Compile for gfx908 and gfx90a (#130)

* adding compilation for multiple targets

* fix build

* clean

* update Jekinsfile

* update readme

* update Jenkins

* use ck::half_t instead of ushort for bf16

* rename enum classes

* clean

* rename

* clean

[ROCm/composable_kernel commit: cd167e492a]
This commit is contained in:
Chao Liu
2022-03-31 12:33:34 -05:00
committed by GitHub
parent 59506defde
commit 3f732cceab
227 changed files with 1398 additions and 2944 deletions

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@@ -1,44 +1,11 @@
# Instructions for ```gemm_xdl``` Example
# Instructions for ```example_gemm_xdl```
## Docker script
```bash
docker run \
-it \
--rm \
--privileged \
--group-add sudo \
-w /root/workspace \
-v ${PATH_TO_LOCAL_WORKSPACE}:/root/workspace \
rocm/tensorflow:rocm4.3.1-tf2.6-dev \
/bin/bash
```
## Build ```gemm_xdl```
```bash
mkdir build && cd build
```
```bash
# Need to specify target ID, example below is gfx908
cmake \
-D BUILD_DEV=OFF \
-D CMAKE_BUILD_TYPE=Release \
-D CMAKE_CXX_FLAGS="-DCK_AMD_GPU_GFX908 --amdgpu-target=gfx908 -O3 " \
-D CMAKE_CXX_COMPILER=/opt/rocm/bin/hipcc \
-D CMAKE_PREFIX_PATH=/opt/rocm \
..
```
```bash
make -j gemm_xdl
```
## Run ```gemm_xdl```
## Run ```example_gemm_xdl```
```bash
#arg1: verification (0=no, 1=yes)
#arg2: initialization (0=no init, 1=integer value, 2=decimal value)
#arg3: run kernel # of times (>1)
./example/gemm_xdl 0 1 5
./bin/example_gemm_xdl 0 1 5
```
Result (MI100 @ 1087Mhz, 133.5TFlops peak FP16)

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@@ -40,7 +40,7 @@ using AElementOp = ck::tensor_operation::element_wise::PassThrough;
using BElementOp = ck::tensor_operation::element_wise::PassThrough;
using CElementOp = ck::tensor_operation::element_wise::PassThrough;
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization_t::Default;
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
// clang-format off
using DeviceGemmInstance = ck::tensor_operation::device::DeviceGemm_Xdl_CShuffle

