Buch, Englisch, 286 Seiten, Format (B × H): 185 mm x 257 mm, Gewicht: 726 g
Methodologies and Applications
Buch, Englisch, 286 Seiten, Format (B × H): 185 mm x 257 mm, Gewicht: 726 g
Reihe: Chapman & Hall/CRC Big Data Series
ISBN: 978-1-4987-8399-6
Verlag: Taylor & Francis Ltd (Sales)
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.
Zielgruppe
Professional Practice & Development
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Part 1 Architecture
Dataflow Model for Cloud Computing Frameworks in Big Data
Dong Dai, Yong Chen, Gangyong Jia
Design of a Processor-core Customized for Stencil Computation
Youyang Zhang, Yanhua Li, and Youhui Zhang
Electromigration Alleviation Techniques for 3D Integrated Circuits
Yuanqing Cheng, Aida Todri-Sanial, Alberto Bosio, Luigi Dilillo, Patrick Girard, Arnaud Virazel, Pascal Vivet, Marc Belleville
A 3D Hybrid Cache Design for CMP Architecture for Data-intensive Applications
Ing-Chao Lin, Jeng-Nian Chiou, and Yun-Kae Law
Part 2 Applications
Matrix Factorization for DrugTarget Interaction Prediction
Yong Liu, Min W, Peilin Zhao; Xiao-Li Li
Overview of Neural Network Accelerators
Yuntao Lu, Chao Wang, Lei Gong, Xi Li, Aili Wang, and Xuehai Zhou
Acceleration for Recommendation Algorithms in Data Mining
Chongchong Xu, Chao Wang, Lei Gong, Xi Li, Aili Wang, and Xuehai Zhou
Deep Learning Accelerators
Yangyang Zhao, Chao Wang, Lei Gong, Xi Li, Aili Wang, and Xuehai Zhou
Recent Advances for Neural Networks Accelerators and Optimizations
Fan Sun, Chao Wang, Lei Gong, Xi Li, Aili Wang, and Xuehai Zhou
Accelerators for Clustering Applications in Machine Learning
Yiwei Zhang, Chao Wang, Lei Gong, Xi Li, Aili Wang, and Xuehai Zhou
Accelerators for Classification Algorithms in Machine Learning
Shiming Lei, Chao Wang, Lei Gong, Xi Li, Aili Wang, and Xuehai Zhou
Accelerators for Big Data Genome Sequencing
Haijie Fang, Chao Wang, Shiming Lei, Lei Gong, Xi Li, Aili Wang, and Xuehai Zhou
