3072) {
if (a.n % 8 == 0)
r = rmsnorm2d_fwd_<trait_<data_type, 1, 3, 1, 128, 8, true, false, false>>(s, a);
else if (a.n % 4 == 0)
r = rmsnorm2d_fwd_<trait_<data_type, 1, 3, 1, 256, 4, true, false, false>>(s, a);
else if (a.n % 2 == 0)
r = rmsnorm2d_fwd_<trait_<data_type, 1, 6, 1, 256, 2, true, false, false>>(s, a);
else
r = rmsnorm2d_fwd_<trait_<data_type, 1, 3, 1, 1024, 1, true, false, false>>(s, a);
}
else if(a.n <= 4096) {
if (a.n % 8 == 0)
r = rmsnorm2d_fwd_<trait_<data_type, 1, 2, 1, 256, 8, true, false, false>>(s, a);
else if (a.n % 4 == 0)
r = rmsnorm2d_fwd_<trait_<data_type, 1, 4, 1, 256, 4, true, false, false>>(s, a);
else if (a.n % 2 == 0)
r = rmsnorm2d_fwd_<trait_<data_type, 1, 2, 1, 1024, 2, true, false, false>>(s, a);
else
r = rmsnorm2d_fwd_<trait_<data_type, 1, 4, 1, 1024, 1, true, false, false>>(s, a);
}
else if(a.n > 4096) {
if (a.n % 8 == 0)
r = rmsnorm2d_fwd_<trait_<data_type, 1, 2, 1, 256, 8, true, false, true>>(s, a);
else if (a.n % 4 == 0)
r = rmsnorm2d_fwd_<trait_<data_type, 1, 4, 1, 256, 4, true, false, true>>(s, a);
else if (a.n % 2 == 0)
r = rmsnorm2d_fwd_<trait_<data_type, 1, 2, 1, 1024, 2, true, false, true>>(s, a);
else
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);
}
else if(t.data_type.compare("bf16") == 0)
{
return rmsnorm2d_fwd_b16_<ck_tile::bf16_t>(t, a, s);
}
if(r < 0)
throw std::runtime_error("Without supported instances!");
return r;
}

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example/ck_tile/06_rmsnorm2d/instances/rmsnorm2d_fwd_bf16_n1024_instance.cpp Normal file
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// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "rmsnorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd rms 2p
#if 0
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 2, 4, 64, 8, true , false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 4, 4, 64, 4, true , false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 8, 4, 64, 2, true , false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 16, 4, 64, 1, true , false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 1, 1, 256, 4, true , false, false>>(const S&, A);
#endif
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 1, 2, 128, 8, true, false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 2, 2, 128, 4, true, false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 4, 2, 128, 2, true, false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 4, 1, 256, 1, true, false, false>>(const S&, A);
// clang-format on

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example/ck_tile/06_rmsnorm2d/instances/rmsnorm2d_fwd_bf16_n1536_instance.cpp Normal file
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// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "rmsnorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd rms 2p
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 3, 4, 64, 8, true, false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 3, 2, 128, 4, true, false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 3, 1, 256, 2, true, false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 6, 1, 256, 1, true, false, false>>(const S&, A);
// clang-format on

14
example/ck_tile/06_rmsnorm2d/instances/rmsnorm2d_fwd_bf16_n2048_instance.cpp Normal file
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// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "rmsnorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd rms 2p
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 1, 1, 256, 8, true, false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 2, 1, 256, 4, true, false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 4, 1, 256, 2, true, false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 8, 1, 256, 1, true, false, false>>(const S&, A);
// clang-format on

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example/ck_tile/06_rmsnorm2d/instances/rmsnorm2d_fwd_bf16_n256_instance.cpp Normal file
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// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "rmsnorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd rms 2p
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 1, 4, 64, 4, true , false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 2, 4, 64, 2, true , false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 4, 4, 64, 1, true , false, false>>(const S&, A);
// clang-format on

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example/ck_tile/06_rmsnorm2d/instances/rmsnorm2d_fwd_bf16_n3072_instance.cpp Normal file
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// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "rmsnorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd rms 2p
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 3, 1, 128, 8, true, false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 3, 1, 256, 4, true, false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 6, 1, 256, 2, true, false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 3, 1, 1024, 1, true, false, false>>(const S&, A);
// clang-format on

