Abstract
We have ported the SIMD Parka knowledge representation system to generic MIMD machines. The system has been recoded in C and supported using runtime optimization packages developed in the High Performance Systems Software Laboratory at the University of Maryland. New "scanning" algorithms have been developed for inheritance and recognition inferences. These algorithms have been tested with both random networks and on a recoding of the ontology of the CYC knowledge base as well as on large planning case-bases. Tests show that the new version is significantly faster than the SIMD system, and that it promises to scale well to knowledge bases orders of magnitude larger than CYC.
| Original language | English |
|---|---|
| Pages (from-to) | 95-118 |
| Number of pages | 24 |
| Journal | Machine Intelligence and Pattern Recognition |
| Volume | 20 |
| Issue number | C |
| DOIs | |
| State | Published - 1997 |
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