Talks to Watch

Stanford Seminar - Generalized Reversible Computing and the Unconventional Computing Landscape

16K views · Oct 19, 2017 · 1:10:03 · 2 HN recommenders · 3 mentions · discussed 2020–2021

A Stanford EE380 seminar by Michael P. Frank of Sandia National Laboratories on generalized reversible computing. It surveys unconventional computing approaches as transistor scaling nears its limits and energy efficiency stops improving.

Why Hacker News points people here: HN commenters cite it as an informative talk from a leading researcher in reversible computing, mainly in threads on reversible computers and energy efficiency.

“his Stanford talk is extremely informative”HN comment, 2020

What Hacker News said 3

Strongly recommendsjonbaerJul 2020

“his Stanford talk is extremely informative”

Informative Stanford talk by a leading reversible computing researcher

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

in “Are “reversible” computers more energy efficient, faster? (2004)” · view on HN
Recommendsgbrown_Feb 2021

“I highly recommend checking out Dr. Michael P. Frank's work.”

Good starting point for Michael Frank's work

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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 this video

Cites itGiggleLiuMar 2021

“there is an architectural overhead of ~500x that people can not get over”

Cites architectural overhead figure for reversible computing

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According to [Michael Frank's video]( 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.