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#reversiblecomputing#landauer'slimit#unconventionalcomputing

Stanford Seminar - Generalized Reversible Computing and the Unconventional Computing Landscape

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  • Presented by Michael P. Frank, Sandia National Laboratories

Advanced. Deep dive for people who know the field.

15K views9 years ago2 recommendations

HardwareComputer scienceCPUs and computer architectureComputation and complexity

Michael P. Frank surveys unconventional computing approaches with a focus on reversible computing to overcome physical limits of CMOS scaling.

EE380: Computer Systems Colloquium Seminar Generalized Reversible Computing and the Unconventional Computing Landscape Speaker: Michael P. Frank, Sandia National Laboratories With the end of transistor scaling now in sight, the raw energy efficiency (and thus, practical performance) of conventional digital computing is expected to soon plateau. Thus, there is presently a growing interest in exploring various unconventional types of computing that may have the potential to take us beyond the limits of conventional CMOS technology. In this talk, I survey a range of unconventional computing approaches, with an emphasis on reversible computing (defined in an appropriately generalized way), which fundamental physical arguments indicate is the only possible approach that can potentially increase energy efficiency and affordable performance of arbitrary computations by unboundedly large factors as the technology is further developed About the Speaker: Michael Frank attended the world's first class on nanotechnology during his Freshman year at Stanford in 1988, and received his B.Sci. in Symbo­lic Systems in 1991, after helping the Cardinal take home the world championship trophy in the ACM International Collegiate Programming Contest. During his graduate work at MIT, his research interests zeroed in on the limits of computing. In 1995 he designed one of the first universal molecular computers using DNA, and, after finding that fundamental thermochemistry forced it to be reversible, he began studying more efficient electronic implementations of reversible computing for his Ph.D. After helping to design the world's first fully reversible microprocessors, he graduated in 1999 and spent most of the next 16 years teaching and continuing his research at the University of Florida and the FAMU-FSU College of Engineering. In 2015 he joined the Non-conventional Computing Technologies department at Sandia National Laboratories, where he is once again trying to help the world understand that it really needs to pursue reversible computing, so that civilization can extract unboundedly manyfold times greater total economic value from computation than would otherwise be possible. For more information about this seminar and its speaker, you can visit ee380.stanford.edu/Abstracts/171018.html Support for the Stanford Colloquium on Computer Systems Seminar Series provided by the Stanford Computer Forum. Colloquium on Computer Systems Seminar Series (EE380) presents the current research in design, implementation, analysis, and use of computer systems. Topics range from integrated circuits to operating systems and programming languages. It is free and open to the public, with new lectures each week. Learn more: bit.ly/WinYX5

Why it's here

2 people recommend this

What people say. Recommended as an extremely informative and deep dive into the physics and architecture of reversible computing.

jonbaeron Hacker News • Recommends

On “Are “reversible” computers more energy efficient, faster? (2004)”

I think Michael P Frank is one of the more knowledgable people working on the subject, his Stanford talk is extremely informative ... link to this video

gbrown_on Hacker News • Recommends

On “Reversible Computing”

For anyone interested in the topic I highly recommend checking out Dr. Michael P. Frank's work. This video is good one to start with link to this video

GiggleLiuon Hacker News • Mentions

On “Reversible Computing”

According to Michael Frank's video( link to this video ), there is an architectural overhead of ~500x that people can not get over (IIUC, this overhead only applies for gate based computing models). A reasonable gap between state-of-the-art gate based computing models and Landauer's limit should be 10^2-10^3. On the other side, reversible computing in general has 2-16 times computational overhead at the software level from my using experience. To save energy, reversible computing has to be at least ~10x more energy efficient at the instruction level.