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Harnessing the incredible acceleration of NVIDIA GPUs is easier than ever. For over a decade NVIDIA has been collaborating in the C++ standard language committees on the adoption of features to enable parallel programming without the need for additional extensions or APIs. On account of this work, developers can now write GPU-accelerated C++ code using only standard language features: no language extensions, pragmas, directives, or non-standard libraries. Standard language parallelism is the simplest, most productive, and most portable approach to accelerated computing. It requires nothing more than ISO standard C++ and allows developers to write applications that are parallel-first such that there is never a need to port them to new platforms or to run them on GPU-accelerators. In this interactive hands-on workshop we introduce how to write GPU-accelerated applications using only C++ standard language features. By the time you complete this workshop you will be able to: Rewrite serial code to instead use C++ standard template library parallel algorithms. Use ISO C++ execution policies to indicate when algorithms may be run in parallel on platforms supporting parallelism. Use the NVIDIA HPC C++ compiler (NVC++) to compile standard C++ algorithms for execution on NVIDIA GPUs. Write C++ applications that are parallel by default so they can run without modification on GPU-accelerated (and many other) platforms. Prerequisite(s): Familiarity with the C++ programming language. Content is co-developed by Professor Jonas Latt from University of Geneva, Switzerland.
*Please disregard any reference to "Event Code" for access to training materials. "Event Codes" are only valid during the original live session.
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