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R benchmark for High-Performance Analytics and Computing (II): GPU Packages

April 7, 2017
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R benchmark for High-Performance Analytics and Computing (II): GPU Packages

Share This: 1. Overview In the previous post (here), we have analyzed the performance gain of R in the heterogeneous system by accelerators, including NVIDIA GPU and Intel Xeon Phi. Furthermore, GPU accelerated packages can greatly improve the performance of R. Figure 1 shows the download statistics of CRAN over the years. Obviously, GPU is

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R benchmark for High-Performance Analytics and Computing (I)

April 14, 2016
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R benchmark for High-Performance Analytics and Computing (I)

  Objectives of Experiments R is more and more popular in various fields, including the high-performance analytics and computing (HPAC) fields. Nowadays, the architecture of HPC system can be classified as pure CPU system, CPU + Accelerators (GPGPU/FPGA) heterogeneous system, CPU + Coprocessors system. In software side, high performance scientific libraries, such as basic linear

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