ABSTRACT
Exploiting unused processor time in workstation environments can result in large performance gains in user applications. A parallel each operator is shown which implements client-server based distributed processing. A time-consuming algorithm is sped up by using idle workstations in a local area network as APL servers.
- 1.A. Geyer-Schulz and T. Kolarik. Distribut, e~t Coniputing with APL. APL Quote Quad, 23(1), July 1992. (APL 92 Conference Proceedings). Google ScholarDigital Library
- 2.A. Y. Gralna and V. Kumar. Parallel Proce.~sing of Discrete Optimization Problems: A Survey, 1992. (to be published).Google Scholar
- 3.J. R. Koza. Genetic Evohltion and Co-Evolution of Computer Programs. In C. G. Langton, C. Taylor, J. D. Farmer, and S. Rasmussen, editors, Artificial Life II. Addison-Wesley, 1991.Google Scholar
- 4.D. E. Goldberg. Genetic Algorithm.~ in S~.arch, OI)- timization and Machine Learning. Addison-Wesley, 1989. Google ScholarDigital Library
- 5.V. Braitenberg. Vehicles - Experimcnt.~ in Synthetic P.,ychoIogy. MIT Press, 1984.Google Scholar
Index Terms
- Distributed computing in the workstation environment
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