14
example/ck_tile/06_rmsnorm2d/instances/rmsnorm2d_fwd_bf16_n4096_instance.cpp Normal file
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// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "rmsnorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd rms 2p
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 2, 1, 256, 8, true, false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 4, 1, 256, 4, true, false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 2, 1, 1024, 2, true, false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 4, 1, 1024, 1, true, false, false>>(const S&, A);
// clang-format on

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example/ck_tile/06_rmsnorm2d/instances/rmsnorm2d_fwd_bf16_n4096_tp_instance.cpp Normal file
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// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "rmsnorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd rms 2p
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 2, 1, 256, 8, true, false, true>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 4, 1, 256, 4, true, false, true>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 2, 1, 1024, 2, true, false, true>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 4, 1, 1024, 1, true, false, true>>(const S&, A);
// clang-format on

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example/ck_tile/06_rmsnorm2d/instances/rmsnorm2d_fwd_bf16_n512_instance.cpp Normal file
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// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "rmsnorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd rms 2p
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 1, 4, 64, 8, true , false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 2, 4, 64, 4, true , false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 4, 4, 64, 2, true , false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 8, 4, 64, 1, true , false, false>>(const S&, A);
// clang-format on

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example/ck_tile/06_rmsnorm2d/instances/rmsnorm2d_fwd_bf16_n64_n128_instance.cpp Normal file
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// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "rmsnorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd rms 2p
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 1, 4, 64, 1, true , false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 1, 4, 64, 2, true , false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 2, 4, 64, 1, true , false, false>>(const S&, A);
// clang-format on

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example/ck_tile/06_rmsnorm2d/instances/rmsnorm2d_fwd_bf16_n768_instance.cpp Normal file
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// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "rmsnorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd rms 2p
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 3, 4, 64, 4, true , false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 6, 4, 64, 2, true , false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 12, 4, 64, 1, true , false, false>>(const S&, A);
// clang-format on

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example/ck_tile/06_rmsnorm2d/instances/rmsnorm2d_fwd_fp16_n1024_instance.cpp Normal file
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// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "rmsnorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd rms 2p
#if 0
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 2, 4, 64, 8, true , false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 4, 4, 64, 4, true , false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 8, 4, 64, 2, true , false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 16, 4, 64, 1, true , false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 1, 1, 256, 4, true , false, false>>(const S&, A);
#endif
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 1, 2, 128, 8, true, false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 2, 2, 128, 4, true, false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 4, 2, 128, 2, true, false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 4, 1, 256, 1, true, false, false>>(const S&, A);
// clang-format on

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example/ck_tile/06_rmsnorm2d/instances/rmsnorm2d_fwd_fp16_n1536_instance.cpp Normal file
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// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "rmsnorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd rms 2p
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 3, 4, 64, 8, true, false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 3, 2, 128, 4, true, false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 3, 1, 256, 2, true, false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 6, 1, 256, 1, true, false, false>>(const S&, A);
// clang-format on

14
example/ck_tile/06_rmsnorm2d/instances/rmsnorm2d_fwd_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 "rmsnorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd rms 2p
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 1, 1, 256, 8, true, false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 2, 1, 256, 4, true, false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 4, 1, 256, 2, true, false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 8, 1, 256, 1, true, false, false>>(const S&, A);
// clang-format on

12
example/ck_tile/06_rmsnorm2d/instances/rmsnorm2d_fwd_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 "rmsnorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd rms 2p
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 1, 4, 64, 4, true , false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 2, 4, 64, 2, true , false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 4, 4, 64, 1, true , false, false>>(const S&, A);
// clang-format on

14
example/ck_tile/06_rmsnorm2d/instances/rmsnorm2d_fwd_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 "rmsnorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd rms 2p
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 3, 1, 128, 8, true, false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 3, 1, 256, 4, true, false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 6, 1, 256, 2, true, false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 3, 1, 1024, 1, true, false, false>>(const S&, A);
// clang-format on

14
example/ck_tile/06_rmsnorm2d/instances/rmsnorm2d_fwd_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 "rmsnorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd rms 2p
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 2, 1, 256, 8, true, false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 4, 1, 256, 4, true, false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 2, 1, 1024, 2, true, false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 4, 1, 1024, 1, true, false, false>>(const S&, A);
// clang-format on

14
example/ck_tile/06_rmsnorm2d/instances/rmsnorm2d_fwd_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 "rmsnorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd rms 2p
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 2, 1, 256, 8, true, false, true>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 4, 1, 256, 4, true, false, true>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 2, 1, 1024, 2, true, false, true>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 4, 1, 1024, 1, true, false, true>>(const S&, A);
// clang-format on

