The ability to dumping entropy is essential to computing, so Wei Dai's work is relevant. Limits on entropy dumping provide limits on computation.

Actually this is not generally true. The ability to dump entropy .. . is simply the ability to dump entropy. In the current dominant framework of irreversible deterministically programmable von neuman architectures, entropy is dumped left and right. Moore's law for traditional computing will run into this landauer limit relatively soon - this decade or next at the latest, and it will come to a hard end.

However, many algorithms can actually use entropy. Any type of algorithm that can use about as much entropy as it produces can trivially be made fully reversible and approach asymptotic zero net energy dissipation. Monte carlo simulation is a prototypical example, and entropy has similar uses in pattern prediction from compressed knowledge in the domain of AI algorithms.

Furthermore, advanced physics simulations of the type that future upload civilizations would desire can be made trivially reversible because physics itself is reversible. Any state updates and differential equations used in physics simulation are thus reversible and need not even produce any waste entropy. This combined with the potential positive uses of any actual entropy could allow computation in general to continue to advance. The limit only applies to specific classes of computation, and fortunately the most important future domains of massive computation (general simulation and related general intelligence) are fully reversible at zero penalty.

Yes, approaching those limits will require very low temperatures and there will always be some random entropy coming in from the outside on the surface of the computer, but this surface can simply be used as a source entropy circuit.

And finally, moving from deterministic to nondeterministic statistical computation in general further eliminates potential problems with entropy.

Of course there are other limits: there is a fundamental final limit based on QM quantization and the uncertainty principle in the minimum energy required to represent a bit and compute a "bit op".

That limit is very far away, but miniaturization limits of building any structures out of atoms places a closer soft limit in terms of the energy density that can be contained in a molecular structure. This may limit regular computing out of safe everyday materials to chemical bond energy densities, but we exceed those densities in nuclear reactors and eventually we could achieve those energy densities in computation. And again if the computation is reversible and all entropy is recycled it need not generate any heat (although the result of catastrophic failure of such a system could result in a nuclear-level accident, so this severely constrains the practical economics).

Looking farther ahead we can see that the uncertainty principle does not say that 1 quantum of energy can only use or compute 1 bit. In fact the limits are unimaginably more generous. An interaction (such as a collision) of 2 particles with N bit-states can have on the order 2^N possible output states, so the final ladder is to turn each individual particle into a complex functional mapping or small computer unto-itself. If climbing that ladder is ever practically possible (and it appears to be), it may not technically lead to infinity but it's close enough. This is all with known physics.