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

Authors:
André R. Brodtkorb;Trond R. Hagen;Martin L. SæTra
Affiliations:
SINTEF ICT, Department of Applied Mathematics, P.O. Box 124, Blindern, NO-0314 Oslo, Norway;SINTEF ICT, Department of Applied Mathematics, P.O. Box 124, Blindern, NO-0314 Oslo, Norway and Centre of Mathematics for Applications, University of Oslo, P.O. Box 1053 Blindern, NO-0316 Oslo, No ...;Centre of Mathematics for Applications, University of Oslo, P.O. Box 1053 Blindern, NO-0316 Oslo, Norway
Venue:
Journal of Parallel and Distributed Computing
Year:
2013

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Abstract

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.