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@@ -1,44 +1,11 @@
# Instructions for ```gemm_xdl_alpha_beta``` Example
# Instructions for ```example_gemm_xdl_alpha_beta```
## Docker script
```bash
docker run \
-it \
--rm \
--privileged \
--group-add sudo \
-w /root/workspace \
-v ${PATH_TO_LOCAL_WORKSPACE}:/root/workspace \
rocm/tensorflow:rocm4.3.1-tf2.6-dev \
/bin/bash
```
## Build ```gemm_xdl_alpha_beta```
```bash
mkdir build && cd build
```
```bash
# Need to specify target ID, example below is gfx908
cmake \
-D BUILD_DEV=OFF \
-D CMAKE_BUILD_TYPE=Release \
-D CMAKE_CXX_FLAGS="-DCK_AMD_GPU_GFX908 --amdgpu-target=gfx908 -O3 " \
-D CMAKE_CXX_COMPILER=/opt/rocm/bin/hipcc \
-D CMAKE_PREFIX_PATH=/opt/rocm \
..
```
```bash
make -j gemm_xdl_alpha_beta
```
## Run ```gemm_xdl_alpha_beta```
## Run ```example_gemm_xdl_alpha_beta```
```bash
#arg1: verification (0=no, 1=yes)
#arg2: initialization (0=no init, 1=integer value, 2=decimal value)
#arg3: run kernel # of times (>1)
./example/gemm_xdl_alpha_beta 1 1 1 0.5 0.5
./bin/example_gemm_xdl_alpha_beta 1 1 1 0.5 0.5
```
Result (MI100 @ 1502Mhz, 184.6TFlops peak FP16)
```

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@@ -1,45 +1,12 @@
# Instructions for ```gemm_xdl_bias_relu_add``` Example
# Instructions for ```example_gemm_xdl_bias_relu_add```
## Docker script
```bash
docker run \
-it \
--rm \
--privileged \
--group-add sudo \
-w /root/workspace \
-v ${PATH_TO_LOCAL_WORKSPACE}:/root/workspace \
rocm/tensorflow:rocm4.3.1-tf2.6-dev \
/bin/bash
```
## Build ```gemm_xdl_bias_relu_add```
```bash
mkdir build && cd build
```
```bash
# Need to specify target ID, example below is gfx908
cmake \
-D BUILD_DEV=OFF \
-D CMAKE_BUILD_TYPE=Release \
-D CMAKE_CXX_FLAGS="-DCK_AMD_GPU_GFX908 --amdgpu-target=gfx908 -O3 " \
-D CMAKE_CXX_COMPILER=/opt/rocm/bin/hipcc \
-D CMAKE_PREFIX_PATH=/opt/rocm \
..
```
```bash
make -j gemm_xdl_bias_relu_add
```
## Run ```gemm_xdl_bias_relu_add```
## Run ```example_gemm_xdl_bias_relu_add```
```bash
#arg1: verification (0=no, 1=yes)
#arg2: initialization (0=no init, 1=integer value, 2=decimal value)
#arg3: run kernel # of times (>1)
#arg4 to 9: M (256x), N(128x), K(32x), StrideA, StrideB, StrideC
./example/gemm_xdl_bias_relu_add 0 1 5 3840 4096 4096 4096 4096 4096
./bin/example_gemm_xdl_bias_relu_add 0 1 5 3840 4096 4096 4096 4096 4096
```
Result (MI100 @ 1087Mhz, 133.5TFlops peak FP16)

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@@ -1,45 +1,12 @@
# Instructions for ```gemm_xdl_bias_relu_add``` Example
# Instructions for ```example_gemm_xdl_bias_relu_add```
## Docker script
```bash
docker run \
-it \
--rm \
--privileged \
--group-add sudo \
-w /root/workspace \
-v ${PATH_TO_LOCAL_WORKSPACE}:/root/workspace \
rocm/tensorflow:rocm4.3.1-tf2.6-dev \
/bin/bash
```
## Build ```gemm_xdl_bias_relu_add```
```bash
mkdir build && cd build
```
```bash
# Need to specify target ID, example below is gfx908
cmake \
-D BUILD_DEV=OFF \
-D CMAKE_BUILD_TYPE=Release \
-D CMAKE_CXX_FLAGS="-DCK_AMD_GPU_GFX908 --amdgpu-target=gfx908 -O3 " \
-D CMAKE_CXX_COMPILER=/opt/rocm/bin/hipcc \
-D CMAKE_PREFIX_PATH=/opt/rocm \
..
```
```bash
make -j gemm_xdl_bias_relu_add
```
## Run ```gemm_xdl_bias_relu_add```
## Run ```example_gemm_xdl_bias_relu_add```
```bash
#arg1: verification (0=no, 1=yes)
#arg2: initialization (0=no init, 1=integer value, 2=decimal value)
#arg3: run kernel # of times (>1)
#arg4 to 9: M (256x), N(128x), K(32x), StrideA, StrideB, StrideC
./example/gemm_xdl_bias_relu_add 0 1 5 3840 4096 4096 4096 4096 4096
./bin/example_gemm_xdl_bias_relu_add 0 1 5 3840 4096 4096 4096 4096 4096
```
Result (MI100 @ 1087Mhz, 133.5TFlops peak FP16)

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@@ -1,45 +1,12 @@
# Instructions for ```conv2d_fwd_xdl``` Example
# Instructions for ```example_conv2d_fwd_xdl```
## Docker script
```bash
docker run \
-it \
--rm \
--privileged \
--group-add sudo \
