Scout: a data-parallel programming language for graphics processors

被引:23
|
作者
McCormick, Patrick [1 ]
Inman, Jeff [1 ]
Ahrens, James [1 ]
Mohd-Yusof, Jamaludin [1 ]
Roth, Greg [2 ]
Cummins, Sharen [1 ]
机构
[1] Los Alamos Natl Lab, Comp Computat & Stat Sci Div, Los Alamos, NM 87545 USA
[2] Univ Utah, Dept Comp Sci, Salt Lake City, UT 84112 USA
基金
美国能源部;
关键词
graphics processors; data-parallel programming; heterogeneous computing; visualization;
D O I
10.1016/j.parco.2007.09.001
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
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. Published by Elsevier B.V.
引用
收藏
页码:648 / 662
页数:15
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