GPU Acceleration with the C++ Standard Library

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.

Explore more training options offered by the NVIDIA Deep Learning Institute (DLI).