Implementation of production systems on message passing computers: Simulation results and analysis


A. Acharya, M. Tambe, and A. Gupta. 1992. “Implementation of production systems on message passing computers: Simulation results and analysis.” In IEEE Transactions on Parallel and Distributed Computing (IEEE TPDC), 4th ed., 3: Pp. 477-487.


In the past, researchers working on parallel implementations of production systems have focused on shared- memory multiprocessors and special-purpose architectures. Message-passing computers have not been given as much attention. The main reasons for this have been the large message- passing latency (as large as a few milliseconds) and high message-handling overheads (several hundred microseconds) associated with the first generation message-passing computers. These overheads were too large for parallel implementations of production systems, which require a fine-grain decomposition to obtain a significant speedup. Recent advances in interconnection network technology and processing element design, however, promise to reduce the network latency and message-handling overhead by 2-3 orders of magnitude, making these computers much more interesting for implementation of production systems. In this paper, we examine the suitability of message-passing computers for parallel implementations of production systems. We present two mappings for production systems on these computers, one targeted toward fine-grained message-passing machines and the other targeted toward medium-grained machines. We also present simulation results for the medium- grained mapping and show that it is possible to exploit the available parallelism and to obtain reasonable speedups. Finally, we perform a detailed analysis of the results and suggest solutions for some of the problems. Index Terms- Coarse-grain mapping, concurrent distributed hash table, fine-grain mapping, medium-grain mapping, message- passing computers, OPS5, parallel production systems, Rete net- work, simulation results.
See also: 1992
Last updated on 05/31/2020