Performance comparison of scientific applications on Cray architectures
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You, Haihang↗
Engineering topics
Patel, Pragneshkumar B
Publications and source records attributed to Patel, Pragneshkumar B.
Combining R with Scalable Libraries to Get the Best of Both for Big Data
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Ostrouchov, George↗
Tight Coupling of R and Distributed Linear Algebra for High-Level Programming with Big Data
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Schmidt, Drew↗
OpenMP-style parallelism in data-centered multicore computing with R
R is a domain specific language widely used for data analysis by the statistics community as well as by researchers in finance, biology, social sciences, and many other disciplines. As R programs are linked to input data, the exponential growth of available data makes high-performance computing with R imperative. To ease the process of writing parallel programs in R, code transformation from a sequential program to a parallel version would bring much convenience to R users. In this paper, we present our work in semiautomatic parallelization of R codes with user-added OpenMPstyle pragmas. While such pragmas are used at the frontend, we take advantage of multiple parallel backends with different R packages. We provide flexibility for importing parallelism with plug-in components, impose built-in MapReduce for data processing, and also maintain code reusability. We illustrate the advantage of the on-the-fly mechanisms which can lead to significant applications in data-centered parallel computing.
Jiang, Lei↗