BIB-VERSION:: CS-TR-v2.0
          ID:: STAN//CS-TR-87-1188
       ENTRY:: April 24, 1995
ORGANIZATION:: Stanford University, Department of Computer Science
       TITLE:: Experiments with a Knowledge-Based System on a Multiprocessor
        TYPE:: Technical Report
      AUTHOR:: Nakano, Russell
      AUTHOR:: Minami, Masafumi
        DATE:: October 1987
       PAGES:: 56
    ABSTRACT:: This paper documents the results we obtained and the lessons
               we learned in the design, implementation, and execution of a
               simulated real-time application on a simulated parallel
               processor. Specifically, our parallel program ran 100 times
               faster on a 100-processor multiprocessor.

               The machine architecture is a distributed-memory
               multiprocessor. The target machine consists of 10 to 1000
               processors, but because of simulator limitations, we ran
               simulations of machines consisting of 1 to 100 processors.
               Each processor is a computer with its own local memory,
               executing an independent instruction stream. There is no
               global shared memory; all processes communicate by message
               passing. The target programming environment, called Lamina,
               encourages a programming style that stresses performance
               gains through problem decomposition, allowing many processors
               to be brought to bear on a problem. THe key is to distribute
               the processing load over replicated objects, and to incresase
               throughput by building pipelined sequences of objects that
               handle stages of problem solving.

               We focused on a knowledge-based application that simulates
               real-time understanding of radar tracks, called Airtrac. This
               paper describes a portion of the Airtrac application
               implemented in Lamina and a set of experiments that we
               performed. We confirmed the following hypotheses: 1)
               Performance of our concurrent program improves with
               additional processors, and thereby attains a significant
               level of speedup. 2) Correctness of our concurrent program
               can be maintained despite a high degree of problem
               decomposition and highly overloaded input data conditions.
       NOTES:: [Adminitrivia V1/Prg/19950424]
         END:: STAN//CS-TR-87-1188