Abstract
To handle complex problems of the type solved by human experts, knowledge bases will need to become larger than 10,000 chunks of knowledge. In order to provide necessary response times it appears that parallel inference must be considered. The advent of affordable parallel processing computers may allow the use of parallel inference to decrease reasoning time. In this paper we discuss Backpac, a backward-chained inferencing system designed to run on parallel processor machines. The system has been developed in Multilisp and rewritten in mul-t. The system has been tested on a 10 processor Encore Multimax in both languages. Several experiments, in Multilisp, have been run on the Concert [22] multiprocessor at the Harris Corporation. The speedups have ranged as high as an order of magnitude.
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