-w /root/workspace \
-v ${PATH_TO_LOCAL_WORKSPACE}:/root/workspace \
rocm/tensorflow:rocm4.3.1-tf2.6-dev \
/bin/bash
```
## Build ```conv2d_fwd_xdl```
```bash
mkdir build && cd build
```
```bash
# Need to specify target ID, example below is gfx908
cmake \
-D BUILD_DEV=OFF \
-D CMAKE_BUILD_TYPE=Release \
-D CMAKE_CXX_FLAGS="-DCK_AMD_GPU_GFX908 --amdgpu-target=gfx908 -O3 " \
-D CMAKE_CXX_COMPILER=/opt/rocm/bin/hipcc \
-D CMAKE_PREFIX_PATH=/opt/rocm \
..
```
```bash
make -j conv2d_fwd_xdl
```
## Run ```conv2d_fwd_xdl```
## Run ```example_conv2d_fwd_xdl```
```bash
#arg1: verification (0=no, 1=yes)
#arg2: initialization (0=no init, 1=integer value, 2=decimal value)
#arg3: run kernel # of times (>1)
#arg4 to 18: N, K, C, Y, X, Hi, Wi, Sy, Sx, Dy, Dx, LeftPy, LeftPx, RightPy, RightPx
./example/conv2d_fwd_xdl 0 1 5
./bin/example_conv2d_fwd_xdl 0 1 5
```
Result (MI100 @ 1087Mhz, 133.5TFlops peak FP16)

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@@ -34,7 +34,7 @@ using WeiElementOp = ck::tensor_operation::element_wise::PassThrough;
using OutElementOp = ck::tensor_operation::element_wise::PassThrough;
static constexpr auto ConvFwdDefault =
ck::tensor_operation::device::ConvolutionForwardSpecialization_t::Default;
ck::tensor_operation::device::ConvolutionForwardSpecialization::Default;
using DeviceConvFwdInstance = ck::tensor_operation::device::
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<

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@@ -35,7 +35,7 @@ using OutElementOp = ck::tensor_operation::element_wise::PassThrough;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
static constexpr auto ConvFwdDefault =
ck::tensor_operation::device::ConvolutionForwardSpecialization_t::Default;
ck::tensor_operation::device::ConvolutionForwardSpecialization::Default;
using DeviceConvFwdInstance = ck::tensor_operation::device::
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<

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@@ -1,45 +1,12 @@
# Instructions for ```conv_xdl_bias_relu_add``` Example
# Instructions for ```example_conv_xdl_bias_relu```
## Docker script
```bash
docker run \
-it \
--rm \
--privileged \
--group-add sudo \
-w /root/workspace \
-v ${PATH_TO_LOCAL_WORKSPACE}:/root/workspace \
rocm/tensorflow:rocm4.3.1-tf2.6-dev \
/bin/bash
```
## Build ```conv_xdl_bias_relu_add```
```bash
mkdir build && cd build
```
```bash
# Need to specify target ID, example below is gfx908
cmake \
-D BUILD_DEV=OFF \
-D CMAKE_BUILD_TYPE=Release \
-D CMAKE_CXX_FLAGS="-DCK_AMD_GPU_GFX908 --amdgpu-target=gfx908 -O3 " \
-D CMAKE_CXX_COMPILER=/opt/rocm/bin/hipcc \
-D CMAKE_PREFIX_PATH=/opt/rocm \
..
```
```bash
make -j conv_xdl_bias_relu_add
```
## Run ```conv_xdl_bias_relu_add```
## Run ```example_conv_xdl_bias_relu```
```bash
#arg1: verification (0=no, 1=yes)
#arg2: initialization (0=no init, 1=integer value, 2=decimal value)
#arg3: run kernel # of times (>1)
#arg4 to 18: N, K, C, Y, X, Hi, Wi, Sy, Sx, Dy, Dx, LeftPy, LeftPx, RightPy, RightPx
./example/conv_xdl_bias_relu_add 0 1 5
./bin/example_conv_xdl_bias_relu 0 1 5
```
Result (MI100 @ 1087Mhz, 133.5TFlops peak FP16)
@@ -48,14 +15,8 @@ in_n_c_hi_wi: dim 4, lengths {128, 192, 71, 71}, strides {967872, 1, 13632, 192}
wei_k_c_y_x: dim 4, lengths {256, 192, 3, 3}, strides {1728, 1, 576, 192}
out_n_k_ho_wo: dim 4, lengths {128, 256, 36, 36}, strides {331776, 1, 9216, 256}
bias_k: dim 1, lengths {256}, strides {1}
resi_n_k_ho_wo: dim 4, lengths {128, 256, 36, 36}, strides {331776, 1, 9216, 256}
arg.a_grid_desc_k0_m_k1_{216, 165888, 8}
arg.b_grid_desc_k0_n_k1_{216, 256, 8}
arg.c_grid_desc_m_n_{ 165888, 256}
arg.c0_grid_desc_m_n_{ 165888, 256}
arg.c1_grid_desc_m_n_{ 165888, 256}
launch_and_time_kernel: grid_dim {1296, 1, 1}, block_dim {256, 1, 1}
Warm up
Start running 5 times...
Perf: 1.71779 ms, 85.4396 TFlops, 194.2 GB/s
Perf: 1.39009 ms, 105.581 TFlops, 239.981 GB/s
```