13
example/ck_tile/06_rmsnorm2d/instances/rmsnorm2d_fwd_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 "rmsnorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd rms 2p
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 1, 4, 64, 8, true , false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 2, 4, 64, 4, true , false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 4, 4, 64, 2, true , false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 8, 4, 64, 1, true , false, false>>(const S&, A);
// clang-format on

12
example/ck_tile/06_rmsnorm2d/instances/rmsnorm2d_fwd_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 "rmsnorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd rms 2p
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 1, 4, 64, 1, true , false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 1, 4, 64, 2, true , false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 2, 4, 64, 1, true , false, false>>(const S&, A);
// clang-format on

12
example/ck_tile/06_rmsnorm2d/instances/rmsnorm2d_fwd_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 "rmsnorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd rms 2p
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 3, 4, 64, 4, true , false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 6, 4, 64, 2, true , false, false>>(const S&, A);
template float rmsnorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 12, 4, 64, 1, true , false, false>>(const S&, A);
// clang-format on

65
example/ck_tile/06_rmsnorm2d/instances/rmsnorm2d_fwd_instance_common.hpp Normal file
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@@ -0,0 +1,65 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include <ck_tile/core.hpp>
#include "rmsnorm2d_fwd.hpp"
#include <iostream>
#pragma once
using S = ck_tile::stream_config;
using A = rmsnorm2d_fwd_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 kSaveInvRms_,
bool kTwoPass_>
using trait_ = rmsnorm2d_fwd_traits_<DataType_,
Repeat_M_,
Repeat_N_,
ThreadPerBlock_M_,
ThreadPerBlock_N_,
Vector_N_,
kPadN_,
kSaveInvRms_,
kTwoPass_>;
template <typename Traits_>
float rmsnorm2d_fwd_(const S& s, A a)
{
using DataType = typename Traits_::DataType;
using PipelineProblem =
ck_tile::Rmsnorm2dFwdPipelineProblem<typename RmsNormTypeConfig<DataType>::XDataType,
typename RmsNormTypeConfig<DataType>::GammaDataType,
typename RmsNormTypeConfig<DataType>::ComputeDataType,
typename RmsNormTypeConfig<DataType>::YDataType,
typename RmsNormTypeConfig<DataType>::InvRmsDataType,
typename Traits_::Shape,
Traits_::kPadN,
Traits_::kSaveInvRms,
Traits_::kTwoPass>;
using OnePassPipeline = ck_tile::Rmsnorm2dFwdPipelineOnePass<PipelineProblem>;
using TwoPassPipeline = ck_tile::Rmsnorm2dFwdPipelineTwoPass<PipelineProblem>;
using Pipeline = std::conditional_t<Traits_::kTwoPass, TwoPassPipeline, OnePassPipeline>;
using Kernel = ck_tile::Rmsnorm2dFwd<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));
}

