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<p><b>Abstract</b>—This paper evaluates the IBM SP2 architecture, the AIX parallel programming environment, and the IBM message-passing library (MPL) through STAP (Space-Time Adaptive Processing) benchmark experiments. Only coarse-grain parallelism was exploited on the SP2 due to its high communication overhead. A new parallelization scheme is developed for programming message passing multicomputers. Parallel STAP benchmark structures are illustrated with domain decomposition, efficient mapping of partitioned programs, and optimization of collective communication operations. We measure the SP2 performance in terms of execution time, Gflop/s rate, speedup over a single SP2 node, and overall system utilization. With 256 nodes, the Maui SP2 demonstrated the best performance of 23 Gflop/s in executing the High-Order Post-Doppler program, corresponding to a 34% system utilization. We have conducted a scalability analysis to reveal the performance growth rate as a function of machine size and STAP problem size. Important lessons learned from these parallel processing benchmark experiments are discussed in the context of real-time, adaptive, radar signal processing on massively parallel processors (MPP).</p>
Message passing, data parallelism, massively parallel processors, adaptive sensor array processing, scalability, programmability, performance evaluation, STAP benchmarks, real-time applications.

Z. Xu, K. Hwang and M. Arakawa, "Benchmark Evaluation of the IBM SP2 for Parallel Signal Processing," in IEEE Transactions on Parallel & Distributed Systems, vol. 7, no. , pp. 522-536, 1996.
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