Composable Kernel (CK) library aims to provide a programming model for writing performance critical kernels for machine learning workloads across multiple architectures including GPUs, CPUs, etc, through general purpose kernel languages, like HIP C++.

CK utilizes two concepts to achieve performance portability and code maintainability:

• A tile-based programming model
• Algorithm complexity reduction for complex ML operators, using innovative technique we call "Tensor Coordinate Transformation".

Current CK library are structured into 4 layers:

• "Templated Tile Operators" layer
• "Templated Kernel and Invoker" layer
• "Instantiated Kernel and Invoker" layer
• "Client API" layer

The list of developers and contributors is here: Contributors

If you use CK, please use following citations:

• CK paper will be freely available on arXiv soon: Realizing Tensor Operators Using Coordinate Transformations and Tile Based Programming
• CITATION.cff

CK is released under the MIT license. License File

DOCKER_BUILDKIT=1 docker build -t ck:latest -f Dockerfile .

docker run                                     \
-it                                            \
--privileged                                   \
--group-add sudo                               \
-w /root/workspace                             \
-v ${PATH_TO_LOCAL_WORKSPACE}:/root/workspace  \
ck:latest                                      \
/bin/bash

mkdir build && cd build

# Need to specify target ID, example below is for gfx908 and gfx90a
cmake                                                                                             \
-D CMAKE_PREFIX_PATH=/opt/rocm                                                                    \
-D CMAKE_CXX_COMPILER=/opt/rocm/bin/hipcc                                                         \
-D CMAKE_CXX_FLAGS="-O3"                                                                          \
-D CMAKE_BUILD_TYPE=Release                                                                       \
-D GPU_TARGETS="gfx908;gfx90a"                                                                    \
..

 make -j examples tests
 make test

Instructions for running each individual examples are under example

 make -j ckProfiler

Instructions for running ckProfiler are under profiler

make install

Instructions for using CK as a pre-built kernel library are under client_example

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 verification 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.