179
example/ck_tile/06_rmsnorm2d/rmsnorm2d_fwd.cpp Normal file
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@@ -0,0 +1,179 @@
#include "ck_tile/host.hpp"
#include "rmsnorm2d_fwd.hpp"
#include <cstring>
// different threshold for different dtype
template <typename DataType>
auto get_elimit()
{
double rtol = 1e-2;
double atol = 1e-2;
return ck_tile::make_tuple(rtol, atol);
}
template <>
auto get_elimit<ck_tile::bf16_t>()
{
double rtol = 1e-2;
double atol = 1e-2;
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("save_rms", "0", "save rms(invrms) or not. set to 1 in training case")
.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 SaveRms>
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;
float epsilon = arg_parser.get_float("e");
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 = RmsNormTypeConfig<DataType>;
using XDataType = typename TypeConfig::XDataType;
using YDataType = typename TypeConfig::YDataType;
using GammaDataType = typename TypeConfig::GammaDataType;
using InvRmsDataType =
std::conditional_t<SaveRms, typename TypeConfig::InvRmsDataType, ck_tile::null_type>;
using ComputeDataType = typename TypeConfig::ComputeDataType;
// host verify
ck_tile::HostTensor<XDataType> x_host({m, n}, {stride, 1});
ck_tile::HostTensor<GammaDataType> gamma_host({n});
ck_tile::HostTensor<YDataType> y_host_ref({m, n}, {stride, 1});
ck_tile::HostTensor<YDataType> y_host_dev({m, n}, {stride, 1});
ck_tile::HostTensor<InvRmsDataType> invRms_host_ref({m});
ck_tile::FillUniformDistribution<XDataType>{-.5f, .5f}(x_host);
ck_tile::FillUniformDistribution<GammaDataType>{-.5f, .5f}(gamma_host);
ck_tile::DeviceMem x_buf(x_host.get_element_space_size_in_bytes());
ck_tile::DeviceMem gamma_buf(gamma_host.get_element_space_size_in_bytes());
ck_tile::DeviceMem y_buf(y_host_dev.get_element_space_size_in_bytes());
x_buf.ToDevice(x_host.data());
gamma_buf.ToDevice(gamma_host.data());
std::cout << "[" << data_type << "]"
<< " m:" << m << ", n:" << n << ", stride:" << stride << std::flush;
rmsnorm2d_fwd_traits traits{data_type, SaveRms};
rmsnorm2d_fwd_args args{x_buf.GetDeviceBuffer(),
gamma_buf.GetDeviceBuffer(),
y_buf.GetDeviceBuffer(),
nullptr,
epsilon,
m,
n,
stride};
float ave_time = rmsnorm2d_fwd(
traits, args, ck_tile::stream_config{nullptr, true, kname ? 1 : 0, warmup, repeat});
std::size_t num_byte =
sizeof(XDataType) * m * n + sizeof(GammaDataType) * n + sizeof(YDataType) * 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)
{
// reference
ck_tile::reference_rmsnorm2d_fwd<XDataType,
GammaDataType,
ComputeDataType,
YDataType,
InvRmsDataType>(
x_host, gamma_host, y_host_ref, invRms_host_ref, epsilon);
y_buf.FromDevice(y_host_dev.data());
auto [rtol, atol] = get_elimit<DataType>();
if(stride == n)
{
pass = ck_tile::check_err(
y_host_dev, y_host_ref, std::string("OUT Error: Incorrect results!"), rtol, atol);
}
else
{
for(int i_r = 0; i_r < m; i_r++)
{
std::vector<YDataType> y_host_dev_row(y_host_dev.begin() + i_r * stride,
y_host_dev.begin() + i_r * stride + n);
std::vector<YDataType> y_host_ref_row(y_host_ref.begin() + i_r * stride,
y_host_ref.begin() + i_r * stride + n);
pass &= ck_tile::check_err(y_host_dev_row,
y_host_ref_row,
std::string("OUT[") + 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");
int save_rms = arg_parser.get_int("save_rms");
if(data_type == "fp16" && save_rms)
{
return run<ck_tile::half_t, true>(arg_parser) ? 0 : -2;
}
else if(data_type == "fp16" && !save_rms)
{
return run<ck_tile::half_t, false>(arg_parser) ? 0 : -2;
}
else if(data_type == "bf16" && save_rms)
{
return run<ck_tile::bf16_t, true>(arg_parser) ? 0 : -2;
}
else if(data_type == "bf16" && !save_rms)
{
return run<ck_tile::bf16_t, true>(arg_parser) ? 0 : -2;
}
return -3;
}

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example/ck_tile/06_rmsnorm2d/rmsnorm2d_fwd.hpp Normal file
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@@ -0,0 +1,117 @@
// 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/rmsnorm2d.hpp"
#include <string>
template <typename DataType>
struct RmsNormTypeConfig;
template <>
struct RmsNormTypeConfig<ck_tile::half_t>
{
using XDataType = ck_tile::half_t;
using YDataType = ck_tile::half_t;
using GammaDataType = ck_tile::half_t;
using InvRmsDataType = ck_tile::half_t;
using ComputeDataType = float;
};
template <>
struct RmsNormTypeConfig<ck_tile::bf16_t>
{
using XDataType = ck_tile::bf16_t;
using YDataType = ck_tile::bf16_t;
using GammaDataType = ck_tile::bf16_t;
using InvRmsDataType = ck_tile::bf16_t;
using ComputeDataType = float;
};
// runtime args
struct rmsnorm2d_fwd_args : public ck_tile::Rmsnorm2dFwdHostArgs
{
};
// 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 kSaveInvRms_,
bool kTwoPass_>
struct rmsnorm2d_fwd_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::Rmsnorm2dShape<BlockTile, BlockWarps, WarpTile, Vector>;
static constexpr bool kPadN = kPadN_;
static constexpr bool kSaveInvRms = kSaveInvRms_;
static constexpr bool kTwoPass = kTwoPass_;
};
template <typename Traits_>
float rmsnorm2d_fwd_(const ck_tile::stream_config& s, rmsnorm2d_fwd_args a);
// This is the public API, will be generated by script
struct rmsnorm2d_fwd_traits
{
std::string data_type;
bool save_mean_var;
};
float rmsnorm2d_fwd(rmsnorm2d_fwd_traits, rmsnorm2d_fwd_args, const ck_tile::stream_config&);

