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General Purpose Computation on Graphics Hardware
Minneapolis, Minnesota October 23-October 28
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/VIS.2005.4316th IEEE Visualization 2005 (VIS 2005)
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Aaron Lefohn, University of California, Davis
Ian Buck, NVIDIA Corporation
Patrick McCormick, Los Alamos National Lab
John Owens, University of California, Davis
Timothy Purcell, NVIDIA Corporation
Robert Strzodka, Caesar Institute, Bonn, Germany
Desktop computer architecture is at a turning point. In the last two years, CPU speeds have nearly stopped increasing and all major CPU manufacturers have announced multi-core, parallel processors. Future performance improvements will predominantly come from parallelism rather than from an ever-increasing uniprocessor clock speed. Commodity graphics processors (GPUs), in contrast, already contain many parallel processing units and are capable of sustaining computation rates greater than ten times that of a modern CPU. The GPU programming model, however, is very different from traditional CPU models. Researchers in the evolving field of general-purpose computation on graphics processors (GPGPU) are actively developing techniques to make the power of GPUs accessible to a wide range of programmers. This tutorial provides a detailed introduction and overview of GPGPU programming abstractions, modern GPU architectures, and the techniques required for attendees to apply GPUs to their own applications.
Citation:
Aaron Lefohn, Ian Buck, Patrick McCormick, John Owens, Timothy Purcell, Robert Strzodka, "General Purpose Computation on Graphics Hardware," vis, pp.121, 16th IEEE Visualization 2005 (VIS 2005), 2005
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