A statistical method was developed previously for improving process mapping heuristics. The method systematically explores the space of possible heuristics under a specified time constraint. Its goal is to get the best possible heuristics while trading between the solution quality of the process mapping heuristics and their execution time. The statistical selection method is extended to take into consideration the variations in the amount of time used to evaluate heuristics on a problem instance. The improvement in performance is presented using the more realistic assumption along with some methods that alleviate the additional complexity.


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    Title :

    Learning process mapping heuristics under stochastic sampling overheads


    Contributors:

    Conference:

    AIAA Computing in Aerospace Conference ; 1991 ; Baltimore, MD, United States


    Publication date :

    1991-01-01


    Type of media :

    Conference paper


    Type of material :

    No indication


    Language :

    English


    Keywords :


    Learning process mapping heuristics under stochastic sampling overheads

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