1
example/ck_tile/CMakeLists.txt
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@@ -7,3 +7,4 @@ add_subdirectory(02_layernorm2d)
add_subdirectory(03_gemm)
add_subdirectory(04_img2col)
add_subdirectory(05_reduce)
add_subdirectory(06_rmsnorm2d)

1
include/ck_tile/host.hpp
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@@ -23,6 +23,7 @@
#include "ck_tile/host/reference/reference_im2col.hpp"
#include "ck_tile/host/reference/reference_layernorm2d_fwd.hpp"
#include "ck_tile/host/reference/reference_reduce.hpp"
#include "ck_tile/host/reference/reference_rmsnorm2d_fwd.hpp"
#include "ck_tile/host/reference/reference_softmax.hpp"
#include "ck_tile/host/stream_config.hpp"
#include "ck_tile/host/timer.hpp"

52
include/ck_tile/host/reference/reference_rmsnorm2d_fwd.hpp Normal file
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@@ -0,0 +1,52 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "ck_tile/core.hpp"
#include "ck_tile/host/host_tensor.hpp"
namespace ck_tile {
template <typename XDataType,
typename GammaDataType,
typename ComputeDataType,
typename YDataType,
typename InvRmsDataType>
void reference_rmsnorm2d_fwd(const HostTensor<XDataType>& x_m_n,
const HostTensor<GammaDataType>& gamma_n,
HostTensor<YDataType>& y_m_n,
HostTensor<InvRmsDataType>& invRms_m,
ComputeDataType epsilon)
{
auto rmsnorm2d_fwd_func = [&](auto m) {
const int N = x_m_n.mDesc.get_lengths()[1];
ComputeDataType mean_square = 0;
ComputeDataType divisor = 0;
for(int n = 0; n < N; ++n)
{
ComputeDataType x = ck_tile::type_convert<ComputeDataType>(x_m_n(m, n));
mean_square += x * x;
}
mean_square = mean_square / N;
divisor = ck_tile::type_convert<ComputeDataType>(1) / ck_tile::sqrt(mean_square + epsilon);
if constexpr(!std::is_same_v<InvRmsDataType, ck_tile::null_type>)
invRms_m(m) = ck_tile::type_convert<InvRmsDataType>(divisor);
for(int n = 0; n < N; ++n)
{
ComputeDataType x = ck_tile::type_convert<ComputeDataType>(x_m_n(m, n));
ComputeDataType gamma = ck_tile::type_convert<ComputeDataType>(gamma_n(n));
auto y = x * divisor * gamma;
y_m_n(m, n) = ck_tile::type_convert<YDataType>(y);
}
};
make_ParallelTensorFunctor(rmsnorm2d_fwd_func,
invRms_m.mDesc.get_lengths()[0])(std::thread::hardware_concurrency());
}
} // namespace ck_tile

12
include/ck_tile/ops/rmsnorm2d.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/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"
#include "ck_tile/ops/rmsnorm2d/pipeline/rmsnorm2d_fwd_pipeline_two_pass.hpp"
#include "ck_tile/ops/common/tensor_layout.hpp"

