nodebook
fib
nodebook | fib | |
---|---|---|
1 | 5 | |
1,645 | 900 | |
0.0% | 1.1% | |
0.0 | 7.1 | |
about 1 year ago | about 2 months ago | |
Go | Ruby | |
ISC License | - |
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nodebook
fib
- Not only Clojure – Chez Scheme: Lisp with native code speed
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Is Rust faster than Python out of the box
I've typically found rust to be about 100x faster than Python for the projects I've ported. This is consistent with https://github.com/drujensen/fib.
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Speed & LSP
Here is a similar benchmark but includes compile times. https://github.com/drujensen/fib
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Elixir Protocols vs. Clojure Multimethods
How? Do you mean how do I know it's slow? Because it takes longer to run.
Write a typical computation such as Fibonacci in Java and Erlang/Elixir and compare. Fortunately someone has already done this.
Elixir is 3x slower than C and 2x slower than Java for this single thread example.
https://github.com/drujensen/fib
Apparently this upsets people for me to point this out. However, I did not say that Elixir was slow in general or a bad choice. It's an excellent choice for problems which suit parallelization or which require reliable, consistent performance.
Since the parent poster had commented that adding this multi-module dispatch would not be performant, I merely pointed out that the single thread peformance was already slow (as in, why worry too much about the performance cost of the multi dispatch suggestion).
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I created a GitHub repo of some simple benchmarks to test different programming languages. Feel free to add more languages!
Is there some advantage over repos that also show the results ?
What are some alternatives?
codecrumbs - Learn, design or document codebase by putting breadcrumbs in source code. Live updates, multi-language support and more.
nx - Multi-dimensional arrays (tensors) and numerical definitions for Elixir
comby - A code rewrite tool for structural search and replace that supports ~every language.
protocol_ex - Elixir Extended Protocol
syntax-highlighter - Syntax Highlighter extension for Visual Studio Code (VSCode). Based on Tree-sitter.
tangram - Tangram makes it easy for programmers to train, deploy, and monitor machine learning models.