[csdvrx]

Sometimes, you can't find the average because it's undefined: it can happen with a Cauchy and a few other statistical distributions: the wikipedia page has a nice plot of how the first 2 moments don't converge https://en.wikipedia.org/wiki/Cauchy_distribution#History

When in doubt, don't use the mean: prefer more robust estimates, as even with degenerate statistical distributions, there are still some "good numbers to report" like the mode or the median.

And if you don't know statistics, just use a plot!

[FilosofumRex]

Indeed, the best averaging method depends on the underlying probability distribution from which data is drawn. Arithmetic is best for normal whereas geometric is better suited for lognormal distribution, and as the above comment suggests average is meaningless for most power law distributions where exponent is less than 2.

However, When all else fails, define your own Von Neumann entropy. Figure out how often you compile GCC, FFT, or video compression, then compute probabilities (ratios) and multiply by logarithm of speedups for each use case. Sum them up and report it as machine/architecture entropy and you'll win every argument about it.

[code_biologist]

I agree with your point, but it is funny to think about true consumer workloads: I... mostly JIT and run Javascript, layout algorithms, and whatever compositing cannot be offloaded to the GPU.