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Parallel and Distributed Processing Symposium, International (2005)
Denver, Colorado
Apr. 4, 2005 to Apr. 8, 2005
ISSN: 1530-2075
ISBN: 0-7695-2312-9
pp: 265a
Darrell R. Ulm , University of Akron
Michael Scherger , Kent State University
Parallel random access memory, or PRAM, is a now venerable model of parallel computation that that still retains its usefulness for the design and analysis of parallel algorithms. Parallel computational models proposed after PRAM address short comings of PRAM in terms of modeling realism of actual machines. In this work, we propose a multiple instruction stream partitioned PRAM, or "stream PRAM." This model embodies the reality of a small number of parallel processors, each with local memory (which could also be small), where a problem is generally evenly distributed among all processing elements. Actual hardware configurations limit the number of shared memories which can be efficiently implemented. By allowing each shared memory to also act as an independent instruction stream, more functionality is possible with a small extra cost. The additional instruction streams provide limited asynchronous abilities and offer the flexibility of a reconfigurable network as well as allowing the processing elements to perform independent actions. Because the proposed stream PRAM allows variable sizes for processors, memory, and problem sizes, it is valuable for present as well as future parallelism.
Darrell R. Ulm, Michael Scherger, "Stream PRAM", Parallel and Distributed Processing Symposium, International, vol. 15, no. , pp. 265a, 2005, doi:10.1109/IPDPS.2005.412
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