Optimizing the MapReduce framework on Intel Xeon Phi coprocessor

@article{Lu2013OptimizingTM,
  title={Optimizing the MapReduce framework on Intel Xeon Phi coprocessor},
  author={Mian Lu and Lei Zhang and Huynh Phung Huynh and Zhongliang Ong and Yun Liang and Beixin Julie He and Rick Siow Mong Goh and Richard Huynh},
  journal={2013 IEEE International Conference on Big Data},
  year={2013},
  pages={125-130}
}
MapReduce has become one of the most popular framework for building big-data applications. It was originally designed for distributed-computing, and has been extended to various hardware architectures, e.g., multi-core CPUs, GPUs and FPGAs. In this work, we develop the first MapReduce framework on the recently released Intel Xeon Phi coprocessor. We utilize advanced features of the Xeon Phi to achieve high performance. In order to take advantage of the SIMD vector processing units, we propose a… CONTINUE READING
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