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@@ -32,10 +32,10 @@ using InElementOp = ck::tensor_operation::element_wise::PassThrough;
using WeiElementOp = ck::tensor_operation::element_wise::PassThrough;
using OutElementOp = ck::tensor_operation::element_wise::AddRelu;
static constexpr auto MemorySet = ck::InMemoryDataOperationEnum_t::Set;
static constexpr auto MemorySet = ck::InMemoryDataOperationEnum::Set;
static constexpr auto ConvFwdDefault =
ck::tensor_operation::device::ConvolutionForwardSpecialization_t::Default;
ck::tensor_operation::device::ConvolutionForwardSpecialization::Default;
// clang-format off
using DeviceConvFwdInstance = ck::tensor_operation::device::

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@@ -1,45 +1,13 @@
# Instructions for ```conv_xdl_bias_relu_add``` Example
# Instructions for ```example_conv_xdl_bias_relu_add```
## Docker script
```bash
docker run \
-it \
--rm \
--privileged \
--group-add sudo \
-w /root/workspace \
-v ${PATH_TO_LOCAL_WORKSPACE}:/root/workspace \
rocm/tensorflow:rocm4.3.1-tf2.6-dev \
/bin/bash
```
## Build ```conv_xdl_bias_relu_add```
```bash
mkdir build && cd build
```
```bash
# Need to specify target ID, example below is gfx908
cmake \
-D BUILD_DEV=OFF \
-D CMAKE_BUILD_TYPE=Release \
-D CMAKE_CXX_FLAGS="-DCK_AMD_GPU_GFX908 --amdgpu-target=gfx908 -O3 " \
-D CMAKE_CXX_COMPILER=/opt/rocm/bin/hipcc \
-D CMAKE_PREFIX_PATH=/opt/rocm \
..
```
```bash
make -j conv_xdl_bias_relu_add
```
## Run ```conv_xdl_bias_relu_add```
## Run ```example_conv_xdl_bias_relu_add```
```bash
#arg1: verification (0=no, 1=yes)
#arg2: initialization (0=no init, 1=integer value, 2=decimal value)
#arg3: run kernel # of times (>1)
#arg4 to 18: N, K, C, Y, X, Hi, Wi, Sy, Sx, Dy, Dx, LeftPy, LeftPx, RightPy, RightPx
./example/conv_xdl_bias_relu_add 0 1 5
./bin/example_conv_xdl_bias_relu_add 0 1 5
```
Result (MI100 @ 1087Mhz, 133.5TFlops peak FP16)
@@ -49,13 +17,8 @@ wei_k_c_y_x: dim 4, lengths {256, 192, 3, 3}, strides {1728, 1, 576, 192}
out_n_k_ho_wo: dim 4, lengths {128, 256, 36, 36}, strides {331776, 1, 9216, 256}
bias_k: dim 1, lengths {256}, strides {1}
resi_n_k_ho_wo: dim 4, lengths {128, 256, 36, 36}, strides {331776, 1, 9216, 256}
arg.a_grid_desc_k0_m_k1_{216, 165888, 8}
arg.b_grid_desc_k0_n_k1_{216, 256, 8}
arg.c_grid_desc_m_n_{ 165888, 256}
arg.c0_grid_desc_m_n_{ 165888, 256}
arg.c1_grid_desc_m_n_{ 165888, 256}
launch_and_time_kernel: grid_dim {1296, 1, 1}, block_dim {256, 1, 1}
Warm up
Start running 5 times...
Perf: 1.71779 ms, 85.4396 TFlops, 194.2 GB/s
Perf: 1.44711 ms, 101.421 TFlops, 289.218 GB/s
```

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@@ -33,7 +33,7 @@ using WeiElementOp = ck::tensor_operation::element_wise::PassThrough;
using OutElementOp = ck::tensor_operation::element_wise::AddReluAdd;
static constexpr auto ConvFwdDefault =
ck::tensor_operation::device::ConvolutionForwardSpecialization_t::Default;
ck::tensor_operation::device::ConvolutionForwardSpecialization::Default;
// clang-format off
using DeviceConvFwdInstance = ck::tensor_operation::device::

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@@ -1,57 +1,24 @@
# Instructions for ```conv3d_fwd_xdl``` Example
# Instructions for ```example_conv3d_fwd_xdl```
## Docker script
```bash
docker run \
-it \
--rm \
--privileged \
--group-add sudo \
-w /root/workspace \
-v ${PATH_TO_LOCAL_WORKSPACE}:/root/workspace \
rocm/tensorflow:rocm4.3.1-tf2.6-dev \
/bin/bash
```
## Build ```conv3d_fwd_xdl```
```bash
mkdir build && cd build
```
```bash
# Need to specify target ID, example below is gfx908
cmake \
-D BUILD_DEV=OFF \
-D CMAKE_BUILD_TYPE=Release \
-D CMAKE_CXX_FLAGS="-DCK_AMD_GPU_GFX908 --amdgpu-target=gfx908 -O3 " \
-D CMAKE_CXX_COMPILER=/opt/rocm/bin/hipcc \
-D CMAKE_PREFIX_PATH=/opt/rocm \
..
```
```bash
make -j conv3d_fwd_xdl
```
## Run ```conv3d_fwd_xdl```
## Run ```example_conv3d_fwd_xdl```
```bash
#arg1: verification (0=no, 1=yes)
#arg2: initialization (0=no init, 1=integer value, 2=decimal value)
#arg3: run kernel # of times (>1)
#arg4 to 24: N, K, C, Z, Y, X, Di, Hi, Wi, Sz, Sy, Sx, Dz, Dy, Dx, leftPz, LeftPy, LeftPx, RightPz, RightPy, RightPx
./example/conv3d_fwd_xdl 0 1 5
./bin/example_conv3d_fwd_xdl 0 1 5
```
Result (MI100 dynamic frequency)
Result (MI100 @ 1087Mhz, 133.5TFlops peak FP16)
```
in: dim 5, lengths {4, 71, 71, 71, 192}, strides {68718912, 967872, 13632, 192, 1}
wei: dim 5, lengths {256, 3, 3, 3, 192}, strides {5184, 1728, 576, 192, 1}
out: dim 5, lengths {4, 36, 36, 36, 256}, strides {11943936, 331776, 9216, 256, 1}
a_grid_desc_b_k0_m_k1{1, 648, 186624, 8}
b_grid_desc_b_k0_n_k1{1, 648, 256, 8}
num_batches_of_GEMM = 1
a_grid_desc_k0_m_k1{648, 186624, 8}
b_grid_desc_k0_n_k1{648, 256, 8}
c_grid_desc_m_n{ 186624, 256}
launch_and_time_kernel: grid_dim {1458, 1, 1}, block_dim {256, 1, 1}
Warm up
Start running 5 times...
Perf: 4.49466 ms, 110.206 TFlops, 144.161 GB/s
Perf: 4.58795 ms, 107.965 TFlops, 141.23 GB/s
```

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@@ -37,7 +37,7 @@ using WeiLayout = ck::tensor_layout::convolution::KZYXC;
using OutLayout = ck::tensor_layout::convolution::NDHWK;
