High performance computing for big data : methodologies and applications / edited by Chao Wang.

Format
Book
Language
English
Εdition
1st ed.
Published/​Created
Boca Raton : Taylor & Francis, a CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the Academic Division of T&F Informa, plc, [2017]
Description
1 online resource (268 pages).

Availability

Available Online

Details

Subject(s)
Editor
Series
Summary note
"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. FeaturesCovers a wide range of Big Data architectures, including distributed systems like Hadoop/SparkIncludes accelerator-based approaches for big data applications such as GPU-based acceleration techniques, and hardware acceleration such as FPGA/CGRA/ASICsPresents emerging memory architectures and devices such as NVM, STT- RAM, 3D IC design principlesDescribes advanced algorithms for different big data application domainsIllustrates 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."--Provided by publisher.
Bibliographic references
Includes bibliographical references and index.
Source of description
Description based on print version record.
Contents
  • part Section 1: 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
  • part Section 2: 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
  • chapter 11 ? Accelerators for Classification Algorithms in Machine Learning
  • chapter 12 ? Accelerators for Big Data Genome Sequencing haiJie Fang, chao wang, ShiMing Lei, Lei gong, Xi Li, aiLi wang, anD Xuehai Zhou.
ISBN
  • 1-351-65157-9
  • 1-315-15552-4
  • 1-4987-8400-3
OCLC
1005692900
Doi
  • 10.1201/9781315155524
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