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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: