Title :
JazzMatch: fine-grained parallel matching for large rule sets
Author :
Richeldi, Marco ; Tan, Jack
Author_Institution :
Dept. of Comput. Sci., Houston Univ., TX, USA
Abstract :
JazzMatch, a parallel matching algorithm explicitly designed for secondary memory-based production systems, is presented. JazzMatch is a state-saving algorithm that performs incremental match. It exploits extremely fine-grained parallelism and optimizes the storage state by permitting the sharing of common conditions in the rules. JazzMatch is supported by a message passing parallel architecture. A cost and performance analysis of JazzMatch is provided, and the results are compared with those for other schemes in current literature
Keywords :
deductive databases; inference mechanisms; message passing; parallel programming; JazzMatch; fine-grained parallel matching; large rule sets; message passing parallel architecture; performance analysis; secondary memory-based production systems; state-saving algorithm; Algorithm design and analysis; Artificial intelligence; Costs; Lifting equipment; Memory management; Message passing; Parallel architectures; Parallel processing; Production systems; Relational databases;
Conference_Titel :
Data Engineering, 1993. Proceedings. Ninth International Conference on
Conference_Location :
Vienna
Print_ISBN :
0-8186-3570-3
DOI :
10.1109/ICDE.1993.344018
