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Comment by jesse__ | Hacker News Reader

Author here, AMA :)

pretty sweet! I'm mostly interested in how / what did you do to measure the performance and focus on a function. Is it perf pretty much with hist or visualizer or what?

I just called _rdtsc() before and after the noise gen once every iteration, and pushed the sample onto a fixed size buffer .. after some N iterations (4k maybe, can't remember) of samples, computed min/max/avg.

There's a little project here that I used to benchmark in part 4

https://github.com/scallyw4g/bonsai_noise_bench

Nice write-up, and congratulations on the result! Since it's about perlin and performance, have you had a look at opensimplex?

PS. bonsai looks really cool! Checking it out right now

I haven't looked at opensimplex. I will when I get around to doing a simplex implementation.

And thanks for the kind words!

Which compiler & optimization settings did you use? Out of curiosity, any idea why the compiler failed to auto-vectorize the loops?

Clang -O2

-O3 didn't seem to make any appreciable difference.

Re. the auto-vectorization, I really don't know. I didn't even read the assembly the compiler generated until at least halfway through the process. Generally I've found that you basically can't rely on the compiler auto vectorizing anything, ever, if it actually matters.

you should post the result at the end

and yes, make a benchmark

(although I would not know how to make one, or what reference point to use)

what do you think about the fastnoiselite implementation used in godot?

I kinda did post results at the end of part 4 .. I beat the SOTA by 1.8x

There's a benchmark utility here: https://github.com/scallyw4g/bonsai_noise_bench

Fastnoise2 is a high quality library. Can't speak to fastnoiselite .. never looked at it.

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