An experiment in knowledge-base signal understanding using parallel architectures

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abstract: This report documents an experiment investigating the potential of a parallel computing architecture to enhance the performance of a knowledge-based signal understanding system. The experiment consisted of implementing and evaluating an application encoded in a parallel programming extension of Lisp and executing on a simulated multiprocessor system.The chosen application for the experiment was a knowledge-based system for interpreting pre-processed, passively acquired radar emissions from aircraft. The application was implemented in an experimental concurrent, asynchronous object-oriented framework. This framework, in turn, relied on the services provided by the underlying hardware system. The hardware system for the experiment was a simulation of various sized grids of processors with inter-processor communication via message-passing.The experiment investigated the effects of various high-level control strategies on the quality of the problem solution, the speed of the overall system performance as a function of the number of processors in the grid, and some of the issues in implementing and debugging a knowledge-based system on a message-passing multiprocessor system.In this report we describe the software and (simulated) hardware components of the experiment and present the qualitative and quantitative experimental results.

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