# Composable Kernel ## Methodology 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". ![ALT](/doc/image/ck_component.png "CK Components") ## Code Structure 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 ![ALT](/doc/image/ck_layer.png "CK Layers") ## Contributors The list of developers and contributors is here: [Contributors](/CONTRIBUTORS.md) ## Citation 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](/CITATION.cff) ## License CK is released under the MIT license. [License File](/LICENSE) # Build CK ## Build docker image ```bash DOCKER_BUILDKIT=1 docker build -t ck:latest -f Dockerfile . ``` ## Launch docker ```bash docker run \ -it \ --privileged \ --group-add sudo \ -w /root/workspace \ -v ${PATH_TO_LOCAL_WORKSPACE}:/root/workspace \ ck:latest \ /bin/bash ``` ## Build CK ```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 \ .. ``` ### Build examples and tests ```bash make -j examples tests make test ``` Instructions for running each individual examples are under [example](/example) ## Build ckProfiler ```bash make -j ckProfiler ``` Instructions for running ckProfiler are under [profiler](/profiler) ## Install CK ```bash make install ``` ## Using CK as pre-built kernel library Instructions for using CK as a pre-built kernel library are under [client_example](/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 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.