Issue No. 10 - Oct. (2012 vol. 23)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.298
Henry Hoffmann , Massachusetts Institute of Technology, Cambridge
Anant Agarwal , Massachusetts Institute of Technology, Cambridge
Srinivas Devadas , Massachusetts Institute of Technology, Cambridge
Design patterns for parallel computing attempt to make the field accessible to nonexperts by generalizing the common techniques experts use to develop parallel software. Existing parallel patterns have tremendous descriptive power, but it is often unclear to nonexperts how to choose a pattern based on the specific performance goals of a given application. This paper addresses the need for a pattern selection methodology by presenting four patterns and an accompanying decision framework for choosing from these patterns given an application's throughput and latency goals. The patterns are based on recognizing that one can partition an application's data or instructions and that these partitionings can be done in time or space, hence we refer to them as spatiotemporal partitioning strategies. This paper introduces a taxonomy that describes each of the resulting four partitioning strategies and presents a three-step methodology for selecting one or more given a throughput and latency goal. Several case studies are presented to illustrate the use of this methodology. These case studies cover several simple examples as well as more complicated applications including a radar processing application and an H.264 video encoder.
Cameras, Indexes, Spatiotemporal phenomena, Throughput, Spatial databases, Security, Decision trees, parallel programming, Design patterns, parallel computing
A. Agarwal, H. Hoffmann and S. Devadas, "Selecting Spatiotemporal Patterns for Development of Parallel Applications," in IEEE Transactions on Parallel & Distributed Systems, vol. 23, no. , pp. 1970-1982, 2012.