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Commit 5cfd751b authored by carlushuang's avatar carlushuang
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refactor layernorm2d pipeline and add block-per-block utility

parent 68e67701
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example/ck_tile/02_layernorm2d/instances/layernorm2d_fwd_api.cpp
View file @ 5cfd751b
......@@ -2,184 +2,87 @@
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include <ck_tile/core.hpp>
#include "layernorm2d_fwd.hpp"
#include "layernorm2d_fwd_instance_common.hpp"
template <typename DataType,
ck_tile::index_t kNRepeat,
ck_tile::index_t kMThreadPerBlock,
ck_tile::index_t kNThreadPerBlock,
ck_tile::index_t kVectorAccessSize,
bool kPadN,
bool kTwoPass = false>
using trait_ = layernorm2d_fwd_traits_<DataType,
kNRepeat,
kMThreadPerBlock,
kNThreadPerBlock,
kVectorAccessSize,
kPadN,
false,
kTwoPass>;
template <typename data_type>
float layernorm2d_fwd_b16_(layernorm2d_fwd_traits /*t*/,
layernorm2d_fwd_args a,
const ck_tile::stream_config& s)
{
#if 1
float r = -1;
// clang-format off
// rm rn tm tn vn pd mv 2p
if(a.n <= 64) {
r = layernorm2d_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 = layernorm2d_fwd_<trait_<data_type, 1, 1, 4, 64, 2, true, false, false>>(s, a);
else
r = layernorm2d_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 = layernorm2d_fwd_<trait_<data_type, 1, 1, 4, 64, 4, true, false, false>>(s, a);
else if (a.n % 2 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 2, 4, 64, 2, true, false, false>>(s, a);
else
r = layernorm2d_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 = layernorm2d_fwd_<trait_<data_type, 1, 1, 4, 64, 8, true, false, false>>(s, a);
else if (a.n % 4 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 2, 4, 64, 4, true, false, false>>(s, a);
else if (a.n % 2 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 4, 4, 64, 2, true, false, false>>(s, a);
else
r = layernorm2d_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 = layernorm2d_fwd_<trait_<data_type, 1, 3, 4, 64, 4, true, false, false>>(s, a);
else if (a.n % 2 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 6, 4, 64, 2, true, false, false>>(s, a);
else
r = layernorm2d_fwd_<trait_<data_type, 1,12, 4, 64, 1, true, false, false>>(s, a);
}
else if(a.n <= 1024) {
if (a.n % 4 == 0)
// r = layernorm2d_fwd_<trait_<data_type, 1, 4, 4, 64, 4, true, false, false>>(s, a);
r = layernorm2d_fwd_<trait_<data_type, 1, 1, 1, 256, 4, true, false, false>>(s, a);
else if (a.n % 8 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 2, 4, 64, 8, true, false, false>>(s, a);
else if (a.n % 2 == 0)
r = layernorm2d_fwd_<trait_<data_type, 1, 8, 4, 64, 2, true, false, false>>(s, a);
else
r = layernorm2d_fwd_<trait_<data_type, 1, 16, 4, 64, 1, true, false, false>>(s, a);
}
return r;
#else
return layernorm2d_fwd_<trait_<data_type, 1, 1, 1, 256, 4, true, false, false>>(s, a);
#endif
// clang-format on
}
float layernorm2d_fwd(layernorm2d_fwd_traits t,
layernorm2d_fwd_args a,
const ck_tile::stream_config& s)
{
float r = -1;
if(t.data_type.compare("fp16") == 0)
{
if(a.N % 4 == 0)
{
if(a.N <= 128)
{
return a.N == 128
? layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 4, 32, 4, false>>(s, a)
: layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 4, 32, 4, true>>(s, a);
}
else if(a.N <= 256)
{
return a.N == 256
? layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 4, 64, 4, false>>(s, a)
: layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 4, 64, 4, true>>(s, a);
}
else if(a.N <= 512)
{
return a.N == 512
? layernorm2d_fwd_<trait_<ck_tile::fp16_t, 2, 4, 64, 4, false>>(s, a)
