Programming Your GPU with OpenMP Performance Portability for GPUs

<b>The essential guide for writing portable, parallel programs for GPUs using the OpenMP programming model.</b><br><br>Today’s computers are complex, multi-architecture systems: multiple cores in a shared address space, graphics processing units (GPUs), and specialized accelerators. To get the most from these systems, programs must use all these different processors. In <i>Programming Your GPU with OpenMP</i>, Tom Deakin and Timothy Mattson help everyone, from beginners to advanced programmers, learn how to use OpenMP to program a GPU using just a few directives and runtime functions. Then programmers can go further to maximize performance by using CPUs and GPUs in parallel—true heterogeneous programming. And since OpenMP is a portable API, the programs will run on almost any system.<br><br><i>Programming Your GPU with OpenMP </i>shares best practices for writing performance portable programs. Key features include:<br><br><ul><li>The most up-to-date APIs for programming GPUs with OpenMP with concepts that transfer to other approaches for GPU programming.</li><li>Written in a tutorial style that embraces active learning, so that readers can make immediate use of what they learn via provided source code.</li><li>Builds the OpenMP GPU Common Core to get programmers to serious production-level GPU programming as fast as possible.</li></ul><br>Additional features:<br><br><ul><li>A reference guide at the end of the book covering all relevant parts of OpenMP 5.2.</li><li>An online repository containing source code for the example programs from the book—provided in all languages currently supported by OpenMP: C, C++, and Fortran.</li><li>Tutorial videos and lecture slides.</li></ul>