1st Edition

High Performance Computing for Big Data Methodologies and Applications

Edited By Chao Wang Copyright 2018
286 Pages
by Chapman & Hall

286 Pages 118 B/W Illustrations
by Chapman & Hall

286 Pages 118 B/W Illustrations
by Chapman & Hall

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... Read more

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

Biography

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.