static constexpr auto ConvFwdDefault =
ck::tensor_operation::device::ConvolutionForwardSpecialization_t::Default;
ck::tensor_operation::device::ConvolutionForwardSpecialization::Default;
using DeviceConv3dFwdInstance = ck::tensor_operation::device::
DeviceConv3dFwdXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho_Wo_K<

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@@ -1,39 +1,6 @@
# Instructions for ```convnd_fwd_xdl``` Example
# Instructions for ```example_convnd_fwd_xdl```
## Docker script
```bash
docker run \
-it \
--rm \
--privileged \
--group-add sudo \
-w /root/workspace \
-v ${PATH_TO_LOCAL_WORKSPACE}:/root/workspace \
rocm/tensorflow:rocm4.3.1-tf2.6-dev \
/bin/bash
```
## Build ```convnd_fwd_xdl```
```bash
mkdir build && cd build
```
```bash
# Need to specify target ID, example below is gfx908
cmake \
-D BUILD_DEV=OFF \
-D CMAKE_BUILD_TYPE=Release \
-D CMAKE_CXX_FLAGS="-DCK_AMD_GPU_GFX908 --amdgpu-target=gfx908 -O3 " \
-D CMAKE_CXX_COMPILER=/opt/rocm/bin/hipcc \
-D CMAKE_PREFIX_PATH=/opt/rocm \
..
```
```bash
make -j convnd_fwd_xdl
```
## Run ```convnd_fwd_xdl```
## Run ```example_convnd_fwd_xdl```
```bash
#arg1: verification (0=no, 1=yes)
#arg2: initialization (0=no init, 1=integer value, 2=decimal value)
@@ -47,7 +14,7 @@ cmake \
# <dilations>, (ie Dy, Dx for 2D)
# <left padding>, (ie LeftPy, LeftPx for 2D)
# <right padding>, (ie RightPy, RightPx for 2D)
./example/convnd_fwd_xdl 0 1 100
./bin/example_convnd_fwd_xdl 0 1 100
```
Result (MI100 @ 1087Mhz, 33.4TFlops peak FP32)

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@@ -26,7 +26,7 @@ using WeiElementOp = ck::tensor_operation::element_wise::PassThrough;
using OutElementOp = ck::tensor_operation::element_wise::PassThrough;
static constexpr auto ConvFwdDefault =
ck::tensor_operation::device::ConvolutionForwardSpecialization_t::Default;
ck::tensor_operation::device::ConvolutionForwardSpecialization::Default;
using DeviceConvFwdBasePtr =
ck::tensor_operation::device::DeviceConvFwdPtr<InElementOp, WeiElementOp, OutElementOp>;

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@@ -1,45 +1,13 @@
# Instructions for ```conv2d_bwd_data_xdl``` Example
# Instructions for ```example_conv2d_bwd_data_xdl``` Example
## Docker script
```bash
docker run \
-it \
--rm \
--privileged \
--group-add sudo \
-w /root/workspace \
-v ${PATH_TO_LOCAL_WORKSPACE}:/root/workspace \
rocm/tensorflow:rocm4.3.1-tf2.6-dev \
/bin/bash
```
## Build ```conv2d_bwd_data_xdl```
```bash
mkdir build && cd build
```
```bash
# Need to specify target ID, example below is gfx908
cmake \
-D BUILD_DEV=OFF \
-D CMAKE_BUILD_TYPE=Release \
-D CMAKE_CXX_FLAGS="-DCK_AMD_GPU_GFX908 --amdgpu-target=gfx908 -O3 " \
-D CMAKE_CXX_COMPILER=/opt/rocm/bin/hipcc \
-D CMAKE_PREFIX_PATH=/opt/rocm \
..
```
```bash
make -j conv2d_bwd_data_xdl
```
## Run ```conv2d_bwd_data_xdl```
## Run ```example_conv2d_bwd_data_xdl```
```bash
#arg1: verification (0=no, 1=yes)
#arg2: initialization (0=no init, 1=integer value, 2=decimal value)
#arg3: run kernel # of times (>1)
#arg4 to 18: N, K, C, Y, X, Hi, Wi, Sy, Sx, Dy, Dx, LeftPy, LeftPx, RightPy, RightPx
./bin/conv2d_bwd_data_xdl 0 1 5
./bin/example_conv2d_bwd_data_xdl 0 1 5
```
Result

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@@ -27,7 +27,7 @@ using InElementOp = ck::tensor_operation::element_wise::PassThrough;
using WeiElementOp = ck::tensor_operation::element_wise::PassThrough;
using OutElementOp = ck::tensor_operation::element_wise::PassThrough;
static constexpr auto ConvBwdDefault =
ck::tensor_operation::device::ConvolutionBackwardDataSpecialization_t::Default;
ck::tensor_operation::device::ConvolutionBackwardDataSpecialization::Default;
using DeviceConvBwdDataInstance = ck::tensor_operation::device::
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<
@@ -38,7 +38,7 @@ using DeviceConvBwdDataInstance = ck::tensor_operation::device::
InElementOp, // InElementwiseOperation
WeiElementOp, // WeiElementwiseOperation
OutElementOp, // OutElementwiseOperation
ConvBwdDefault, // ConvolutionBackwardDataSpecialization_t
ConvBwdDefault, // ConvolutionBackwardDataSpecialization
256, // BlockSize
128, // MPerBlock
128, // NPerBlock

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@@ -1,39 +1,6 @@
# Instructions for ```conv2d_wrw_xdl``` Example
# Instructions for ```example_conv2d_wrw_xdl``` Example
## Docker script
```bash
docker run \
-it \
--rm \
--privileged \
--group-add sudo \
-w /root/workspace \
-v ${PATH_TO_LOCAL_WORKSPACE}:/root/workspace \
rocm/tensorflow:rocm4.3.1-tf2.6-dev \
/bin/bash
```
## Build ```conv2d_wrw_xdl```
```bash
mkdir build && cd build
```
```bash
# Need to specify target ID, example below is gfx908
cmake \
-D BUILD_DEV=OFF \
-D CMAKE_BUILD_TYPE=Release \
-D CMAKE_CXX_FLAGS="-DCK_AMD_GPU_GFX908 --amdgpu-target=gfx908 -O3 " \
-D CMAKE_CXX_COMPILER=/opt/rocm/bin/hipcc \
-D CMAKE_PREFIX_PATH=/opt/rocm \
..
```
```bash
make -j conv2d_wrw_xdl
```
## Run ```conv2d_wrw_xdl```
## Run ```example_conv2d_wrw_xdl```
```bash
#arg1: verification (0=no, 1=yes)
#arg2: initialization (0=no init, 1=integer value, 2=decimal value)

