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dc.contributor.authorFann, YWen_US
dc.contributor.authorYang, CTen_US
dc.contributor.authorTsai, CJen_US
dc.contributor.authorTseng, SSen_US
dc.date.accessioned2014-12-08T15:27:21Z-
dc.date.available2014-12-08T15:27:21Z-
dc.date.issued1998en_US
dc.identifier.isbn0-8186-8603-0en_US
dc.identifier.urihttp://hdl.handle.net/11536/19602-
dc.description.abstractIn this paper we propose a knowledge-based approach for solving loop-scheduling problems. A rule-based system, called the IPLS, is developed by repertory grid and attribute ordering table to construct the knowledge base. The IPLS chooses an appropriate scheduling algorithm by inferring some features of loops and assign parallel loops on multiprocessors for achieving high speedup. In addition, the refined system of IPLS can automatically adjust the attributes in, knowledge base according to profile information; therefore IPLS has the feedback-learning ability.en_US
dc.language.isoen_USen_US
dc.titleIPLS: An intelligent parallel loop scheduling for multiprocessor systemsen_US
dc.typeProceedings Paperen_US
dc.identifier.journal1998 INTERNATIONAL CONFERENCE ON PARALLEL AND DISTRIBUTED SYSTEMS, PROCEEDINGSen_US
dc.citation.spage775en_US
dc.citation.epage782en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000078318400095-
Appears in Collections:Conferences Paper