High-Performance Big Data Computing

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Description

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. 

Additional information

Weight 0.58 kg
Dimensions 1.73 × 18.27 × 23.65 cm
PubliCanadation City/Country

USA

by

, ,

format

Language

Pages

272

publisher

Year Published

2022-8-2

Imprint

ISBN 10

0262046857

About The Author

Dhabaleswar K. Panda is Professor and University Distinguished Scholar of Computer Science and Engineering at the Ohio State University. Xiaoyi Lu is an Assistant Professor in the Department of Computer Science and Engineering at the University of California, Merced. Dipti Shankar is currently working at SAP, Germany. 

Table Of Content

Acknowledgments viii1 Introduction 12 Parallel Programming Models and Systems 133 Parallel and Distributed Storage Systems 374 HPC Architectures and Trends 615 Opportunities and Challenges in Accelerating Big Data Computing 936 Benchmarking Big Data Systems 1077 Accelerations with RDMA 1218 Accelerations with Multicore/Accelerator Technologies 1459 Acceleration with High-Performance Storage Technologies 15910 Deep Learning over Big Data 17511 Designs with Cloud Technologies 19512 Frontier Research on High-Performance Big Data Computing 215References 227Index 257

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