Parallel implementation of OPS5 on the encore multiprocessor: Results and analysis |
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Authors: | Anoop Gupta Milind Tambe Dirk Kalp Charles Forgy Allen Newell |
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Affiliation: | (1) Department of Computer Science, Stanford University, 94305 Stanford, California;(2) Department of Computer Science, Carnegie Mellon University, 15213 Pittsburgh, Pennsylvania |
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Abstract: | Until now, most results reported for parallelism in production systems (rulebased systems) have been simulation results-very few real parallel implementations exist. In this paper, we present results from our parallel implementation of OPS5 on the Encore multiprocessor. The implementation exploits very finegrained parallelism to achieve significant speed-ups. For one of the applications, we achieve 12.4 fold speed-up using 13 processes. Our implementation is also distinct from other parallel implementations in that we parallelize a highly optimized C-based implementation of OPS5. Running on a uniprocessor, our C-based implementation is 10–20 times faster than the standard lisp implementation distributed by Carnegie Mellon University. In addition to presenting the performance numbers, the paper discusses the details of the parallel implementation-the data structures used, the amount of contention observed for shared data structures, and the techniques used to reduce such contention. |
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Keywords: | Production Systems Rule-based Systems OPS5 Parallel Processing Fine-Grained Parallelism AI Architectures |
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