High Performance Computing for Big Data Methodologies and Applications

This book presents state-of-the-art research, methodologies, and applications of high performance computing for big data applications. It covers fundamental issues in Big Data research, including emerging architectures for data-intensive applications, novel analytical strategies to boost data processing, and cutting-edge applications.

About the author

Prof. Chao Wang received B.S. and Ph.D. degrees from School of Computer Science, University of Science and Technology of China, in 2006 and 2011 respectively. He has been a postdoctoral researcher in USTC from 2011 to 2013. He also worked with Infineon Technologies A.G. in 2007-2008. He is the associate editor of Microprocessors and Microsystems, IET Computers & Digital Techniques, and International Journal of Electronics.

Summary

This book presents state-of-the-art research, methodologies, and applications of high performance computing for big data applications. It covers fundamental issues in Big Data research, including emerging architectures for data-intensive applications, novel analytical strategies to boost data processing, and cutting-edge applications.

Product details

• Authors: Chao (City University of Hong Kong Wang, Chao (University of Science and Technology o Wang, Chao Wang
• Assisted by: Wang Chao (Editor), Chao Wang (Editor)
• Publisher: Taylor & Francis Ltd.
• Content: Book
• Product form: Hardback
• Publication date: 10.10.2017
• Subject: Natural sciences, medicine, IT, technology > IT, data processing > General, dictionaries
• EAN: 9781498783996
• ISBN: 978-1-4987-8399-6
• Pages: 268
• Series: Chapman & Hall/CRC Big Data Series
• Subjects: Data Mining, NN, COMPUTERS / General, BUSINESS & ECONOMICS / Statistics, Distributed Data Processing, COMPUTERS / Programming / Games, FPGA, Energy Efficiency, Databases, Supercomputers, Probability and statistics, Computer architecture and logic design, COMPUTERS / Data Science / Data Analytics, neural network, Neuromorphic systems, Cloud Infrastructure, heterogeneous computing, KNN Algorithm, dataflow model, RNNs, Convolutional Layers, bioinformatics algorithms, memory architecture design, high performance machine learning applications, DNNs, DBSCAN Algorithm, IP Core, Average AUC, Multiple FPGAs, General Purpose Processors, Distance Calculation Function, User Base CF, Spin Transfer Torque Ram, Acceleration Ratio, FPGA Platform, Cache Banks, Intel Core I7 Cpu