The problem of mapping the tasks of a multitarget tracking algorithm onto parallel computing architectures to maximize speedup is considered. An asymptotically optimal mapping algorithm is developed and applied to study the effects of task granularity and processor architectures on the speedup. From the simulation results, it is concluded that task granularity and the parallelization of clustering and global hypotheses formation stages of the tracking algorithm are major determinants of speedup.<>


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    On mapping a tracking algorithm onto parallel processors


    Contributors:
    Pattipati, K.R. (author) / Kurien, T. (author) / Lee, R.-T. (author) / Luh, P.B. (author)


    Publication date :

    1990-09-01


    Size :

    1513652 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English