nheer

7 ms·

1.
by nheer 9mo ago
Thanks for the links - the benchmarks game is a great resource and has been around for a long time. That said, I'm not sure what "do better" means here. This is an open source project I maintain in my spare time. If you see r
2.
by nheer 9mo ago
Author here. There are actually 3 Swift versions in the benchmark: - Swift (standard): 893ms - Swift (relaxed): 903ms (uses fast-math equivalent) - Swift (SIMD): 509ms (explicit SIMD4) The standard version uses x *= -1.0 which cr
3.
by nheer 9mo ago
Author here. I just tested this with Zig by timing the segments inside the program: 1 billion iterations: - Startup + file read: 0.01ms - Computation: ~200ms - Overhead: 0.01% Even at 1 million iterations (0.24ms total), startu
4.
by nheer 9mo ago
Author here! Thanks for the detailed breakdown. Let me address a few points: - C++ SIMD being slower: The standard C++ uses i & 0x1 which lets the compiler auto-vectorize. With -O3 -ffast-math -march=native, gcc/clang do this reall
5.
by nheer 9mo ago
Author here — yep, you understood the repository correctly. My Python version is a good example of the structure: read rounds.txt, run the loop, print the result, exit. I’m timing the whole program with hyperfine. I agree that for a “pure
6.
by nheer 9mo ago
Thank you for your comment. > > a silly little experiment > This I don't like. What do you mean with that? To explain what I meant. I knew that that in the end this was a microbenchmark. It can certainly give you some clue abo
7.
by nheer 9mo ago
Hi everyone, author here! I’m genuinely blown away by all the interest in what started as a silly little experiment. The project grew way beyond its original scope. My initial curiosity was simply: how could you set up a pipeline to do au