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cp2k/docs/technologies/accelerators/opencl.md

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OpenCL

OpenCL devices are currently supported for DBCSR and DBM/DBT, and can cover GPUs and other devices. Kernels can be automatically tuned.

Note: the OpenCL backend uses some functionality from LIBXSMM (dependency). CP2K's offload-library serving DBM/DBT and other libraries depends on DBCSR's OpenCL backend.

Installing OpenCL and preparing the runtime environment

  • Installing an OpenCL runtime depends on the operating system and the device vendor. Debian for instance brings two packages called opencl-headers and ocl-icd-opencl-dev which can be present in addition to a vendor-specific installation. The OpenCL header files are only necessary if CP2K/DBCSR is compiled from source. Please note, some implementations ship with outdated OpenCL headers which can prevent using latest features (if an application discovers such features only at compile-time). When building from source, for instance libOpenCL.so is sufficient at link-time (ICD loader). However, an Installable Client Driver (ICD) is finally necessary at runtime.
  • NVIDIA CUDA, AMD HIP, and Intel OneAPI are fully equipped with an OpenCL runtime (if opencl-headers package is not installed, CPATH can be needed to point into the former installation, similarly LIBRARY_PATH for finding libOpenCL.so at link-time). Installing a minimal or stand-alone OpenCL is also possible, e.g., following the instructions for Debian (or Ubuntu) as given for every release of the Intel Compute Runtime.
  • The environment variable ACC_OPENCL_VERBOSE prints information at runtime of CP2K about kernels generated (ACC_OPENCL_VERBOSE=2) or executed (ACC_OPENCL_VERBOSE=3) which can be used to check an installation.

Building CP2K with OpenCL-based DBCSR

  • CP2K's toolchain supports --enable-opencl to select DBCSR's OpenCL backend. This can be combined with --enable-cuda (--gpu-ver is then imposed) to use a GPU for CP2K's GRID and PW components (no OpenCL support yet) with DBM's CUDA implementation to be preferred.
  • For manually writing an ARCH-file, add -D__OPENCL and -D__DBCSR_ACC to CFLAGS and add -lOpenCL to the LIBS variable, i.e., OFFLOAD_CC and OFFLOAD_FLAGS can duplicate CC and CFLAGS (no special offload compiler needed). Please also set OFFLOAD_TARGET = opencl to enable the OpenCL backend in DBCSR. For OpenCL, it is not necessary to specify a GPU version (e.g., GPUVER = V100 would map/limit to exts/dbcsr/src/acc/opencl/smm/params/tune_multiply_V100.csv). In fact, GPUVER limits tuned parameters to the specified GPU, whereas by default all tuned parameters are embedded (exts/dbcsr/src/acc/opencl/smm/params/*.csv) and applied at runtime. If auto-tuned parameters are not available for DBCSR, well-chosen defaults will be used to populate kernels at runtime.
  • Auto-tuned parameters are embedded into the binary, i.e., CP2K does not rely on a hard-coded location. Setting OPENCL_LIBSMM_SMM_PARAMS=/path/to/csv-file environment variable can supply parameters for an already built application, or OPENCL_LIBSMM_SMM_PARAMS=0 can disable using tuned parameters. Refer to https://cp2k.github.io/dbcsr/ on how to tune kernels (parameters).

Building CP2K with OpenCL-based DBM library

  • Pass -DCP2K_USE_ACCEL=OPENCL to CMake in addition to following above instructions for "Building CP2K with OpenCL-based DBCSR". An additional Makefile rule can be necessary to transform OpenCL code into a ressource header file.