Title :
Configuring a parallel knowledge engine
Author :
Arran, John M. ; Saeedi, M.H. ; Steele, Bob
Author_Institution :
Comput. Res. Center, Sheffield Hallam Univ., UK
Abstract :
We present results from our research work on the parallel processing of knowledge-base systems, for which a new computational model has been developed. The focus is on the preprocessing aspect of this model, which plays a crucial role in reducing the communication overheads and establishing a suitable environment for run-time processing. Algorithms have been developed for three operations: the clustering of hierarchies, their mapping to a processor network, and the determination of efficient communication paths between hierarchies assigned to adjacent and non-adjacent processors. Throughout these operations speed is a primary goal, and the algorithms developed are designed to give good solutions in reasonable time, rather than to give optimal solutions
Keywords :
inference mechanisms; knowledge based systems; knowledge engineering; parallel processing; resource allocation; software performance evaluation; Sheffield Parallel Inference Knowledge Engine; communication overhead; computational model; hierarchy clustering; knowledge-base systems; parallel knowledge engine; parallel processing; processor network; research; run-time processing; speed; time; Algorithm design and analysis; Clustering algorithms; Computational modeling; Concurrent computing; Data preprocessing; Delay; Engines; Hardware; Inference algorithms; Parallel processing;
Conference_Titel :
Artificial Neural Networks and Expert Systems, 1995. Proceedings., Second New Zealand International Two-Stream Conference on
Conference_Location :
Dunedin
Print_ISBN :
0-8186-7174-2
DOI :
10.1109/ANNES.1995.499472
