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    Hadoop Acceleration with Scalable Merging Algorithms
    Update time: 2011-10-28
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    Title: Hadoop Acceleration with Scalable Merging Algorithms
    Speaker: Dr. Weikuan Yu, Auburn University & Oak Ridge National Laboratory, USA
    Time: 10:00am—11:30am, October 28th, 2011 (Friday)
    Place: Room 1201, 12th Floor, ICT, CAS
    Cloud computing has emerged as a new computing paradigm for the government and industry to process and analyze increasingly larger volumes of data. Hadoop implements the MapReduce programming model for cloud computing. However, it faces a number of issues to achieve the best performance from the underlying system. These include a serialization barrier that delays the reduce phase, repetitive merges and disk access, and lack of capability to leverage latest high speed interconnects. This presentation will shed light on a number of recent efforts to leverage high speed interconnects and accelerate Hadoop for fast data analytics.
    In the talk, the speaker will also describe other active projects in his group and open positions and opportunities for students who are interested in studying abroad for their Ph.D. or post-doc training.
    Weikuan Yu is currently an Assistant Professor in the Department of Computer Science and Software Engineering at Auburn University, and a Joint Faculty Member in the Future Technolgoies group at Oak Ridge National Laboratory. He directs the Parallel Architecture and System Laboratory (PASL) which hosts a NVIDIA CUDA teaching center at Auburn University and a 30Teraflop, 80-node heterogenous GPU+CPU computer cluster. Yu has research interests on cloud computing, high-performance computing, computer architecture, file and storage systems, and interdisciplinary research on climate modeling and computational biology. Yu's research is sponsored by NASA, NSF, DOE/ORNL, Mellanox, NVIDIA, and Auburn University.

    Center for Advanced Computing Research, ICT
    October, 2011

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