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Optimal multiprocessor real-time schedulers incur significant overhead for pre-emptions and migrations. We present RUN, an efficient scheduler that reduces the multiprocessor problem to a series of uniprocessor problems. RUN significantly outperforms existing optimal algorithms with an upper bound of O(log m) average preemptions per job on m processors (3(More)
We consider the problem of optimal real-time scheduling of periodic and sporadic tasks for identical multipro-cessors. A number of recent papers have used the notions of fluid scheduling and deadline partitioning to guarantee optimality and improve performance. In this paper, we develop a unifying theory with the DP-FAIR scheduling policy and examine how it(More)
The ability to change direction while sprinting is considered essential for successful participation in most team and individual sports. It has traditionally been thought that strength and power development would enhance change of direction (COD) performance. The most common approach to quantifying these relationships, and to discovering determinants(More)
The <i>MapReduce</i> framework is being extended for domains quite different from the web applications for which it was designed, including the processing of big structured data, e.g., scientific and financial data. Previous work using <i>MapReduce</i> to process scientific data ignores existing structure when assigning intermediate data and scheduling(More)
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