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<p><b>Abstract</b>—In a <it>distributed shared memory</it> (DSM) multiprocessor, the processors cooperate in solving a parallel application by accessing the shared memory. The latency of a memory access depends on several factors, including the distance to the nearest valid data copy, data sharing conditions, and traffic of other processors. To provide a better understanding of DSM performance and to support application tuning and compiler development for DSM systems, this paper extends microbenchmarking techniques to characterize the important aspects of a DSM system. We present an experiment-based methodology for characterizing the memory, communication, scheduling, and synchronization performance, and apply it to the Convex SPP1000. We present carefully designed microbenchmarks to characterize the performance of the local and remote memory, producer-consumer communication involving two or more processors, and the effects on performance when multiple processors contend for utilization of the distributed memory and the interconnection network.</p>
Performance evaluation, memory performance, communication performance, microbenchmarking, distributed shared memory, Convex SPP1000.

G. A. Abandah and E. S. Davidson, "Characterizing Distributed Shared Memory Performance: A Case Study of the Convex SPP1000," in IEEE Transactions on Parallel & Distributed Systems, vol. 9, no. , pp. 206-216, 1998.
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