• Smaller data sets are problematic because — Overheads involved with launching a kernel — GPU underutilization: lower thread count has lower tolerance for long memory access latencies as there are no "other threads" ready to run. • Not all algorithms benefit from parallelization — Trade off between "parallelization effort" and "performance gain". — If it takes a lot of effort to parallelize an algorithm, it might mean that the algorithm is has no inherent parallelism, (e.g. the aircraft climbing metric).


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    Title :

    Massively parallel processing for dynamic airspace configuration


    Contributors:


    Publication date :

    2011-10-01


    Size :

    594773 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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