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Exploiting HPC Technologies for Accelerating Big Data Processing and Associated Deep Learning

In this video from the 2018 Swiss HPC Conference, DK Panda from Ohio State University presents: Exploiting HPC Technologies for Accelerating Big Data Processing and Associated Deep Learning. "This talk will provide an overview of challenges in accelerating Hadoop, Spark, and Memcached on modern HPC clusters. An overview of RDMA-based designs for Hadoop (HDFS, MapReduce, RPC and HBase), Spark, Memcached, Swift, and Kafka using native RDMA support for InfiniBand and RoCE will be presented. Enhanced designs for these components to exploit NVM-based in-memory technology and parallel file systems (such as Lustre) will also be presented. Benefits of these designs on various cluster configurations using the publicly available RDMA-enabled packages from the OSU HiBD project (http://hibd.cse.ohio-state.edu) will be shown. Benefits of these stacks to accelerate deep learning frameworks (such as CaffeOnSpark and TensorFlowOnSpark) will be presented." Learn more: http://www.hpcadvisorycouncil.com/eve... Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter