- Häftad (Paperback / softback)
- Antal sidor
- Softcover reprint of the original 1st ed. 2017
- Springer International Publishing AG
- Wang, Yu / Yang, Huazhong
- 43 Illustrations, color; 8 Illustrations, black and white; IX, 129 p. 51 illus., 43 illus. in color.
- Antal komponenter
- 1 Paperback / softback
Du kanske gillar
Parallel Sparse Direct Solver for Integrated Circuit Simulation
Fri frakt inom Sverige för privatpersoner.
Skickas inom 3-6 vardagar1399
Passar bra ihop
De som köpt den här boken har ofta också köpt Probabilistic Approaches for Geotechnical Site ... av Zijun Cao, Yu Wang, Li Dianqing (inbunden).Köp båda 2 för 3158 kr
Bloggat om Parallel Sparse Direct Solver for Integra...
Xiaoming Chen is now a Visiting Assistant Professor with the Department of Computer Science and Engineering, University of Notre Dame. He received the B.S. and Ph.D. degrees from the Department of Electronic Engineering, Tsinghua University, in 2009 and 2014, respectively. His research interests include hardware security, deep learning, parallel circuit simulation, and circuit reliability. Yu Wang is an Associate Professor with the Department of Electronic Engineering, Tsinghua University. He received the B.S. and Ph.D. (with honor) degrees from the Department of Electronic Engineering, Tsinghua University, in 2002 and 2007, respectively. His research interests include parallel circuit analysis, power/reliability-aware system design methodology, brain inspired computing, and application specific hardware computing. Huazhong Yang is a specially-appointed Professor of the Cheung Kong Scholars Program with the Department of Electronic Engineering, Tsinghua University. He received the B.S. degree in microelectronics and the M.S. and Ph.D. degrees in electronic engineering from Tsinghua University, in 1989, 1993, and 1998, respectively. His current research interests include wireless sensor networks, data converters, parallel circuit simulation algorithms, nonvolatile processors, and energy-harvesting circuits.
Introduction.- Related Work.- Overall Solver Flow.- Parallel Sparse Left-Looking Algorithm.- Improvement Techniques.- Test Results.- Performance Model.- Conclusions.