Domain-Specific Computer Architectures for Emerging Applications: Machine Learning and Neural Networks

With the end of Moore’s Law, domain-specific architecture (DSA) has become a crucial mode of implementing future computing architectures. This book discusses the system-level design methodology of DSAs and their applications, providing a unified design process that guarantees functionality, performance, energy efficiency, and real-time responsiveness for the target application.

DSAs often start from domain-specific algorithms or applications, analyzing the characteristics of algorithmic applications, such as computation, memory access, and communication, and proposing the heterogeneous accelerator architecture suitable for that particular application. This book places particular focus on accelerator hardware platforms and distributed systems for various novel applications, such as machine learning, data mining, neural networks, and graph algorithms, and also covers RISC-V open-source instruction sets. It briefly describes the system design methodology based on DSAs and presents the latest research results in academia around domain-specific acceleration architectures.

Providing cutting-edge discussion of big data and artificial intelligence scenarios in contemporary industry and typical DSA applications, this book appeals to industry professionals as well as academicians researching the future of computing in these areas.

Dr. Chao Wang is an Associate Professor with School of Computer Science, University of Science and Technology of China. He is a Senior Member of ACM, Senior Member of IEEE, and Senior Member of CCF. He 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 visited Professor Yuan Xie’s research group in University of California, Santa Barbara from 2015 to 2016. He also worked with Infineon Technologies A.G. in 2007-2008. He is the Associate Editor of ACM Transactions on Design Automations for Electronics Systems (TODAES), IEEE/ACM Transactions on Computational Biology and Bioinformatics, Microprocessors and Microsystems, IET Computers & Digital Techniques, and International Journal of Electronics. Dr. Chao Wang was the recipient of Youth Innovation Promotion Association, CAS (2017), ACM China Rising Star Honorable Mention (2016), and best IP nomination of DATE 2015, Best Paper Candidate of CODES+ISSS 2018. He is now in the CCF Technical Committee on Computer Architecture, CCF Task Force on Formal methods. His webpage can be found at http: //staff.ustc.edu.cn/ cswang/