View File

@@ -1,45 +1,12 @@
# Instructions for ```reduce_blockwise``` Example
# Instructions for ```example_reduce_blockwise```
## Docker script
```bash
docker run \
-it \
--rm \
--privileged \
--group-add sudo \
-w /root/workspace \
-v ${PATH_TO_LOCAL_WORKSPACE}:/root/workspace \
rocm/tensorflow:rocm4.3.1-tf2.6-dev \
/bin/bash
```
## Build ```reduce_blockwise```
```bash
mkdir build && cd build
```
```bash
# Need to specify target ID, example below is gfx908
cmake \
-D BUILD_DEV=OFF \
-D CMAKE_BUILD_TYPE=Release \
-D CMAKE_CXX_FLAGS="-DCK_AMD_GPU_GFX908 --amdgpu-target=gfx908 -O3 " \
-D CMAKE_CXX_COMPILER=/opt/rocm/bin/hipcc \
-D CMAKE_PREFIX_PATH=/opt/rocm \
..
```
```bash
make -j reduce_blockwise
```
## Run ```reduce_blockwise```
## Run ```example_reduce_blockwise```
```bash
# -D <xxx> : input 4-d tensor lengths
# -v <x> : verification (0=no, 1=yes)
#arg1: initialization (0=no init, 1=single integer value, 2=scope integer value, 3=decimal value)
#arg2: run kernel # of times (>1)
./bin/reduce_blockwise -D 16,64,32,960 -v 1 1 10
./bin/example_reduce_blockwise -D 16,64,32,960 -v 1 1 10
```
Result
@@ -50,7 +17,7 @@ Start running 3 times...
Perf: 0.23536 ms, 267.32 GB/s, DeviceReduceBlockWise<256,M_C4_S1,K_C64_S1,InSrcVectorDim_0_InSrcVectorSize_1_OutDstVectorSize_1>
error: 0
max_diff: 0, 529, 529
root@dc-smc-18:/data/composable_kernel/Build3# bin/reduce_blockwise -D 16,64,32,960 -v 1 1 10
root@dc-smc-18:/data/composable_kernel/Build3# bin/example_reduce_blockwise -D 16,64,32,960 -v 1 1 10
launch_and_time_kernel: grid_dim {240, 1, 1}, block_dim {256, 1, 1}
Warm up
Start running 10 times...

