Parallel fuzzy inference on hypercube computer

Sang Gu Lee*, Hee Hyol Lee, Michio Miyazaki, Kageo Akizuki

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review


In fuzzy database systems that have very large rules or fuzzy data, the inference time is much increased. Therefore, a high performance parallel fuzzy inference architecture is needed. In this paper, we propose a novel parallel fuzzy inference engine using Hypercube architecture. In this, fuzzy rules are distributed and executed simultaneously. The ONE_TO_ALL algorithm is used to broadcast the fuzzy input to the all nodes. The results of the MIN/MAX operations are transferred to the output processor by the ALL_TO_ONE algorithm. By parallel processing of the fuzzy rules, the parallel fuzzy inference algorithm extracts match parallelism and achieves a good speed factor. This architecture can be used in large expert systems or fuzzy database systems.

Original languageEnglish
PagesI-309 - I-314
Publication statusPublished - 1999 Dec 1
Externally publishedYes
EventProceedings of the 1999 IEEE International Fuzzy Systems Conference, FUZZ-IEEE'99 - Seoul, South Korea
Duration: 1999 Aug 221999 Aug 25


OtherProceedings of the 1999 IEEE International Fuzzy Systems Conference, FUZZ-IEEE'99
CitySeoul, South Korea

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Artificial Intelligence
  • Applied Mathematics


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