{"title":"Performance of a decentralized knowledge base system","authors":"Craig A. Lee, L. Bic","doi":"10.1109/ICDCS.1989.37964","DOIUrl":null,"url":null,"abstract":"The binary predicate execution model (BPEM) is a computational model that combines logic programming, semantic nets, and message-driven computation into a paradigm for the construction of highly parallel knowledge-base systems. Simulation results are presented that demonstrate the ability of BPM to exploit effectively the resources of a loosely coupled computer network consisting of large numbers of independent processing elements. These simulations suggest performance on the order of 10/sup 5/ logical inferences per second for 256 processing elements in an n-cube configuration. A very important feature of the BPEM is that it scales-up linearly under simple OR-parallelism and AND-parallelism. Hence, the BPEM can scale-up to exploit parallelism efficiently in very large semantic networks and knowledge bases.<<ETX>>","PeriodicalId":266544,"journal":{"name":"[1989] Proceedings. The 9th International Conference on Distributed Computing Systems","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1989-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1989] Proceedings. The 9th International Conference on Distributed Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDCS.1989.37964","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The binary predicate execution model (BPEM) is a computational model that combines logic programming, semantic nets, and message-driven computation into a paradigm for the construction of highly parallel knowledge-base systems. Simulation results are presented that demonstrate the ability of BPM to exploit effectively the resources of a loosely coupled computer network consisting of large numbers of independent processing elements. These simulations suggest performance on the order of 10/sup 5/ logical inferences per second for 256 processing elements in an n-cube configuration. A very important feature of the BPEM is that it scales-up linearly under simple OR-parallelism and AND-parallelism. Hence, the BPEM can scale-up to exploit parallelism efficiently in very large semantic networks and knowledge bases.<>