This robust implementation provides Fortran programmers access to many capabilities of Intel® Data Center GPUs right from their native language. The Intel® Fortran Compiler supports an OpenMP* v5.0 and 5.1 offload to GPUs and is already in use in released applications.

This demo showcases the offloading capabilities of Intel Fortran Compiler using GRILLIX/PARALLAX, a plasma turbulence and transport simulator. Port a small portion of this code, originally written for the CPU, to run on an Intel® Data Center GPU Max Series (formerly code named Ponte Vecchio) using OpenMP* offloading, and then compare the performance obtained across three devices:

• Intel® Xeon® CPU Max Series (formerly code named Sapphire Rapids)
• 3^rd gen Intel® Xeon® Scalable processors
• Intel Data Center GPU Max Series

The video covers:

• The two leading advantages of Intel Fortran Compiler: Its performance and its support up to the 2018 Fortran standards—and, most importantly, its support for OpenMP, a vendor-agnostic, open-standard solution for portable and scalable shared-memory multiprocessing.
• How the compiler can offload Fortran to GPUs. This demo focuses on porting GRILLIX/PARALLAX, written in Fortran 2008 for CPUs only. Having a robust compiler and performant code is essential for this real-life, complex application. GRILLIX and PARALLAX exploit hybrid OpenMP and MPI parallelism but so far have not explored the OpenMP offloading features.
• A focus on the most expensive part of the application—the multigrid solver. This is a complex class of linear solvers composed of multiple independent components.
• Porting of the Jacobi and red-black Gauss-Seidel smoothers from CPU to GPU, including the code and pragmas, which ultimately are vendor neutral and can be used with any compiler that possesses a back end for the target architecture.
• Assessment of performance gains from this trivial code change, including a reduction to 0.6 seconds on Intel Data Center GPU Max Series versus roughly 4.3 seconds on Intel® Xeon® CPU Max Series.
• Additional code fine-tuning to explore data locality, vectorization, and pipelining for the GPU solver. In the case of GRILLIX/PARALLAX, a simple one-time reordering in the way the data is stored in the GPU memory results in a further 40% performance gain in an Intel Data Center GPU Max Series.

Speaker

Rafael Lago, software technical consulting engineer, Intel

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Download the Software

Get the latest stand-alone version of Intel Fortran Compiler or as part of the Intel® HPC Toolkit. The compiler:

• Is production-ready for CPUs and GPUs.
• Is based on the Intel Fortran Compiler Classic front-end and runtime libraries but uses LLVM* backend compiler technology.
• Implements standard language features of Fortran 2018. Supports FORTRAN 77 to Fortran 2008, all main versions of Fortran standard, and many OpenMP 4.5, 5.0, and 5.1 directives and offloading features.
• Provides Fortran programmers access to many capabilities of Intel Data Center GPU Max Series right from their native language.