[GiggleLiu]

It is not clever to build a completely reversible computer. No one wants to undo the computing to erase the disk after training a neural network for a month. Reversible computing is not always more energy efficient. The "proof" follows from the Bennett's time space tradeoff: https://www.math.ucsd.edu/~sbuss/CourseWeb/Math268_2013W/Lev...

As the coarse graining process goes, the ratio between computing time and garbadge space size increases exponentially. Erasing space is more energy efficient when E_compute/E_erase > N_uncompute/N_erase, where E and N are energy and number of instructions.

BUT, it is very likely to have a reversible computing device like GPU that can do part of works. The key point is: most reversible computing devices CAN erase information, although with energy cost. We just need to switch between uncomputing and erasing at the right place. e.g NiLang is an eDSL that lives in function level, while most other reversible programming languages are standalone.