: layernorm2d_fwd_<trait_<ck_tile::fp16_t, 2, 4, 64, 4, true>>(s, a);
}
else if(a.N <= 1024)
{
return a.N == 1024
? layernorm2d_fwd_<trait_<ck_tile::fp16_t, 4, 4, 64, 4, false>>(s, a)
: layernorm2d_fwd_<trait_<ck_tile::fp16_t, 4, 4, 64, 4, true>>(s, a);
}
else if(a.N <= 2048)
{
return a.N == 2048
? layernorm2d_fwd_<trait_<ck_tile::fp16_t, 8, 4, 64, 4, false>>(s, a)
: layernorm2d_fwd_<trait_<ck_tile::fp16_t, 8, 4, 64, 4, true>>(s, a);
}
else
{
return a.N % 2048 == 0
? layernorm2d_fwd_<trait_<ck_tile::fp16_t, 8, 4, 64, 4, false, true>>(s,
a)
: layernorm2d_fwd_<trait_<ck_tile::fp16_t, 8, 4, 64, 4, true, true>>(s,
a);
}
}
else if(a.N % 2 == 0)
{
if(a.N <= 128)
{
return layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 4, 64, 2, true>>(s, a);
}
else if(a.N <= 256)
{
return layernorm2d_fwd_<trait_<ck_tile::fp16_t, 2, 4, 64, 2, true>>(s, a);
}
else if(a.N <= 512)
{
return layernorm2d_fwd_<trait_<ck_tile::fp16_t, 4, 4, 64, 2, true>>(s, a);
}
else if(a.N <= 1024)
{
return layernorm2d_fwd_<trait_<ck_tile::fp16_t, 8, 4, 64, 2, true>>(s, a);
}
else if(a.N <= 2048)
{
return layernorm2d_fwd_<trait_<ck_tile::fp16_t, 16, 4, 64, 2, true>>(s, a);
}
else
{
return layernorm2d_fwd_<trait_<ck_tile::fp16_t, 16, 4, 64, 2, true, true>>(s, a);
}
}
else
{
return a.N <= 2048
? layernorm2d_fwd_<trait_<ck_tile::fp16_t, 32, 4, 64, 1, true, false>>(s, a)
: layernorm2d_fwd_<trait_<ck_tile::fp16_t, 32, 4, 64, 1, true, true>>(s, a);
}
return layernorm2d_fwd_b16_<ck_tile::fp16_t>(t, a, s);
}
else if(t.data_type.compare("bf16") == 0)
{
if(a.N % 4 == 0)
{
if(a.N <= 128)
{
return a.N == 128
? layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 4, 32, 4, false>>(s, a)
: layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 4, 32, 4, true>>(s, a);
}
else if(a.N <= 256)
{
return a.N == 256
? layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 4, 64, 4, false>>(s, a)
: layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 4, 64, 4, true>>(s, a);
}
else if(a.N <= 512)
{
return a.N == 512
? layernorm2d_fwd_<trait_<ck_tile::bf16_t, 2, 4, 64, 4, false>>(s, a)
: layernorm2d_fwd_<trait_<ck_tile::bf16_t, 2, 4, 64, 4, true>>(s, a);
}
else if(a.N <= 1024)
{
return a.N == 1024
? layernorm2d_fwd_<trait_<ck_tile::bf16_t, 4, 4, 64, 4, false>>(s, a)
: layernorm2d_fwd_<trait_<ck_tile::bf16_t, 4, 4, 64, 4, true>>(s, a);
}
else if(a.N <= 2048)
{
return a.N == 2048
? layernorm2d_fwd_<trait_<ck_tile::bf16_t, 8, 4, 64, 4, false>>(s, a)
: layernorm2d_fwd_<trait_<ck_tile::bf16_t, 8, 4, 64, 4, true>>(s, a);
}
else
{
return a.N % 2048 == 0
? layernorm2d_fwd_<trait_<ck_tile::bf16_t, 8, 4, 64, 4, false, true>>(s,
a)
: layernorm2d_fwd_<trait_<ck_tile::bf16_t, 8, 4, 64, 4, true, true>>(s,
a);
}
}
else if(a.N % 2 == 0)
{
if(a.N <= 128)
{
return layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 4, 64, 2, true>>(s, a);
}
else if(a.N <= 256)
{
return layernorm2d_fwd_<trait_<ck_tile::bf16_t, 2, 4, 64, 2, true>>(s, a);
}
else if(a.N <= 512)
{
return layernorm2d_fwd_<trait_<ck_tile::bf16_t, 4, 4, 64, 2, true>>(s, a);
}
else if(a.N <= 1024)
{
return layernorm2d_fwd_<trait_<ck_tile::bf16_t, 8, 4, 64, 2, true>>(s, a);
}
else if(a.N <= 2048)
{
return layernorm2d_fwd_<trait_<ck_tile::bf16_t, 16, 4, 64, 2, true>>(s, a);
}
else
{
return layernorm2d_fwd_<trait_<ck_tile::bf16_t, 16, 4, 64, 2, true, true>>(s, a);
}
}
else
{
return a.N <= 2048
? layernorm2d_fwd_<trait_<ck_tile::bf16_t, 32, 4, 64, 1, true, false>>(s, a)
: layernorm2d_fwd_<trait_<ck_tile::bf16_t, 32, 4, 64, 1, true, true>>(s, a);
}
return layernorm2d_fwd_b16_<ck_tile::bf16_t>(t, a, s);
}
if(r < 0)
throw std::runtime_error("Without supported instances!");
......
