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https://github.com/ROCm/composable_kernel.git
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d00e6115b9d0ca583a27ac9fba53da647ac3ea15
* GEMM + Reduce max fp16+fp32 * GEmm + Max bf16 + int8 * Refactor common definitions. * Refactor common func of mean meansquare example. * More examples for mean meansquare. * Update int8 examples and skip them cause of random errors. * Int4 examples. * Fix examples for max int4/8 * Tensor conversion for int4 input data for mean meansquare example. * Remove int4 mean_meansquare example * Fix int8 mean_meansquare example. -All ReductionAccData and R<N>DataType have to be F32. The INT32 data type is giving wrong results. * Guard int4 with ifdef * Change int8 example to add_addsquare due to div rounding err. * Clang format * Change the return type of common function. * Get back int8 example with division. * Remove int8 mean meansquare. * Use proper cast for BF16 data type. * Use ck::literals. * Use proper data type for host tensors & reference. - Use ReduceAccDataType for reference gemm output data type. - Cast host reference output tensor to EDataType - Fix ifdefs for int4. Co-authored-by: Adam Osewski <aosewski@amd.com>
Docker script
docker run \
-it \
--privileged \
--group-add sudo \
-w /root/workspace \
-v ${PATH_TO_LOCAL_WORKSPACE}:/root/workspace \
rocm/tensorflow:rocm5.1-tf2.6-dev \
/bin/bash
Install newer version of rocm-cmake
https://github.com/RadeonOpenCompute/rocm-cmake
Build
mkdir build && cd build
# Need to specify target ID, example below is gfx908 and gfx90a
cmake \
-D BUILD_DEV=OFF \
-D CMAKE_BUILD_TYPE=Release \
-D CMAKE_CXX_FLAGS=" --offload-arch=gfx908 --offload-arch=gfx90a -O3" \
-D CMAKE_CXX_COMPILER=/opt/rocm/bin/hipcc \
-D CMAKE_PREFIX_PATH=/opt/rocm \
-D CMAKE_INSTALL_PREFIX=${PATH_TO_CK_INSTALL_DIRECTORY} \
..
Build and Run Examples
make -j examples
Instructions for running each individual examples are under example/
Tests
make -j examples tests
make test
Build ckProfiler
make -j ckProfiler
Instructions for running ckProfiler are under profiler/
Install CK
make install
Using CK as pre-built kernel library
Instructions for using CK as a pre-built kernel library are under client_example/
Caveat
Kernel Timing and Verification
CK's own kernel timer will warn up kernel once, and then run it multiple times to get average kernel time. For some kernels that use atomic add, this will cause output buffer to be accumulated multiple times, causing verfication failure. To work around it, do not use CK's own timer and do verification at the same time. CK's own timer and verification in each example and ckProfiler can be enabled or disabled from command line.
Languages
C++
93.1%
Python
4.5%
CMake
1.5%
Shell
0.5%
Pawn
0.2%