Event

<p>GPU vendors provide highly optimized libraries for math operations such as fast Fourier transformation or linear algebra (FFT, (sparse)BLAS/LAPACK, …) to perform those on devices. And OpenMP is a popular, vendor-agnostic method for parallelization on the CPU but increasingly also for offloading calculations to the GPU.</p> <p>This talk shows how OpenMP can be used to reduce to reduce vendor-specific code, make calling it more convenient, and to combine OpenMP offloading with those libraries. While the presentation illustrates the use with the GNU Compiler Collection (GCC), the feature is a generic feature of OpenMP 5.2, extended in 6.0, and is supported by multiple compilers.</p> <p><em>In terms of OpenMP features, the 'interop' directive provides the interoperability support, the 'declare variant' directive with the 'adjust_args' and 'append_args' clauses enable to write neater code; means for memory allocation and memory transfer and running code blocks on the GPU ('target' construct) complete the required feature set.</em></p> <ul> <li>The <strong>OpenMP specification,</strong> current, past and future version, errata and example documents can be found at https://www.openmp.org/specifications/; a list of compilers and tools for OpenMP is at https://www.openmp.org/resources/openmp-compilers-tools/</li> <li><strong>GCC's OpenMP documentation</strong> is available at https://gcc.gnu.org/onlinedocs/libgomp/ (API routines, implementation status, …) and, in particular, the supported interop foreign runtimes are documented at https://gcc.gnu.org/onlinedocs/libgomp/Offload-Target-Specifics.html; GCC supports offloading to Nvidia and AMD GPUs. GCC supports OpenMP interop since GCC 15, including most of the OpenMP 6.0 additions, including the Fortran API routines.</li> </ul>