JuliaSIMD / JuliaSIMD/LoopVectorization.jl
Using AcuteBenchmark system
- Langage dominant
- Julia
- Étoiles
- 789
- Forks
- 73
- Métriques de merge des PR
- Aucune PR mergée en 30 j
Description
I created a package for benchmarking functions called AcuteBenchmark.
https://github.com/aminya/AcuteBenchmark.jl
I particularly made it for [IntelVectorMath (VML)](https://github.com/JuliaMath/VML.jl/tree/AcuteBenchmark)
If you want we can switch the benchmarking system to AcuteBenchmark. It is very easy to use. It automatically generates random vectors based on the limits and the size given and then benchmarks and plots the result.

Other than the Acutebenchmark doc, there is a fully working example available here: https://github.com/JuliaMath/VML.jl/blob/AcuteBenchmark/benchmark/benchmark.jl
Guide de contribution
Aucun guide de contribution indexé pour ce dépôt
Piste de recherche
Start with the linked AcuteBenchmark documentation and the fully working example in benchmark/benchmark.jl, then compare them with the repository's current benchmarking setup. Determine whether adopting AcuteBenchmark fits this project and what benchmark coverage and plots would need to be preserved; done means the adoption decision and scope are documented.
Rédigé par le modèle d'indexation à partir du texte de l'issue.
Évaluation
- Stack technique
- julia
- Domaine
- performance, testing-qa
- Type d'issue
- Fonctionnalité
- Difficulté
- 4/5
- Temps estimé
- 3-5 jours
- Activité
- À l'abandon
- Clarté
- Plutôt claire
- Accessibilité débutants
- 30/100