Graphics processing unit (GPU) programming strategies and trends in GPU computing

Over the last decade, there has been a growing interest in the use of graphics processing units (GPUs) for non-graphics applications. From early academic proof-of-concept papers around the year 2000, the use of GPUs has now matured to a point where there are countless industrial applications. Together with the expanding use of GPUs, we have also seen a tremendous development in the programming languages and tools, and getting started programming GPUs has never been easier. However, whilst getting started with GPU programming can be simple, being able to fully utilize GPU hardware is an art that can take months or years to master. The aim of this article is to simplify this process, by giving an overview of current GPU programming strategies, profile-driven development, and an outlook to future trends.

► The article gives a step-by-step guide to profile-guided optimization of graphics processing unit (GPU) algorithms.
► The article gives an overview of current GPU hardware and programming techniques required to achieve peak performance.
► The article gives an overview of current and future trends of GPU computing.