I'm trying to explain why some complex process obeys Central Limit Theorem.
The process is a chip compiler that runs complex place & route algorithms. The input is an integer seed. It initializes the algorithms in a random way. The output is a real number, which determines quality of results; the higher the number - the better. Exact implementation of place & route algorithms is not known. But their goal is to reach quality of results be positive.
I run 100 compiles with different seeds. When I plot a histogram of the results, it looks like a normal distribution. I tried different designs, tool versions, etc., and always get nicely shaped normal distribution, but with different mean and variance.
I strongly suspect that Central Limit Theorem plays a role here. But why?
Why would a complex place&route algorithm obey CLT, if it has nothing to do with any random distribution. Or maybe the interpretation of the results has nothing to do with the CLT.
Below is a process block diagram and example of the results.