Scout: a data-parallel programming language for graphics processors

Commodity graphics hardware has seen incredible growth in terms of performance, programmability, and arithmetic precision. Even though these trends have been primarily driven by the entertainment industry, the price-to-performance ratio of graphics processors (GPUs) has attracted the attention of ma...

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Bibliographic Details
Published in:Parallel computing Vol. 33; no. 10; pp. 648 - 662
Main Authors: McCormick, Patrick, Inman, Jeff, Ahrens, James, Mohd-Yusof, Jamaludin, Roth, Greg, Cummins, Sharen
Format: Journal Article
Language:English
Published: Elsevier B.V 01.11.2007
Subjects:
Data-parallel programming
Graphics processors
Heterogeneous computing
Visualization
Data-parallel programming
Visualization
Graphics processors
Heterogeneous computing
ISSN:0167-8191, 1872-7336
Online Access:Get full text
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Summary:Commodity graphics hardware has seen incredible growth in terms of performance, programmability, and arithmetic precision. Even though these trends have been primarily driven by the entertainment industry, the price-to-performance ratio of graphics processors (GPUs) has attracted the attention of many within the high-performance computing community. While the performance of the GPU is well suited for computational science, the programming interface, and several hardware limitations, have prevented their wide adoption. In this paper we present Scout, a data-parallel programming language for graphics processors that hides the nuances of both the underlying hardware and supporting graphics software layers. In addition to general-purpose programming constructs, the language provides extensions for scientific visualization operations that support the exploration of existing or computed data sets.
ISSN:0167-8191
1872-7336
DOI:10.1016/j.parco.2007.09.001