This book constitutes the refereed proceedings of the First International Workshop on Communication and Architectural Support for Network-Based Parallel Computing, CANPC'97, held in San Antonio, Texas, USA, in February 1997. The 19 revised full papers presented were carefully selected from a total of 36 submissions. Among the topics addressed are processor/network interfaces, communication protocols, high-performance network technology, operating systems and architectural issues, and load balancing techniques. All in all, the papers competently describe the state-of-the-art for network-based computing systems.
This book constitutes the strictly refereed proceedings of the Second International Workshop on Communication and Architectural Support for Network-Based Parallel Computing, CANPC'98, held in Las Vegas, Nevada, USA, in January/February 1998. The 18 revised full papers presented were selected from 38 submissions on the basis of four to five reviews per paper. The volume comprises a representative compilation of state-of-the-art solutions for network-based parallel computing. Several new interconnection technologies, new software schemes and standards are studied and developed to provide low-latency and high-bandwidth interconnections for network-based parallel computing.
An in-depth overview of an emerging field that brings together high-performance computing, big data processing, and deep lLearning. Over the last decade, the exponential explosion of data known as big data has changed the way we understand and harness the power of data. The emerging field of high-performance big data computing, which brings together high-performance computing (HPC), big data processing, and deep learning, aims to meet the challenges posed by large-scale data processing. This book offers an in-depth overview of high-performance big data computing and the associated technical issues, approaches, and solutions. The book covers basic concepts and necessary background knowledge, including data processing frameworks, storage systems, and hardware capabilities; offers a detailed discussion of technical issues in accelerating big data computing in terms of computation, communication, memory and storage, codesign, workload characterization and benchmarking, and system deployment and management; and surveys benchmarks and workloads for evaluating big data middleware systems. It presents a detailed discussion of big data computing systems and applications with high-performance networking, computing, and storage technologies, including state-of-the-art designs for data processing and storage systems. Finally, the book considers some advanced research topics in high-performance big data computing, including designing high-performance deep learning over big data (DLoBD) stacks and HPC cloud technologies.
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