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Stanford Seminar - Generalized Reversible Computing and the Unconventional Computing Landscape
About this video
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 it appears in the archive
HN commenters cite it as an informative talk from a leading researcher in reversible computing, mainly in threads on reversible computers and energy efficiency.
AI-generated summary and labels from the source dataset; verify important details against the video. Source & credits.
From the Hacker News discussion
I think Michael P Frank is one of the more knowledgable people working on the subject, his Stanford talk is extremely informative ... [VIDEO]
Read original comment ↗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 [VIDEO]
Read original comment ↗According to [Michael Frank's video]( [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.
Read original comment ↗