As someone posted Landauer’s principle, I’m going to elaborate. Computation is not zero entropy as many operations (the classic example is erasing memory, which you can think about as filling a buffer with a constant) is not invertible. You are mapping memory from holding any value to a constant. Given memory filled with that constant, you can’t undo that deletion unless you have a copy saved somewhere else (in which case the inverse requires extra knowledge than just the state of the memory).
This is also true for many more useful computations: OR and XOR and modulo are not invertible because they map many possible inputs to the same value.
Thus, if you have a distribution over inputs to your algorithm, the distribution over outputs cannot have more entropy and typically will have less.