JuliaSIMD / JuliaSIMD/LoopVectorization.jl

Using AcuteBenchmark system

Abierto
#5 7 comentarios 0 reacciones 0 asignados Ver en GitHub
Lenguaje dominante
Julia
Estrellas
789
Forks
73
Métricas de merge de PR
Sin PR fusionados en 30 d

Descripción

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.

![IntelVectorMath Performance Comparison](https://github.com/JuliaMath/VML.jl/raw/AcuteBenchmark/benchmark/Real/bar/bench-dims-set4-relative.png)

Other than the Acutebenchmark doc, there is a fully working example available here: https://github.com/JuliaMath/VML.jl/blob/AcuteBenchmark/benchmark/benchmark.jl

Guía de contribución

No hay ninguna guía de contribución indexada para este repositorio

Línea de trabajo

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.

Escrito por el modelo de indexación a partir del texto del issue.

Evaluación

Stack tecnológico
julia
Área
performance, testing-qa
Tipo de issue
Nueva funcionalidad
Dificultad
4/5
Tiempo estimado
3-5 días
Estado de actividad
Estancado
Claridad
Bastante claro
Aptitud para principiantes
30/100

Recibe los nuevos issues en tu correo

Un resumen breve de issues de GitHub para principiantes.