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// 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 Rmsnorm2dFwdHostArgs
{
const void* p_x;
const void* p_gamma;
void* p_y;
void* p_invRms;
float epsilon;
index_t m;
index_t n;
index_t stride; // row_stride
};
// TODO: Extract some type to wrapper class
template <typename Pipeline_>
struct Rmsnorm2dFwd
{
using Pipeline = remove_cvref_t<Pipeline_>;
using Problem = typename Pipeline::Problem;
using XDataType = remove_cvref_t<typename Problem::XDataType>;
using GammaDataType = remove_cvref_t<typename Problem::GammaDataType>;
using ComputeDataType = remove_cvref_t<typename Problem::ComputeDataType>;
using YDataType = remove_cvref_t<typename Problem::YDataType>;
using InvRmsDataType = remove_cvref_t<typename Problem::InvRmsDataType>;
static constexpr bool kHasGamma = !std::is_same_v<GammaDataType, null_type>;
static constexpr bool kSaveInvRms = Problem::kSaveInvRms;
static constexpr index_t Block_M = Problem::BlockShape::Block_M;
static constexpr index_t Block_N = Problem::BlockShape::Block_N;
static constexpr bool kPadM = false; // always no need to pad along M
static constexpr bool kPadN = Problem::kPadN;
static constexpr bool kTwoPass = Problem::kTwoPass;
static constexpr index_t 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_gamma;
void* p_y;
void* p_invRms;
float epsilon;
index_t m;
index_t n;
index_t stride; // row_stride
};
using Hargs = Rmsnorm2dFwdHostArgs;
CK_TILE_HOST static constexpr Kargs MakeKargs(const Hargs& hargs)
{
return Kargs{hargs.p_x,
hargs.p_gamma,
hargs.p_y,
hargs.p_invRms,
hargs.epsilon,
hargs.m,
hargs.n,
hargs.stride};
}
CK_TILE_HOST static constexpr auto GridSize(const Hargs& hargs)
{
return (hargs.m + Block_M - 1) / 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 (kSaveInvRms) n += "_rms";
if (kTwoPass) n += "_2p";
return n; }();
#define _SS_ std::string
#define _TS_ std::to_string
return _SS_("rmsnorm2d_fwd_") + _SS_(t2s<XDataType>::name) + "_" +
_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>{});
// NOTE: we don't do any pad in this kernel for loading, assume that inside kernel will
// check the max count dynamically
const auto tmp2_ = pad_tensor_view(
tmp_, make_tuple(number<Block_M>{}, number<Block_N>{}), sequence<false, false>{});
return make_tile_window(
tmp2_, make_tuple(number<Block_M>{}, number<Block_N>{}), {iM, 0});
}();
const auto gamma_window = [&]() {
const auto tmp_ = make_naive_tensor_view<address_space_enum::global>(
static_cast<const GammaDataType*>(kargs.p_gamma),
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<false>{});
return make_tile_window(tmp2_, make_tuple(number<Block_N>{}), {0});
}();
auto y_window = [&]() {
auto tmp_ = make_naive_tensor_view<address_space_enum::global>(
static_cast<YDataType*>(kargs.p_y),
make_tuple(kargs.m, kargs.n),
make_tuple(kargs.stride, 1),
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});
}();
auto inv_rms_window = [&]() {
if constexpr(kSaveInvRms)
{
const auto inv_rms_m = [&]() {
const auto inv_rms_dram_naive =
make_naive_tensor_view_packed<address_space_enum::global>(
static_cast<InvRmsDataType*>(kargs.p_invRms),
make_tuple(kargs.m),
number<1>{});
return pad_tensor_view(
inv_rms_dram_naive, make_tuple(number<Block_M>{}), sequence<kPadM>{});
}();
return make_tile_window(inv_rms_m, make_tuple(number<Block_M>{}), {iM});
}
else
return make_null_tile_window(make_tuple(number<Block_M>{}));
}();
__shared__ char smem[GetSmemSize()];
Pipeline{}(x_window,
gamma_window,
y_window,
inv_rms_window,
static_cast<const ComputeDataType>(kargs.epsilon),
kargs.n,
smem);
}
};
} // namespace ck_tile

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// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, 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

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// 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/reduce2d/block/block_reduce2d_problem.hpp"
#include "ck_tile/ops/reduce2d/block/block_reduce2d.hpp"
namespace ck_tile {
struct Rmsnorm2dFwdPipelineDefaultPolicy
{
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 MakeGammaBlockTileDistribution()
{
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::XDataType,
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::XDataType,
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::XDataType,
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