example/ck_tile/02_layernorm2d/instances/layernorm2d_fwd_bf16_instance.cpp deleted 100644 → 0
View file @ 68e67701
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "layernorm2d_fwd_instance_common.hpp"
template <ck_tile::index_t kNRepeat,
ck_tile::index_t kMThreadPerBlock,
ck_tile::index_t kNThreadPerBlock,
ck_tile::index_t kkVectorAccessSize,
bool kTwoPass>
using t = layernorm2d_fwd_traits_<ck_tile::bf16_t,
kNRepeat,
kMThreadPerBlock,
kNThreadPerBlock,
kkVectorAccessSize,
false,
false,
kTwoPass>;
// Disable all vector 8fp16 read/write instances as it has performance issue regarding compiler
// template float layernorm2d_fwd_<t<1, 4, 16, 8, false>>(const S&, A);
// template float layernorm2d_fwd_<t<1, 4, 32, 8, false>>(const S&, A);
// template float layernorm2d_fwd_<t<1, 4, 64, 8, false>>(const S&, A);
// template float layernorm2d_fwd_<t<2, 4, 64, 8, false>>(const S&, A);
// template float layernorm2d_fwd_<t<4, 4, 64, 8, false>>(const S&, A);
// template float layernorm2d_fwd_<t<4, 4, 64, 8, true>>(const S&, A);
template float layernorm2d_fwd_<t<1, 4, 32, 4, false>>(const S&, A);
template float layernorm2d_fwd_<t<1, 4, 64, 4, false>>(const S&, A);
template float layernorm2d_fwd_<t<2, 4, 64, 4, false>>(const S&, A);
template float layernorm2d_fwd_<t<4, 4, 64, 4, false>>(const S&, A);
template float layernorm2d_fwd_<t<8, 4, 64, 4, false>>(const S&, A);
template float layernorm2d_fwd_<t<8, 4, 64, 4, true>>(const S&, A);
example/ck_tile/02_layernorm2d/instances/layernorm2d_fwd_bf16_n1024_instance.cpp 0 → 100644
View file @ 5cfd751b
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "layernorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd mv 2p
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 2, 4, 64, 8, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 4, 4, 64, 4, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 8, 4, 64, 2, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 16, 4, 64, 1, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 1, 1, 256, 4, true , false, false>>(const S&, A);
// clang-format on
example/ck_tile/02_layernorm2d/instances/layernorm2d_fwd_bf16_n256_instance.cpp 0 → 100644
View file @ 5cfd751b
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "layernorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd mv 2p
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 1, 4, 64, 4, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 2, 4, 64, 2, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 4, 4, 64, 1, true , false, false>>(const S&, A);
// clang-format on
example/ck_tile/02_layernorm2d/instances/layernorm2d_fwd_bf16_n512_instance.cpp 0 → 100644
View file @ 5cfd751b
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "layernorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd mv 2p
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 1, 4, 64, 8, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 2, 4, 64, 4, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 4, 4, 64, 2, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 8, 4, 64, 1, true , false, false>>(const S&, A);
// clang-format on
example/ck_tile/02_layernorm2d/instances/layernorm2d_fwd_bf16_n64_n128_instance.cpp 0 → 100644
View file @ 5cfd751b
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "layernorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd mv 2p
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 1, 4, 64, 1, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 1, 4, 64, 2, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::bf16_t, 1, 2, 4, 64, 1, true , false, false>>(const S&, A);
// clang-format on
example/ck_tile/02_layernorm2d/instances/layernorm2d_fwd_bf16_n768_instance.cpp 0 → 100644
View file @ 5cfd751b
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "layernorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd mv 2p
