Associate Professor, Electrical and Computer Engineering
University of Minnesota
Seminar: New and Improved! Stochastic Computing 2.0: Lower Power, Lower Latency, and Higher Accuracy
Abstract: Touted as a possible design strategy for emerging technologies that promise scaling beyond CMOS, the paradigm of stochastic computing has garnered attention in recent years. Computation is performed probabilistically, on streams of random bits. Complex functions can be computed with remarkably simple logic. This talk reexamines the foundations of stochastic computing and comes to some surprising conclusions. It demonstrates that one can compute deterministically using the same structures that are used to compute stochastically. In doing so, (i) the latency is reduced by an exponential factor; (ii) the area is reduced significantly which correlates with a reduction in power; and (iii) one obtains completely accurate results, with no errors or uncertainty. As with stochastic computing, the deterministic computation is on bit streams where the value is represented by the fraction of ones versus zeros. As such, it can described as "time-based" or unary computation. The approach is motivated by the observation that, as technology has scaled and device sizes have gotten smaller, the supply voltages have dropped while the device speeds have improved. Control of the dynamic range in the voltage domain is limited; however, control of the length of pulses in the time domain can be precise. Given how precisely values can be encoded in the time, the method could produce designs that are much faster than conventional ones -- operating in the terahertz range.
About the Speaker: Riedel is Associate Professor of Electrical and Computer Engineering at the University of Minnesota. From 2006 to 2011 he was Assistant Professor. He is also a member of the Graduate Faculty in Biomedical Informatics and Computational Biology. From 2004 to 2005, he was a lecturer in Computation and Neural Systems at Caltech. He has held positions at Marconi Canada, CAE Electronics, Toshiba, and Fujitsu Research Labs. He received his Ph.D. and his M.Sc. in Electrical Engineering at Caltech and his B.Eng. in Electrical Engineering with a Minor in Mathematics at McGill University. His Ph.D. dissertation titled "Cyclic Combinational Circuits" received the Charles H. Wilts Prize for the best doctoral research in Electrical Engineering at Caltech. His paper "The Synthesis of Cyclic Combinational Circuits" received the Best Paper Award at the Design Automation Conference. He is a recipient of the NSF CAREER Award.
Host: Cong Shen, assistant professor of electrical and computer engineering.