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Scout: a data-parallel programming language for graphics processors

Patrick McCormick, Jeff Inman, James Ahrens, Jamaludin M. Yusof, Greg Roth, Sharen Cummins
Computer, Computational, and Statistical Sciences Division, Los Alamos National Laboratory, United States
Parallel Comput. In High-Performance Computing Using Accelerators, Vol. 33, No. 10-11. (29 September 2007), pp. 648-662

@article{mccormick2007scout,

   title={Scout: a data-parallel programming language for graphics processors},

   author={McCormick, P. and Inman, J. and Ahrens, J. and Mohd-Yusof, J. and Roth, G. and Cummins, S.},

   journal={Parallel Computing},

   volume={33},

   number={10-11},

   pages={648–662},

   issn={0167-8191},

   year={2007},

   publisher={Elsevier}

}

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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.
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