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 methodologiesFeaturing 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 EditorDr. 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.
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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.
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Section I Big Data ArchitecturesChapter 1 ◾ Dataflow Model for Cloud Computing Frameworks in Big DataDong Dai, Yong Chen, and Gangyong JiaChapter 2 ◾ Design of a Processor Core Customized for Stencil ComputationYouyang Zhang, Yanhua Li, and Youhui ZhangChapter 3 ◾ Electromigration Alleviation Techniques for 3D Integrated CircuitsYuanqing Cheng, Aida Todri-Sanial, Alberto Bosio, Luigi Dilillo, Patrick Girard, Arnaud Virazel, Pascal Vivet, and Marc BellevilleChapter 4 ◾ A 3D Hybrid Cache Design for CMP Architecture for Data-Intensive ApplicationsIng-Chao Lin, Jeng-Nian Chiou, and Yun-Kae LawSection II Emerging Big Data ApplicationsChapter 5 ◾ Matrix Factorization for Drug–Target Interaction PredictionYong Liu, Min Wu, Xiao-Li Li, and Peilin ZhaoChapter 6 ◾ Overview of Neural Network AcceleratorsYuntao Lu, Chao Wang, Lei Gong, Xi Li, Aili Wang, and Xuehai ZhouChapter 7 ◾ Acceleration for Recommendation Algorithms in Data MiningChongchong Xu, Chao Wang, Lei Gong, Xi Li, Aili Wang, and Xuehai ZhouChapter 8 ◾ Deep Learning AcceleratorsYangyang Zhao, Chao Wang, Lei Gong, Xi Li, Aili Wang, and Xuehai ZhouChapter 9 ◾ Recent Advances for Neural Networks Accelerators and OptimizationsFan Sun, Chao Wang, Lei Gong, Xi Li, Aili Wang, and Xuehai ZhouChapter 10 ◾ Accelerators for Clustering Applications in Machine LearningYiwei Zhang, Chao Wang, Lei Gong, Xi Li, Aili Wang, and Xuehai ZhouChapter 11 ◾ Accelerators for Classification Algorithms in Machine LearningShiming Lei, Chao Wang, Lei Gong, Xi Li, Aili Wang, and Xuehai ZhouChapter 12 ◾ Accelerators for Big Data Genome SequencingHaijie Fang, Chao Wang, Shiming Lei, Lei Gong, Xi Li, Aili Wang, and Xuehai Zhou
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Produktdetaljer
ISBN
9781498783996
Publisert
2017-10-10
Utgiver
Vendor
Chapman & Hall/CRC
Vekt
635 gr
Høyde
254 mm
Bredde
178 mm
Aldersnivå
P, 06
Språk
Product language
Engelsk
Format
Product format
Innbundet
Antall sider
268
Redaktør
Biographical note
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.