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// 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_ = Rmsnorm2dFwdPipelineDefaultPolicy>
struct Rmsnorm2dFwdPipelineOnePass
{
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 GammaDataType = ck_tile::remove_cvref_t<typename Problem::GammaDataType>;
using ComputeDataType = ck_tile::remove_cvref_t<typename Problem::ComputeDataType>;
using YDataType = ck_tile::remove_cvref_t<typename Problem::YDataType>;
using InvRmsDataType = ck_tile::remove_cvref_t<typename Problem::InvRmsDataType>;
static constexpr bool kHasGamma = !std::is_same_v<GammaDataType, ck_tile::null_type>;
static constexpr bool kSaveInvRms = Problem::kSaveInvRms;
static constexpr bool kNeedCrossWarpSync = Problem::kNeedCrossWarpSync;
static constexpr bool kPadM = false; // TODO - BlockRmsnorm2dFwdProblem::kPadM
static constexpr bool kPadN = Problem::kPadN;
static constexpr const char* name = []() {
if constexpr(kNeedCrossWarpSync)
return "bpr"; // block per row
else
return "wpr"; // warp per row
}();
CK_TILE_HOST_DEVICE static constexpr index_t GetSmemSize()
{
return Policy::template GetSmemSize<Problem>();
}
template <typename XWindow, typename GammaWindow, typename YWindow, typename InvRmsWindow>
CK_TILE_DEVICE auto operator()(const XWindow& x_window_,
const GammaWindow& gamma_window_,
YWindow& y_window,
InvRmsWindow& inv_rms_window,
ComputeDataType epsilon,
ck_tile::index_t row_size,
void* smem) const
{
const auto x_window =
make_tile_window(x_window_, Policy::template MakeXBlockTileDistribution<Problem>());
const auto gamma_window = make_tile_window(
gamma_window_, Policy::template MakeGammaBlockTileDistribution<Problem>());
auto reduce_square_sum_func = [](const auto& v0, const auto& v1) { return v0 + v1 * v1; };
auto reduce_sum_func = [](const auto& v0, const auto& v1) { return v0 + v1; };
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);
// load gamma (TODO: support no gamma?)
const auto gamma = load_tile(gamma_window);
// compute mean square each-thread->cross-lane->cross-warp
auto square_sum = block_reduce2d(x, 0, reduce_square_sum_func);
block_reduce2d_sync(square_sum, reduce_sum_func);
block_reduce2d_cross_warp_sync(square_sum, smem, reduce_sum_func);
// compute inv-rms
auto inv_rms = tile_elementwise_in(
[&](const auto& v_) {
return type_convert<ComputeDataType>(1.0f) / (sqrt(v_ / row_size + epsilon));
},
square_sum);
if constexpr(kSaveInvRms)
store_tile(inv_rms_window, cast_tile<InvRmsDataType>(inv_rms));
// rmsnorm computation
auto y = make_static_distributed_tensor<YDataType>(x.get_tile_distribution());
sweep_tile(y, [&, inv_rms_ = inv_rms](auto idx) {
constexpr auto i_idx = make_tuple(idx[number<0>{}]);
constexpr auto j_idx = make_tuple(idx[number<1>{}]);
const auto gamma_ = type_convert<ComputeDataType>(gamma[j_idx]);
const auto x_ = type_convert<ComputeDataType>(x[idx]);
auto y_ = x_ * inv_rms_[i_idx] * gamma_;
y(idx) = type_convert<YDataType>(y_);
});
store_tile(y_window, y);
}
};
} // namespace ck_tile

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include/ck_tile/ops/rmsnorm2d/pipeline/rmsnorm2d_fwd_pipeline_problem.hpp Normal file
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// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "ck_tile/core/utility/type_traits.hpp"
namespace ck_tile {
template <typename XDataType_,
typename GammaDataType_,
typename ComputeDataType_,
typename YDataType_,
typename InvRmsDataType_,
typename BlockShape_,
bool kPadN_,
bool kSaveInvRms_,
bool kTwoPass_>
struct Rmsnorm2dFwdPipelineProblem
{
using XDataType = remove_cvref_t<XDataType_>;
using GammaDataType = remove_cvref_t<GammaDataType_>;
using ComputeDataType = remove_cvref_t<ComputeDataType_>;
using YDataType = remove_cvref_t<YDataType_>;
using InvRmsDataType = remove_cvref_t<InvRmsDataType_>;
using BlockShape = remove_cvref_t<BlockShape_>;
static constexpr bool kNeedCrossLaneSync = BlockShape::ThreadPerWarp_N > 1;
static constexpr bool kNeedCrossWarpSync = BlockShape::WarpPerBlock_N > 1;
static constexpr bool kPadN = kPadN_;
static constexpr bool kSaveInvRms = kSaveInvRms_;
static constexpr bool kTwoPass = kTwoPass_;
};
} // namespace ck_tile