View File

@@ -32,10 +32,10 @@ using HostAccDataType = float;
constexpr int Rank = 4;
constexpr int NumReduceDim = 3;
constexpr ReduceTensorOp_t ReduceOpId = ReduceTensorOp_t::NORM2;
constexpr NanPropagation_t NanOpt = NanPropagation_t::PROPAGATE_NAN;
constexpr bool PropagateNan = (NanOpt == NanPropagation_t::NOT_PROPAGATE_NAN) ? false : true;
constexpr ReduceTensorIndices_t IndicesOpt = ReduceTensorIndices_t::NO_INDICES;
constexpr ReduceTensorOp ReduceOpId = ReduceTensorOp::NORM2;
constexpr NanPropagation NanOpt = NanPropagation::PROPAGATE_NAN;
constexpr bool PropagateNan = (NanOpt == NanPropagation::NOT_PROPAGATE_NAN) ? false : true;
constexpr ReduceTensorIndices IndicesOpt = ReduceTensorIndices::NO_INDICES;
using ReduceOperation = typename reduce_binary_operator<AccDataType, ReduceOpId>::opType;
using InElementwiseOperation =
@@ -210,11 +210,11 @@ int main(int argc, char* argv[])
return (-1);
constexpr bool op_support_indices =
(ReduceOpId == ReduceTensorOp_t::MIN || ReduceOpId == ReduceTensorOp_t::MAX ||
ReduceOpId == ReduceTensorOp_t::AMAX);
(ReduceOpId == ReduceTensorOp::MIN || ReduceOpId == ReduceTensorOp::MAX ||
ReduceOpId == ReduceTensorOp::AMAX);
constexpr bool NeedIndices =
(op_support_indices && (IndicesOpt != ReduceTensorIndices_t::NO_INDICES));
(op_support_indices && (IndicesOpt != ReduceTensorIndices::NO_INDICES));
// if input is half type, no reason to use float for indiced reduction operation and must use
// float for non-indiced reduction operation for accuracy
@@ -230,7 +230,7 @@ int main(int argc, char* argv[])
// indices option can only be used when it is really needed
constexpr bool invalid_reduce_3 =
(!op_support_indices && IndicesOpt != ReduceTensorIndices_t::NO_INDICES);
(!op_support_indices && IndicesOpt != ReduceTensorIndices::NO_INDICES);
constexpr bool invalid_reduce = (invalid_reduce_1 || invalid_reduce_2 || invalid_reduce_3);

View File

@@ -1,45 +1,12 @@
# Instructions for ```pool2d_fwd``` Example
# Instructions for ```example_pool2d_fwd``` Example
## Docker script
```bash
docker run \
-it \
--rm \
--privileged \
--group-add sudo \
-w /root/workspace \
-v ${PATH_TO_LOCAL_WORKSPACE}:/root/workspace \
rocm/tensorflow:rocm4.3.1-tf2.6-dev \
/bin/bash
```
## Build ```pool2d_fwd```
```bash
mkdir build && cd build
```
```bash
# Need to specify target ID, example below is gfx908
cmake \
-D BUILD_DEV=OFF \
-D CMAKE_BUILD_TYPE=Release \
-D CMAKE_CXX_FLAGS="-DCK_AMD_GPU_GFX908 --amdgpu-target=gfx908 -O3 " \
-D CMAKE_CXX_COMPILER=/opt/rocm/bin/hipcc \
-D CMAKE_PREFIX_PATH=/opt/rocm \
..
```
```bash
make -j pool2d_fwd
```
## Run ```pool2d_fwd```
## Run ```example_pool2d_fwd```
```bash
#arg1: verification (0=no, 1=yes)
#arg2: initialization (0=no init, 1=single integer value, 2=scope integer value, 3=decimal value)
#arg3: run kernel # of times (>1)
#arg4 to 15: N, C, Y, X, Hi, Wi, Sy, Sx, LeftPy, LeftPx, RightPy, RightPx
./example/pool2d_fwd 1 1 10
./bin/example_pool2d_fwd 1 1 10
```
Result

View File

@@ -22,9 +22,9 @@ using InLayout = ck::tensor_layout::convolution::NHWC;
using OutLayout = ck::tensor_layout::convolution::NHWC;
#if 1
static constexpr auto ReduceOpId = ck::ReduceTensorOp_t::MAX;
static constexpr auto ReduceOpId = ck::ReduceTensorOp::MAX;
#else
static constexpr auto ReduceOpId = ck::ReduceTensorOp_t::AVG;
static constexpr auto ReduceOpId = ck::ReduceTensorOp::AVG;
#endif
static constexpr bool NeedIndices = false;
@@ -47,7 +47,7 @@ using DevicePoolFwdInstance =
template <typename InDataType,
typename OutDataType,
typename AccDataType,
ck::ReduceTensorOp_t ReduceOpId,
ck::ReduceTensorOp ReduceOpId,
bool PropagateNan,
bool NeedIndices>
static void pool_host_verify(const Tensor<InDataType>& in,