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 3, 4, 64, 4, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 6, 4, 64, 2, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 12, 4, 64, 1, true , false, false>>(const S&, A);
// clang-format on
example/ck_tile/02_layernorm2d/instances/layernorm2d_fwd_bf16_pad_instance.cpp deleted 100644 → 0
View file @ 68e67701
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "layernorm2d_fwd_instance_common.hpp"
template <ck_tile::index_t kNRepeat,
ck_tile::index_t kMThreadPerBlock,
ck_tile::index_t kNThreadPerBlock,
ck_tile::index_t kVectorAccessSize,
bool kTwoPass>
using t = layernorm2d_fwd_traits_<ck_tile::bf16_t,
kNRepeat,
kMThreadPerBlock,
kNThreadPerBlock,
kVectorAccessSize,
true,
false,
kTwoPass>;
// Disable all vector 8fp16 read/write instances as it has performance issue regarding compiler
// template float layernorm2d_fwd_<t<1, 16, 8, false>>(const S&, A);
// template float layernorm2d_fwd_<t<1, 32, 8, false>>(const S&, A);
// template float layernorm2d_fwd_<t<1, 64, 8, false>>(const S&, A);
// template float layernorm2d_fwd_<t<2, 64, 8, false>>(const S&, A);
// template float layernorm2d_fwd_<t<4, 64, 8, false>>(const S&, A);
// template float layernorm2d_fwd_<t<4, 64, 8, true>>(const S&, A);
template float layernorm2d_fwd_<t<1, 4, 32, 4, false>>(const S&, A);
template float layernorm2d_fwd_<t<1, 4, 64, 4, false>>(const S&, A);
template float layernorm2d_fwd_<t<2, 4, 64, 4, false>>(const S&, A);
template float layernorm2d_fwd_<t<4, 4, 64, 4, false>>(const S&, A);
template float layernorm2d_fwd_<t<8, 4, 64, 4, false>>(const S&, A);
template float layernorm2d_fwd_<t<8, 4, 64, 4, true>>(const S&, A);
template float layernorm2d_fwd_<t<1, 4, 64, 2, false>>(const S&, A);
template float layernorm2d_fwd_<t<2, 4, 64, 2, false>>(const S&, A);
template float layernorm2d_fwd_<t<4, 4, 64, 2, false>>(const S&, A);
template float layernorm2d_fwd_<t<8, 4, 64, 2, false>>(const S&, A);
template float layernorm2d_fwd_<t<16, 4, 64, 2, false>>(const S&, A);
template float layernorm2d_fwd_<t<16, 4, 64, 2, true>>(const S&, A);
template float layernorm2d_fwd_<t<32, 4, 64, 1, false>>(const S&, A);
template float layernorm2d_fwd_<t<32, 4, 64, 1, true>>(const S&, A);
example/ck_tile/02_layernorm2d/instances/layernorm2d_fwd_fp16_instance.cpp deleted 100644 → 0
View file @ 68e67701
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "layernorm2d_fwd_instance_common.hpp"
template <ck_tile::index_t kNRepeat,
ck_tile::index_t kMThreadPerBlock,
ck_tile::index_t kNThreadPerBlock,
ck_tile::index_t kVectorAccessSize,
bool kTwoPass>
using t = layernorm2d_fwd_traits_<ck_tile::fp16_t,
kNRepeat,
kMThreadPerBlock,
kNThreadPerBlock,
kVectorAccessSize,
false,
false,
kTwoPass>;
// Disable all vector 8fp16 read/write instances as it has performance issue regarding compiler
// template float layernorm2d_fwd_<t<1, 4, 16, 8, false>>(const S&, A);
// template float layernorm2d_fwd_<t<1, 4, 32, 8, false>>(const S&, A);
// template float layernorm2d_fwd_<t<1, 4, 64, 8, false>>(const S&, A);
// template float layernorm2d_fwd_<t<2, 4, 64, 8, false>>(const S&, A);
// template float layernorm2d_fwd_<t<4, 4, 64, 8, false>>(const S&, A);
// template float layernorm2d_fwd_<t<4, 4, 64, 8, true>>(const S&, A);
template float layernorm2d_fwd_<t<1, 4, 32, 4, false>>(const S&, A);
template float layernorm2d_fwd_<t<1, 4, 64, 4, false>>(const S&, A);
template float layernorm2d_fwd_<t<2, 4, 64, 4, false>>(const S&, A);
template float layernorm2d_fwd_<t<4, 4, 64, 4, false>>(const S&, A);
template float layernorm2d_fwd_<t<8, 4, 64, 4, false>>(const S&, A);
template float layernorm2d_fwd_<t<8, 4, 64, 4, true>>(const S&, A);
example/ck_tile/02_layernorm2d/instances/layernorm2d_fwd_fp16_n1024_instance.cpp 0 → 100644
View file @ 5cfd751b
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "layernorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd mv 2p
