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Knowledge-based system for parallel processing of logic programs

Thesis/Dissertation ·
OSTI ID:6210741
Current research on parallel execution of logic programs exploits dynamic parallelism: the parallel processes are dynamically allocated to solve the goals generated in the run-time. This dissertation introduces a knowledge-based execution model, which statically allocates program partitions prior to execution. Each processor is specialized by the allocation, and only handles a category of goals that consult the local knowledge base. A static allocation scheme not only presents better execution characteristics, but also supports the operational semantics that logic-program execution is knowledge deduction. Consequently, this knowledge-based execution model provides new opportunities for knowledge-base maintenance and machine learning in a multiprocessor environment. With help from mode declaration and run-time literal status checking, the computation model takes advantage of the single-assignment characteristics of logic variables to spawn AND-parallel processing.
Research Organization:
Aeronutronic, Newport Beach, CA (USA)
OSTI ID:
6210741
Country of Publication:
United States
Language:
English

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