Computational modeling

Approximate Computing With Stochastic Transistors’ Voltage Over-Scaling

1 min read · Tue, Jan 1 2019

Circuits Transistors Stochastic processes Approximate computing Computational modeling

Ren Li, et al., "Approximate Computing With Stochastic Transistors’ Voltage Over-Scaling" IEEE Access 7, 2019, 6373. Ubiquitous computing and the ever-rising need for energy efficiency pose challenges in terms of the processing requirements and the corresponding machine complexity. Nonetheless, the nature of the underlying applications, particularly dealing with real-world data, offers alternative paradigms toward the efficient utilization of the available design resources. In this paper, approximate computing is addressed as an accommodating technique that can benefit from the inherent

Hiroyuki Kuwahara

Research Scientist, Structural and Functional Bioinformatics

Computational modeling synthetic biology Stochastic processes control systems molecular evolution

Hiroyuki Kuwahara got his Ph.D. degree in Computer Science from the University of Utah in 2008. He was then a junior researcher at Microsoft Research - Trento during 2007 and 2009. During 2009 and 2012, he was a Ray and Stephanie Lane Fellow at the School of Computer Science at Carnegie Mellon University. Since 2012, he joined the SFB group as a Research Scientist. Research Interests Hiroyuki's area of research is broadly in computational systems and synthetic biology. His main research focus is on the theoretical understanding of how various uncertainties contribute to the relation between