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 2, 4, 64, 8, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 4, 4, 64, 4, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 8, 4, 64, 2, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 16, 4, 64, 1, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 1, 1, 256, 4, true , false, false>>(const S&, A);
// clang-format on
example/ck_tile/02_layernorm2d/instances/layernorm2d_fwd_fp16_n256_instance.cpp 0 → 100644
View file @ 5cfd751b
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "layernorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd mv 2p
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 1, 4, 64, 4, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 2, 4, 64, 2, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 4, 4, 64, 1, true , false, false>>(const S&, A);
// clang-format on
example/ck_tile/02_layernorm2d/instances/layernorm2d_fwd_fp16_n512_instance.cpp 0 → 100644
View file @ 5cfd751b
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "layernorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd mv 2p
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 1, 4, 64, 8, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 2, 4, 64, 4, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 4, 4, 64, 2, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 8, 4, 64, 1, true , false, false>>(const S&, A);
// clang-format on
example/ck_tile/02_layernorm2d/instances/layernorm2d_fwd_fp16_n64_n128_instance.cpp 0 → 100644
View file @ 5cfd751b
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "layernorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd mv 2p
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 1, 4, 64, 1, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 1, 4, 64, 2, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 2, 4, 64, 1, true , false, false>>(const S&, A);
// clang-format on
example/ck_tile/02_layernorm2d/instances/layernorm2d_fwd_fp16_n768_instance.cpp 0 → 100644
View file @ 5cfd751b
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "layernorm2d_fwd_instance_common.hpp"
// clang-format off
// rm rn tm tn vn pd mv 2p
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 3, 4, 64, 4, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 6, 4, 64, 2, true , false, false>>(const S&, A);
template float layernorm2d_fwd_<trait_<ck_tile::fp16_t, 1, 12, 4, 64, 1, true , false, false>>(const S&, A);
// clang-format on
example/ck_tile/02_layernorm2d/instances/layernorm2d_fwd_fp16_pad_instance.cpp deleted 100644 → 0
View file @ 68e67701
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "layernorm2d_fwd_instance_common.hpp"
template <ck_tile::index_t kNRepeat,
ck_tile::index_t kMThreadPerBlock,
ck_tile::index_t kNThreadPerBlock,
ck_tile::index_t kVectorAccessSize,
bool kTwoPass>
using t = layernorm2d_fwd_traits_<ck_tile::fp16_t,
kNRepeat,
kMThreadPerBlock,
kNThreadPerBlock,
kVectorAccessSize,
true,
false,
kTwoPass>;
// Disable all vector 8fp16 read/write instances as it has performance issue regarding compiler
// template float layernorm2d_fwd_<t<1, 4, 16, 8, false>>(const S&, A);
// template float layernorm2d_fwd_<t<1, 4, 32, 8, false>>(const S&, A);
// template float layernorm2d_fwd_<t<1, 4, 64, 8, false>>(const S&, A);
// template float layernorm2d_fwd_<t<2, 4, 64, 8, false>>(const S&, A);
// template float layernorm2d_fwd_<t<4, 4, 64, 8, false>>(const S&, A);
// template float layernorm2d_fwd_<t<4, 4, 64, 8, true>>(const S&, A);
template float layernorm2d_fwd_<t<1, 4, 32, 4, false>>(const S&, A);
template float layernorm2d_fwd_<t<1, 4, 64, 4, false>>(const S&, A);
template float layernorm2d_fwd_<t<2, 4, 64, 4, false>>(const S&, A);
template float layernorm2d_fwd_<t<4, 4, 64, 4, false>>(const S&, A);
template float layernorm2d_fwd_<t<8, 4, 64, 4, false>>(const S&, A);
