10月29日学术报告信息(Ohio State University , Xiaoyi Lu )

10月29日学术报告信息(Ohio State University , Xiaoyi Lu )

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报告题目：Accelerating Big Data Processing and Management through HPC Technologies

报告日期及时间：2015.10.29 上午10:00-11:00

报告地点：计算机学院B404

报告人： Xiaoyi Lu (鲁小亿)

报告人国籍：中国

报告人单位：Ohio State University

报告人简介：

Dr. Xiaoyi Lu is a Research Scientist in the Department of Computer Science and Engineering at the Ohio State University, USA.
His current research interests include high-performance interconnects and protocols, Big Data processing and management, Hadoop/Spark ecosystem, parallel computing
models (MPI/PGAS), virtualization and Cloud Computing. He has published over 50 papers in major journals and international
conferences related to these research areas. He has been actively involved in various professional activities (PC Co-Chair, PC Member, Reviewer, etc.) in academic journals and conferences. More details about Dr. Lu are available at
http://web.cse.ohio-state.edu/~luxi. .

报告摘要：

Modern HPC systems and the associated middleware (such as MPI and parallel file systems) have been exploiting the advances
in HPC technologies (multi/many-core architecture, RDMA-enabled networking, and SATA/NVMe-SSD) during the last decade. However, Big Data processing and management middleware (such as Hadoop, Spark, and Memcached) have not
embraced such technologies. These disparities are taking HPC and Big Data processing into divergent trajectories. This talk will
provide an overview of challenges in accelerating Big Data processing and management middleware on modern HPC clusters.
Using the publicly available software packages in the High-Performance Big Data (HiBD, http://hibd.cse.ohio-state.edu) project, case studies of advanced designs based on RDMA and heterogeneous storage architecture for multiple
components of Hadoop, Spark, and Memcached will be presented. Benefits of these designs on various HPC cluster
configurations will be shown. The talk will also address the need for designing benchmarks using a multi-layered approach, which can be used to evaluate the performance of these middleware. All these work aim to bring HPC and
Big Data processing into a convergent trajectory.

邀请人：龚奕利副教授

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