Reversible computing escapes the lab

Hi, someone pointed me at your comment, so I thought I'd reply.

First, the circuit techniques that aren't reversible aren't truly, fully adiabatic either -- they're only quasi-adiabatic. In fact, if you strictly follow the switching rules required for fully adiabatic operation, then (ignoring leakage) you cannot erase information -- none of the allowed operations achieve that.

Second, to say reversible operation "only saves an extra 20%" over quasi-adiabatic techniques is misleading. Suppose a given quasi-adiabatic technique saves 79% of the energy, and a fully adiabatic, reversible version saves you "an extra 20%" -- well, then now that's 99%. But, if you're dissipating 1% of the energy of a conventional circuit, and the quasi-adiabatic technique is dissipating 21%, that's 21x more energy efficient! And so you can achieve 21x greater performance within a given power budget.

Next, to say "resistive losses dominate the losses" is also misleading. The resistive losses scale down arbitrarily as the transition time is increased. We can actually operate adiabatic circuits all the way down to the regime where resistive losses are about as low as the losses due to leakage. The max energy savings factor is on the order of the square root of the on/off ratio of the devices.

Regarding "adiabatic circuits can typically only provide an order of magnitude power savings" -- this isn't true for reversible CMOS! Also, "power" is not even the right number to look at -- you want to look at power per unit performance, or in other words energy per operation. Reducing operating frequency reduces the power of conventional CMOS, but does not directly reduce energy per operation or improve energy efficiency. (It can allow you to indirectly reduce it though, by using a lower switching voltage.)

You are correct that adiabatic circuits can benefit from frequency scaling more than traditional CMOS -- since lowering the frequency actually directly lowers energy dissipation per operation in adiabatic circuits. The specific 4000x number (which includes some benefits from scaling) comes from the analysis outlined in this talk -- see links below - but we have also confirmed energy savings of about this magnitude in detailed (Cadence/Spectre) simulations of test circuits in various processes. Of course, in practice the energy savings is limited by the resonator Q value. And a switched-capacitor design (like a stepped voltage supply) would do much worse, due to the energy required to control the switches.

https://www.sandia.gov/app/uploads/sites/210/2023/11/Comet23... https://www.youtube.com/watch?v=vALCJJs9Dtw

Happy to answer any questions.

Can one define the process of an adiabetic circuit goes through like one would do analogusly for the carnot engine? The idea being coming up with a theoretical cieling for the efficiency of such a circuit in terms of circuit parameters?

Maybe this would work better with superconducting electronics?

Does it not take energy to process information? Can any computable function be computed with arbitrarily low energy input/entropy increase?

Someone else here compared it to regenerative braking in cars, which is what made it click for me. If you spend energy to accelerate, then recapture that energy while decelerating, then you can manage to transport yourself while your net energy expenditure is zero (other than all that pesky friction). On the other hand, if you spend energy to accelerate, then shed all that energy via heat from your brake pads, then you need to expend new energy to accelerate next time.

The trick is not to have a voltage across the channel while it's transitioning states. For this reason, adiabatic circuits are typically "phased" such that any given adiabatic logic gate is either having its gates charged or discharged (by the previous logic gate), or current is passing through its channels to charge/discharge the next logic gate.

As well as Tommaso Toffoli, Norman Margolus, Tom Knight, Richard Feynman, and Charles Bennett:

Reversible Computing, Tommaso Toffoli:

https://publications.csail.mit.edu/lcs/pubs/pdf/MIT-LCS-TM-1...

>Abstract. The theory of reversible computing is based on invertible primitives and composition rules that preserve invertibility. With these constraints, one can still satisfactorily deal with both functional and structural aspects of computing processes; at the same time, one attains a closer correspondence between the behavior of abstract computing systems and the microscopic physical laws (which are presumed to be strictly reversible) that underly any concrete implementation of such systems. According to a physical interpretation, the central result of this paper is that it is ideally possible to build sequential circuits with zero internal power dissipation.

A Scalable Reversible Computer in Silicon:

https://www.researchgate.net/publication/2507539_A_Scalable_...

Reversible computing:

https://web.eecs.utk.edu/~bmaclenn/Classes/494-594-UC-F17/ha...

>In 1970s, Ed Fredkin, Tommaso Toffoli, and others at MIT formed the Information Mechanics group to the study the physics of information. As we will see, Fredkin and Toffoli described computation with idealized, perfectly elastic balls reflecting o↵ barriers. The balls have minimum dissipation and are propelled by (conserved) momentum. The model is unrealistic but illustrates many ideas of reversible computing. Later we will look at it briefly (Sec. C.7).

>They also suggested a more realistic implementation involving “charge packets bouncing around along inductive paths between capacitors.” Richard Feynman (Caltech) had been interacting with Information Mechanics group, and developed “a full quantum model of a serial reversible computer” (Feynman, 1986).

>Charles Bennett (1973) (IBM) first showed how any computation could be embedded in an equivalent reversible computation. Rather than discarding information (and hence dissipating energy), it keeps it around so it can later “decompute” it back to its initial state. This was a theoretical proof based on Turing machines, and did not address the issue of physical implementation. [...]

>How universal is the Toffoli gate for classical reversible computing:

https://quantumcomputing.stackexchange.com/questions/21064/h...

Well actually, "reversible driving" is perfectly apt in the sense of acceleration being a reversible process. It means that in theory the net energy needed to drive anywhere is zero because all the energy spent on acceleration is gained back on braking. Yes I know in practice there's always friction loss, but the point is there isn't a theoretical minimum amount of friction that has to be there. In principle a car with reversible driving can get anywhere with asymptotically close to zero energy spent.

Put another way, there is no way around the fact that a "non-reversible car" has to have friction loss because the brakes work on friction. But there is no theoretical limit to how far you can reduce friction in reversible driving.

The reverse computing is independent of the energy storage mechanism. It's used to "remember" how to route the energy for recovery.

A pub in Cambridge, perhaps! I doubt you'd overhear such talk in some Aldershot dive.

The Falling Edge, maybe? The Doped Wafer?

Sounds like a good time :)

Quantum computations have to be reversible , because you have to collapse the wave function and take a measurement to throw away any bits of data. You can accumulate junk bits as long as they remain in a superposition. But at some point you have to take a measurement. So, very much related.

I doubt it would use DRAM. Maybe some sort of MRAM/FeRAM would be a better fit. Or maybe a tiny amount of memory (e.g. Josephson junction) in a quantum circuit at some point in the future.