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include/ck_tile/ops/rmsnorm2d/pipeline/rmsnorm2d_fwd_pipeline_two_pass.hpp Normal file
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// 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_ = Rmsnorm2dFwdPipelineDefaultPolicy>
struct Rmsnorm2dFwdPipelineTwoPass
{
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 GammaDataType = ck_tile::remove_cvref_t<typename Problem::GammaDataType>;
using ComputeDataType = ck_tile::remove_cvref_t<typename Problem::ComputeDataType>;
using YDataType = ck_tile::remove_cvref_t<typename Problem::YDataType>;
using InvRmsDataType = ck_tile::remove_cvref_t<typename Problem::InvRmsDataType>;
static constexpr bool kHasGamma = !std::is_same_v<GammaDataType, ck_tile::null_type>;
static constexpr bool kSaveInvRms = Problem::kSaveInvRms;
static constexpr bool kNeedCrossWarpSync = Problem::kNeedCrossWarpSync;
static constexpr bool kPadM = false; // TODO - BlockRmsnorm2dFwdProblem::kPadM
static constexpr bool kPadN = Problem::kPadN;
static constexpr const char* name = []() {
if constexpr(kNeedCrossWarpSync)
return "bpr"; // block per row
else
return "wpr"; // warp per row
}();
CK_TILE_HOST_DEVICE static constexpr index_t GetSmemSize()
{
return Policy::template GetSmemSize<Problem>();
}
template <typename XWindow, typename GammaWindow, typename YWindow, typename InvRmsWindow>
CK_TILE_DEVICE auto operator()(const XWindow& x_window_,
const GammaWindow& gamma_window_,
YWindow& y_window,
InvRmsWindow& inv_rms_window,
ComputeDataType epsilon,
ck_tile::index_t row_size,
void* smem) const
{
auto x_window =
make_tile_window(x_window_, Policy::template MakeXBlockTileDistribution<Problem>());
auto gamma_window = make_tile_window(
gamma_window_, Policy::template MakeGammaBlockTileDistribution<Problem>());
// Problem::BlockShape
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_square_sum_func = [](const auto& v0, const auto& v1) { return v0 + v1 * v1; };
auto reduce_sum_func = [](const auto& v0, const auto& v1) { return v0 + v1; };
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(load_tile(x_window));
auto square_sum = block_reduce2d.template MakeYBlockTile<XTensorType>();
set_tile(square_sum, 0);
for(int iN = __builtin_amdgcn_readfirstlane(0); iN < num_n_tile_iteration; ++iN)
{
const auto x = load_tile(x_window);
block_reduce2d(x, square_sum, reduce_square_sum_func);
move_tile_window(x_window, {0, Block_N});
}
block_reduce2d_sync(square_sum, reduce_sum_func);
block_reduce2d_cross_warp_sync(square_sum, smem, reduce_sum_func);
// compute inv-rms
auto inv_rms = tile_elementwise_in(
[&](const auto& v_) {
return type_convert<ComputeDataType>(1.0f) / (sqrt(v_ / row_size + epsilon));
},
square_sum);
if constexpr(kSaveInvRms)
store_tile(inv_rms_window, cast_tile<InvRmsDataType>(inv_rms));
// 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(gamma_window, {stride_to_right_most_window});
move_tile_window(y_window, {0, stride_to_right_most_window});
// rmsnorm computation
for(int iN = __builtin_amdgcn_readfirstlane(0); iN < num_n_tile_iteration; ++iN)
{
const auto x = load_tile(x_window);
// load gamma/beta (TODO: support no gamma/beta?)
const auto gamma = load_tile(gamma_window);
auto y = make_static_distributed_tensor<YDataType>(x.get_tile_distribution());
sweep_tile(y, [&, inv_rms_ = inv_rms](auto idx) {
constexpr auto i_idx = make_tuple(idx[number<0>{}]);
constexpr auto j_idx = make_tuple(idx[number<1>{}]);
const auto gamma_ = type_convert<ComputeDataType>(gamma[j_idx]);
const auto x_ = type_convert<ComputeDataType>(x[idx]);
auto y_ = x_ * inv_rms_[i_idx] * gamma_;
y(idx) = type_convert<YDataType>(y_);
});
store_tile(y_window, y);
move_tile_window(x_window, {0, -Block_N});
move_tile_window(gamma_window, {-Block_N});
move_tile_window(y_window, {0, -Block_N});
}
}
};
} // namespace ck_tile