High Performance Parallel Computing with Cloud and Cloud Technologies
نویسندگان
چکیده
We present our experiences in applying, developing, and evaluating cloud and cloud technologies. First, we present our experience in applying Hadoop and DryadLINQ to a series of data/compute intensive applications and then compare them with a novel MapReduce runtime developed by us, named CGL-MapReduce and MPI. Preliminary applications are developed for particle physics, bioinformatics, clustering, and matrix multiplications. We identify the basic execution units of the MapReduce programming model and categorize the runtimes according to their characteristics. MPI versions of the applications are used where the contrast in performance needs to be highlighted. We discuss the application structure and their mapping to parallel architectures of different types, and look at the performance of these applications. Next, we present a performance analysis of MPI parallel applications on virtualized resources.
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تاریخ انتشار 2009