I've always seen code execution speed measured either in units of time (e.g. t milliseconds), or using asymptotic analysis (e.g. O(n log n)). Execution speed will vary depending on hardware performance, and asymptotic analysis can tell us how code will perform relative to the size of the input, but they're not absolute terms.
For space performance, we have asymptotic analysis, but we can also measure performance in bytes, which allows us to express (and predict) space performance in both relative and absolute terms. e.g. algorithm X's space complexity is O(n) or n * 32 bytes of memory for implementation Y in language Z.
For example we can look at this code:
for i in n: pass
And if we know this will be executed using a 64-bit build of CPython, we can say this for loop will take up 72 + n * 8 bytes for the integer array and 8 bytes for each reference (independent of context/overhead).
My question is: Is there a unit of measurement we can use to express a piece of code's execution speed (or CPU usage) in absolute terms, similar to how we can with bytes for memory?