Evaluating Performance Tradeoffs Between Fine-Grained and Coarse-Grained Alternatives

  • Authors:
  • Pradeep K. Dubey;George B. Adams, III;Michael J. Flynn

  • Affiliations:
  • IBM T. J. Watson Research Center, Yorktown Heights, NY;Purdue Univ., West Lafayette, IN;Stanford Univ., Stanford, CA

  • Venue:
  • IEEE Transactions on Parallel and Distributed Systems
  • Year:
  • 1995

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Abstract

Recent simulation based studies suggest that while superpipelines and superscalars are equally capable of exploiting fine grained concurrency, multiprocessors are better at exploiting coarse grained parallelism. An analytical model that is more flexible and less costly in terms of run time than simulation, is proposed as a tool for analyzing the tradeoff between superpipelined processors, superscalar processors, and multiprocessors. The duality of superpipelines and superscalars is examined in detail. The performance limit for these systems has been derived and it supports the fetch bottleneck observation of previous researchers. Common characteristics of utilization curves for such systems are examined. Combined systems, such as superpipelined multiprocessors and superscalar multiprocessors, are also analyzed. The model shows that the number of pipelines (or processors) at which the maximum throughput is obtained is, as memory access time increases, increasingly sensitive to the ratio of memory access time to network access delay. Further, as a function of interiteration dependence distance, optimum throughput is shown to vary nonlinearly, whereas the corresponding optimum number of processors varies linearly. The predictions from the analytical model agree with similar results published using simulation based techniques