template float layernorm2d_fwd_<t<8, 4, 64, 4, true>>(const S&, A);
template float layernorm2d_fwd_<t<1, 4, 64, 2, false>>(const S&, A);
template float layernorm2d_fwd_<t<2, 4, 64, 2, false>>(const S&, A);
template float layernorm2d_fwd_<t<4, 4, 64, 2, false>>(const S&, A);
template float layernorm2d_fwd_<t<8, 4, 64, 2, false>>(const S&, A);
template float layernorm2d_fwd_<t<16, 4, 64, 2, false>>(const S&, A);
template float layernorm2d_fwd_<t<16, 4, 64, 2, true>>(const S&, A);
template float layernorm2d_fwd_<t<32, 4, 64, 1, false>>(const S&, A);
template float layernorm2d_fwd_<t<32, 4, 64, 1, true>>(const S&, A);
example/ck_tile/02_layernorm2d/instances/layernorm2d_fwd_instance_common.hpp
View file @ 5cfd751b
......@@ -7,36 +7,131 @@
#pragma once
#ifndef _MAX2
#define _MAX2(a, b) ((a) > (b) ? (a) : (b))
#endif
// 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 kSaveMeanInvStd_,
bool kTwoPass_>
struct layernorm2d_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::Layernorm2dShape<BlockTile, BlockWarps, WarpTile, Vector>;
static constexpr bool kPadN = kPadN_;
static constexpr bool kSaveMeanInvStd = kSaveMeanInvStd_;
static constexpr bool kTwoPass = kTwoPass_;
};
using S = ck_tile::stream_config;
using A = layernorm2d_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 kSaveMeanInvStd_,
bool kTwoPass_>
using trait_ = layernorm2d_fwd_traits_<DataType_,
Repeat_M_,
Repeat_N_,
ThreadPerBlock_M_,
ThreadPerBlock_N_,
Vector_N_,
kPadN_,
kSaveMeanInvStd_,
kTwoPass_>;
#include <iostream>
template <typename Traits_>
float layernorm2d_fwd_(const S& s, A a)
{
using DataType = typename Traits_::DataType;
using PipelineProblem =
ck_tile::BlockLayernorm2dFwdProblem<typename LayerNormTypeConfig<DataType>::XDataType,
typename LayerNormTypeConfig<DataType>::GammaDataType,
typename LayerNormTypeConfig<DataType>::BetaDataType,
typename LayerNormTypeConfig<DataType>::ComputeDataType,
typename LayerNormTypeConfig<DataType>::YDataType,
typename LayerNormTypeConfig<DataType>::MeanDataType,
typename LayerNormTypeConfig<DataType>::InvStdDataType,
typename Traits_::Shape,
Traits_::kPadN,
Traits_::kSaveMeanInvStd,
Traits_::kTwoPass>;
using Kernel = ck_tile::Layernorm2dFwd<PipelineProblem>;
const dim3 grids = Kernel::GridSize(a.M);
using PipelineProblem = ck_tile::Layernorm2dFwdWarpPerRowProblem<
typename LayerNormTypeConfig<DataType>::XDataType,
typename LayerNormTypeConfig<DataType>::GammaDataType,
typename LayerNormTypeConfig<DataType>::BetaDataType,
typename LayerNormTypeConfig<DataType>::ComputeDataType,
typename LayerNormTypeConfig<DataType>::YDataType,
typename LayerNormTypeConfig<DataType>::MeanDataType,
typename LayerNormTypeConfig<DataType>::InvStdDataType,
typename Traits_::Shape,
Traits_::kPadN,
Traits_::kSaveMeanInvStd,
Traits_::kTwoPass>;
using Pipeline = ck_tile::Layernorm2dFwdWarpPerRowPipeline<PipelineProblem>;
using Kernel = ck_tile::Layernorm2dFwd<Pipeline>;
const dim3 grids = Kernel::GridSize(a);
constexpr dim3 blocks = Kernel::BlockSize();
constexpr ck_tile::index_t kBlockPerCu = 1;
auto kargs = Kernel::MakeKargs(
a.p_x, a.p_gamma, a.p_beta, a.p_y, a.p_mean, a.p_invStd, a.epsilon, a.M, a.N);
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));
}
#undef _MAX2
example/ck_tile/02_layernorm2d/layernorm2d_fwd.cpp
View file @ 5cfd751b
......@@ -23,9 +23,12 @@ auto create_args(int argc, char* argv[])
{
ck_tile::ArgParser arg_parser;
arg_parser.insert("m", "3328", "m dimension")
.insert("n", "4096", "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_mv", "0", "save mean/variance(invstd) 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");
......@@ -34,18 +37,23 @@ auto create_args(int argc, char* argv[])
return std::make_tuple(result, arg_parser);
}
template <typename DataType>
template <typename DataType, bool SaveMeanVar>
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");
