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High Performance Computing for Big Data - 
      Chao Wang

High Performance Computing for Big Data

Methodologies and Applications

Chao Wang (Redaktør)

High-Performance Computing for Big Data: Methodologies and Applications explores emerging high-performance architectures for data-intensive applications, novel efficient analytical strategies to boost data processing, and cutting-edge applications in diverse fields, such as machine learning, life science, neural networks, and neuromorphic engineering. Les mer
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Innbundet
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Innbundet
Legg i
Vår pris: 1688,-

(Innbundet) Fri frakt!
Leveringstid: Sendes innen 21 dager

High-Performance Computing for Big Data: Methodologies and Applications explores emerging high-performance architectures for data-intensive applications, novel efficient analytical strategies to boost data processing, and cutting-edge applications in diverse fields, such as machine learning, life science, neural networks, and neuromorphic engineering.





The book is organized into two main sections. The first section covers Big Data architectures, including cloud computing systems, and heterogeneous accelerators. It also covers emerging 3D IC design principles for memory architectures and devices. The second section of the book illustrates emerging and practical applications of Big Data across several domains, including bioinformatics, deep learning, and neuromorphic engineering.


Features








Covers a wide range of Big Data architectures, including distributed systems like Hadoop/Spark







Includes accelerator-based approaches for big data applications such as GPU-based acceleration techniques, and hardware acceleration such as FPGA/CGRA/ASICs







Presents emerging memory architectures and devices such as NVM, STT- RAM, 3D IC design principles







Describes advanced algorithms for different big data application domains







Illustrates novel analytics techniques for Big Data applications, scheduling, mapping, and partitioning methodologies








Featuring contributions from leading experts, this book presents state-of-the-art research on the methodologies and applications of high-performance computing for big data applications.





About the Editor





Dr. Chao Wang is an Associate Professor in the School of Computer Science at the University of Science and Technology of China. He is the Associate Editor of ACM Transactions on Design Automations for Electronics Systems (TODAES), Applied Soft Computing, Microprocessors and Microsystems, IET Computers & Digital Techniques, and International Journal of Electronics. Dr. Chao Wang was the recipient of Youth Innovation Promotion Association, CAS, ACM China Rising Star Honorable Mention (2016), and best IP nomination of DATE 2015. He is now on the CCF Technical Committee on Computer Architecture, CCF Task Force on Formal Methods. He is a Senior Member of IEEE, Senior Member of CCF, and a Senior Member of ACM.





FAKTA
Utgitt:
Forlag: Productivity Press
Innbinding: Innbundet
Språk: Engelsk
Sider: 268
ISBN: 9781498783996
Format: 25 x 18 cm
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VURDERING
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Section I Big Data Architectures





Chapter 1 Dataflow Model for Cloud Computing Frameworks in Big Data


Dong Dai, Yong Chen, and Gangyong Jia





Chapter 2 Design of a Processor Core Customized for Stencil Computation


Youyang Zhang, Yanhua Li, and Youhui Zhang





Chapter 3 Electromigration Alleviation Techniques for 3D Integrated Circuits


Yuanqing Cheng, Aida Todri-Sanial, Alberto Bosio, Luigi Dilillo, Patrick Girard, Arnaud Virazel, Pascal Vivet, and Marc Belleville





Chapter 4 A 3D Hybrid Cache Design for CMP Architecture for Data-Intensive Applications


Ing-Chao Lin, Jeng-Nian Chiou, and Yun-Kae Law





Section II Emerging Big Data Applications





Chapter 5 Matrix Factorization for Drug-Target Interaction Prediction


Yong Liu, Min Wu, Xiao-Li Li, and Peilin Zhao





Chapter 6 Overview of Neural Network Accelerators


Yuntao Lu, Chao Wang, Lei Gong, Xi Li, Aili Wang, and Xuehai Zhou





Chapter 7 Acceleration for Recommendation Algorithms in Data Mining


Chongchong Xu, Chao Wang, Lei Gong, Xi Li, Aili Wang, and Xuehai Zhou





Chapter 8 Deep Learning Accelerators


Yangyang Zhao, Chao Wang, Lei Gong, Xi Li, Aili Wang, and Xuehai Zhou





Chapter 9 Recent Advances for Neural Networks Accelerators and Optimizations


Fan Sun, Chao Wang, Lei Gong, Xi Li, Aili Wang, and Xuehai Zhou





Chapter 10 Accelerators for Clustering Applications in Machine Learning


Yiwei Zhang, Chao Wang, Lei Gong, Xi Li, Aili Wang, and Xuehai Zhou





Chapter 11 Accelerators for Classification Algorithms in Machine Learning


Shiming Lei, Chao Wang, Lei Gong, Xi Li, Aili Wang, and Xuehai Zhou





Chapter 12 Accelerators for Big Data Genome Sequencing


Haijie Fang, Chao Wang, Shiming Lei, Lei Gong, Xi Li, Aili Wang, and Xuehai Zhou
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.