2 HN users recommended this lecture2 months2020–2021score 2.5
Years with an HN recommendation, 2007–2026
HN commenters cite it as an informative talk from a leading researcher in reversible computing, mainly in threads on reversible computers and energy efficiency.
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.
“his Stanford talk is extremely informative” (HN, 2020)
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.
Cites architectural overhead figure for reversible computing
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