ck_tile::index_t M = arg_parser.get_int("m");
ck_tile::index_t N = arg_parser.get_int("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 = LayerNormTypeConfig<DataType>;
using XDataType = typename TypeConfig::XDataType;
......@@ -53,21 +61,23 @@ bool run(const ck_tile::ArgParser& arg_parser)
using GammaDataType = typename TypeConfig::GammaDataType;
using BetaDataType = typename TypeConfig::BetaDataType;
using MeanDataType = ck_tile::null_type;
using InvStdDataType = ck_tile::null_type;
using MeanDataType =
std::conditional_t<SaveMeanVar, typename TypeConfig::MeanDataType, ck_tile::null_type>;
using InvStdDataType =
std::conditional_t<SaveMeanVar, typename TypeConfig::InvStdDataType, ck_tile::null_type>;
using ComputeDataType = typename TypeConfig::ComputeDataType;
// host verify
ck_tile::HostTensor<XDataType> x_host({M, N});
ck_tile::HostTensor<GammaDataType> gamma_host({N});
ck_tile::HostTensor<BetaDataType> beta_host({N});
ck_tile::HostTensor<XDataType> x_host({m, n}, {stride, 1});
ck_tile::HostTensor<GammaDataType> gamma_host({n});
ck_tile::HostTensor<BetaDataType> beta_host({n});
ck_tile::HostTensor<YDataType> y_host_ref({M, N});
ck_tile::HostTensor<YDataType> y_host_dev({M, 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<MeanDataType> mean_host_ref({M});
ck_tile::HostTensor<InvStdDataType> invStd_host_ref({M});
ck_tile::HostTensor<MeanDataType> mean_host_ref({m});
ck_tile::HostTensor<InvStdDataType> invStd_host_ref({m});
ck_tile::FillUniformDistribution<XDataType>{-.5f, .5f}(x_host);
ck_tile::FillUniformDistribution<GammaDataType>{-.5f, .5f}(gamma_host);
......@@ -82,7 +92,10 @@ bool run(const ck_tile::ArgParser& arg_parser)
gamma_buf.ToDevice(gamma_host.data());
beta_buf.ToDevice(beta_host.data());
layernorm2d_fwd_traits traits{data_type};
std::cout << "[" << data_type << "]"
<< " m:" << m << ", n:" << n << ", stride:" << stride << std::flush;
layernorm2d_fwd_traits traits{data_type, SaveMeanVar};
layernorm2d_fwd_args args{x_buf.GetDeviceBuffer(),
gamma_buf.GetDeviceBuffer(),
......@@ -91,19 +104,18 @@ bool run(const ck_tile::ArgParser& arg_parser)
nullptr,
nullptr,
epsilon,
M,
N};
m,
n,
stride};
float ave_time =
layernorm2d_fwd(traits, args, ck_tile::stream_config{nullptr, true, 0, warmup, repeat});
float ave_time = layernorm2d_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(BetaDataType) * N + sizeof(YDataType) * M * N;
std::size_t num_byte = sizeof(XDataType) * m * n + sizeof(GammaDataType) * n +
sizeof(BetaDataType) * n + sizeof(YDataType) * m * n;
float gb_per_sec = num_byte / 1.E6 / ave_time;
std::cout << "[" << data_type << "]"
<< " m:" << M << ", n:" << N << ", " << ave_time * 1.E6 << " ns, " << gb_per_sec
<< " GB/s" << std::flush;
std::cout << ", " << ave_time * 1.E3 << " us, " << gb_per_sec << " GB/s" << std::flush;
bool pass = true;
......@@ -122,8 +134,27 @@ bool run(const ck_tile::ArgParser& arg_parser)
y_buf.FromDevice(y_host_dev.data());
auto [rtol, atol] = get_elimit<DataType>();
pass = ck_tile::check_err(
y_host_dev, y_host_ref, std::string("OUT Error: Incorrect results!"), rtol, atol);
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;
}
......@@ -138,13 +169,22 @@ int main(int argc, char* argv[])
return -1;
const std::string data_type = arg_parser.get_str("prec");
if(data_type == "fp16")
int save_mv = arg_parser.get_int("save_mv");
if(data_type == "fp16" && save_mv)
{
return run<ck_tile::half_t, true>(arg_parser) ? 0 : -2;
}
else if(data_type == "fp16" && !save_mv)
{
return run<ck_tile::half_t, false>(arg_parser) ? 0 : -2;
}
else if(data_type == "bf16" && save_mv)
{
return run<ck_tile::half_t>(arg_parser) ? 0 : -2;
return run<ck_tile::bf16_t, true>(arg_parser) ? 0 : -2;
}
if(data_type == "bf16")
else if(data_type == "bf16" && !save_mv)
{
return run<ck_tile::bf16_t>(arg_parser) ? 0 : -2;
return run<ck_tile::bf16_t, true>(arg_parser) ? 0 : -2;
}
return -3;
......
