The essential guide for writing portable, parallel programs for GPUs
using the OpenMP programming model.
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 Programming Your GPU with
OpenMP, 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.
Programming Your GPU with OpenMP shares best practices for writing
performance portable programs. Key features include:
-
The most up-to-date APIs for programming GPUs with OpenMP with
concepts that transfer to other approaches for GPU programming.
-
Written in a tutorial style that embraces active learning, so that
readers can make immediate use of what they learn via provided source
code.
-
Builds the OpenMP GPU Common Core to get programmers to serious
production-level GPU programming as fast as possible.
Additional features:
- A reference guide at the end of the book covering all relevant parts
of OpenMP 5.2.
- 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.
- Tutorial videos and lecture slides.