View File

@@ -1,39 +1,6 @@
# Instructions for ```grouped_gemm_xdl``` Example
# Instructions for ```example_grouped_gemm_xdl```
## Docker script
```bash
docker run \
-it \
--rm \
--privileged \
--group-add sudo \
-w /root/workspace \
-v ${PATH_TO_LOCAL_WORKSPACE}:/root/workspace \
rocm/tensorflow:rocm4.3.1-tf2.6-dev \
/bin/bash
```
## Build ```grouped_gemm_xdl```
```bash
mkdir build && cd build
```
```bash
# Need to specify target ID, example below is gfx908
cmake \
-D BUILD_DEV=OFF \
-D CMAKE_BUILD_TYPE=Release \
-D CMAKE_CXX_FLAGS="-DCK_AMD_GPU_GFX908 --amdgpu-target=gfx908 -O3 " \
-D CMAKE_CXX_COMPILER=/opt/rocm/bin/hipcc \
-D CMAKE_PREFIX_PATH=/opt/rocm \
..
```
```bash
make -j example_grouped_gemm_xdl_fp16
```
## Run ```grouped_gemm_xdl```
## Run ```example_grouped_gemm_xdl```
```bash
#arg1: verification (0=no, 1=yes)
#arg2: initialization (0=no init, 1=integer value, 2=decimal value)

View File

@@ -40,9 +40,9 @@ using AElementOp = ck::tensor_operation::element_wise::PassThrough;
using BElementOp = ck::tensor_operation::element_wise::PassThrough;
using CElementOp = ck::tensor_operation::element_wise::PassThrough;
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization_t::Default;
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
// static constexpr auto GemmMNPadding =
// ck::tensor_operation::device::GemmSpecialization_t::MNPadding;
// ck::tensor_operation::device::GemmSpecialization::MNPadding;
// clang-format off
using DeviceGemmInstance = ck::tensor_operation::device::DeviceGroupedGemmXdl

View File

@@ -40,7 +40,7 @@ using D0ReduceOp = ck::tensor_operation::element_wise::ReduceSum;
using D1ReduceOp = ck::tensor_operation::element_wise::ReduceSquareSum;
static constexpr auto GemmSpecialization =
ck::tensor_operation::device::GemmSpecialization_t::Default;
ck::tensor_operation::device::GemmSpecialization::Default;
// clang-format off
using DeviceGemmReduceInstance = ck::tensor_operation::device::DeviceGemmReduce_Xdl_CShuffle

View File

@@ -1,46 +1,13 @@
# Instructions for ```convnd_bwd_data_xdl``` Example
# Instructions for ```example_convnd_bwd_data_xdl```
## Docker script
```bash
docker run \
-it \
--rm \
--privileged \
--group-add sudo \
-w /root/workspace \
-v ${PATH_TO_LOCAL_WORKSPACE}:/root/workspace \
rocm/tensorflow:rocm4.3.1-tf2.6-dev \
/bin/bash
```
## Build ```convnd_bwd_data_xdl```
```bash
mkdir build && cd build
```
```bash
# Need to specify target ID, example below is gfx908
cmake \
-D BUILD_DEV=OFF \
-D CMAKE_BUILD_TYPE=Release \
-D CMAKE_CXX_FLAGS="-DCK_AMD_GPU_GFX908 --amdgpu-target=gfx908 -O3 " \
-D CMAKE_CXX_COMPILER=/opt/rocm/bin/hipcc \
-D CMAKE_PREFIX_PATH=/opt/rocm \
..
```
```bash
make -j convnd_bwd_data_xdl
```
## Run ```example_convnd_bwd_data_xdl```
## Run ```example_example_convnd_bwd_data_xdl```
```bash
#arg1: verification (0=no, 1=yes)
#arg2: initialization (0=no init, 1=integer value, 2=decimal value)
#arg3: run kernel # of times (>1)
#arg4: num_dim_spatial(1|2|3)
#arg5 to ...: N, K, C, [Z,] [Y,] X, [Di,] [Hi,] Wi, S[z,] [Sy,] Sx, [Dz,] [Dy,] Dx, [LeftPz,] [LeftPy,] LeftPx, [RightPy,] [RightPy,] RightPx
./bin/convnd_bwd_data_xdl 0 1 5
./bin/example_convnd_bwd_data_xdl 0 1 5
```
Result

View File

@@ -29,7 +29,7 @@ using InElementOp = ck::tensor_operation::element_wise::PassThrough;
using WeiElementOp = ck::tensor_operation::element_wise::PassThrough;
using OutElementOp = ck::tensor_operation::element_wise::PassThrough;
static constexpr auto ConvBwdDefault =
ck::tensor_operation::device::ConvolutionBackwardDataSpecialization_t::Default;
ck::tensor_operation::device::ConvolutionBackwardDataSpecialization::Default;
using DeviceConvBwdDataBasePtr =
ck::tensor_operation::device::DeviceConvBwdDataPtr<InElementOp, WeiElementOp, OutElementOp>;
@@ -44,7 +44,7 @@ using DeviceConvNDBwdDataInstance = ck::tensor_operation::device::
InElementOp, // InElementwiseOperation
WeiElementOp, // WeiElementwiseOperation
OutElementOp, // OutElementwiseOperation
ConvBwdDefault, // ConvolutionBackwardDataSpecialization_t
ConvBwdDefault, // ConvolutionBackwardDataSpecialization
NumDimSpatial, // NumDimSpatial
256, // BlockSize
128, // MPerBlock

View File

@@ -40,7 +40,7 @@ using D0ReduceOp = ck::tensor_operation::element_wise::ReduceSum;
using D1ReduceOp = ck::tensor_operation::element_wise::ReduceSquareSum;
static constexpr auto GemmSpecialization =
ck::tensor_operation::device::GemmSpecialization_t::Default;
ck::tensor_operation::device::GemmSpecialization::Default;
// clang-format off
using DeviceBatchedGemmReduceInstance = ck::tensor_operation::device::DeviceBatchedGemmReduce_Xdl_CShuffle