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8-Way Linux Distribution Benchmarks On The Intel Core i9 9900K - One Distro Wins 67% Of The Time

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  • #41
    Originally posted by Zyklon View Post

    My comment was in general that I don’t see a point in doing Octave benchmarks at all, as someone who cares even just a litte bit about performance in scientific computing would never consider Octave in the first place. Even if you run Octave on a dual Xeon machine with terabytes of RAM, Julia on a Raspberry Pie will burn it to the ground with ease. Here are some numbers to compare: https://julialang.org/benchmarks

    Would really be rad if you’re interested in including Julia benchmarks! Here are some, for example:

    https://github.com/JuliaCI/BaseBenchmarks.jl
    https://github.com/JuliaCI/BenchmarkTools.jl
    I'm rather doubtful of that statement. Octave can be extremely fast when working with properly vectorized code. A recursive algorithm such as the one on that page is rather a worst-case scenario.
    Most of the time you use the builtin functions, anyway. Most of these have native and optimized implementations. Then you run the data trough vector operations, that are performed by BLAS-compatible libraries. I'm not sure you can beat that performance-wise.

    On the other hand, sure, basic looping, branching and function calling is quite slow in Octave (though there was a LLVM-based JIT in the works). But I use it a lot, and I've never been disappointed by its performance.

    Vectorizing can be quite hard for newcomers, though: I once helped a guy speed up his materials simulation from a couple days of runtime to a couple seconds. That was with MATLAB, mind you (which is faster than Octave in the aforementioned worst-cases, without JIT at least).

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    • #42
      Originally posted by Artemis3 View Post
      Artix Linux... No systemd. See if your compile optimized systemd can defeat runit...
      Does Artix Linux use its own package repositories like Manjaro? Arco uses Arch Linux's repositories.

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