example/ck_tile/02_layernorm2d/layernorm2d_fwd.hpp
View file @ 5cfd751b
......@@ -36,58 +36,15 @@ struct LayerNormTypeConfig<ck_tile::bf16_t>
};
// runtime args
struct layernorm2d_fwd_args
struct layernorm2d_fwd_args : public ck_tile::Layernorm2dFwdHostArgs
{
const void* p_x;
const void* p_gamma;
const void* p_beta;
void* p_y;
void* p_mean;
void* p_invStd;
float epsilon;
ck_tile::index_t M;
ck_tile::index_t N;
};
// this is used to pattern-match internl kernel implementation, not to instantiate kernel
template <typename DataType_,
ck_tile::index_t kNRepeat,
ck_tile::index_t kMThreadPerBlock,
ck_tile::index_t kNThreadPerBlock,
ck_tile::index_t kVectorAccessSize,
bool kPadN_,
bool kSaveMeanInvStd_,
bool kTwoPass_>
struct layernorm2d_fwd_traits_
{
using DataType = ck_tile::remove_cvref_t<DataType_>;
static constexpr ck_tile::index_t MRepeat = 1;
static_assert(kNThreadPerBlock <= 64, "We only support intra-wave reduction");
static constexpr ck_tile::index_t kNWarpPerBlock = 1;
static constexpr ck_tile::index_t kMWarpPerBlock =
kMThreadPerBlock * kNThreadPerBlock / warpSize;
using thread_tile = ck_tile::sequence<MRepeat, kNRepeat, kVectorAccessSize>;
using warp_tile = ck_tile::sequence<MRepeat * warpSize / kNThreadPerBlock,
kNRepeat * kNThreadPerBlock * kVectorAccessSize>;
using block_tile = ck_tile::sequence<kMWarpPerBlock * MRepeat * warpSize / kNThreadPerBlock,
kNRepeat * kNThreadPerBlock * kVectorAccessSize>;
using Shape = ck_tile::TileLayernorm2dShape<thread_tile, warp_tile, block_tile>;
static constexpr bool kPadN = kPadN_;
static constexpr bool kSaveMeanInvStd = kSaveMeanInvStd_;
static constexpr bool kTwoPass = kTwoPass_;
};
template <typename Traits_>
float layernorm2d_fwd_(const ck_tile::stream_config& s, layernorm2d_fwd_args a);
// This is the public API, will be generated by script
struct layernorm2d_fwd_traits
{
std::string data_type;
bool save_mean_var;
};
float layernorm2d_fwd(layernorm2d_fwd_traits, layernorm2d_fwd_args, const ck_tile::stream_config&);
example/ck_tile/02_layernorm2d/perf_test.sh deleted 100755 → 0
View file @ 68e67701
./bin/tile_example_layernorm2d_fwd -m=1 -n=1 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=80 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=128 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=144 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=168 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=184 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=256 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=288 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=344 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=376 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=448 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=512 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=924 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=1024 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=1078 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=1996 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=4080 -e=1e-12 -v=1 -prec=bf16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=80 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=128 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=144 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=168 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=184 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=256 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=288 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=344 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=376 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=448 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=512 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=924 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=1024 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=1078 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=1996 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
./bin/tile_example_layernorm2d_fwd -m=700 -n=4080 -e=1e-12 -v=1 -prec=fp16 -repeat=1000
\ No newline at end of file
example/ck_tile/02_layernorm2d/script/perf_test.sh 0 → 100755
View file @ 5cfd751b
# run from top of ck folder
EXE=build/bin/tile_example_layernorm2d_fwd
$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
\ No newline at end of file
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