Janvier 2024

Bonjour,

Les prochains wébinaires :

• Trixi platform le 6 février 2024 à 10:00.

• Beta Machine Learning Toolkit le 15 mars 2024 à 10:00.

• FourierFlows.jl le 16 mai 2024 à 10:00.

Merci beaucoup d’être venus si nombreux au webinaire de janvier.

Jusqu’à la version 1.10, les développeurs du noyau se sont concentrés sur les temps de compilation. Cet objectif est désormais atteint. Les principaux objectifs du langage pour la version 1.11 et les suivantes sont :

• Améliorer les performances des allocations et “garbage collector”.

• Compilation statique et création de binaires de taille réduite.

Désolé j’ai perdu le lien vers la source de ces informations...

Billets de blog¶

• Stefan Krastanov - This month in Julia world - 2024-01

• Emma Boudreau - The Julia Guide To Extensible Software

• Mojtaba Farmanbar - Conformalize a time series model using Julia

• Steven Whitaker - Installing Julia and VS Code - A Comprehensive Guide

• Steven Whitaker - Understanding Variables and Functions

• Steven Whitaker - Mastering the Julia REPL

• Steven Whitaker - Explore the Capabilities of Broadcasting in Julia Programming

• Justyn Nissly - Understanding the Julia Type System

• Steven Whitaker - Basic Data Structures Explained

• Steven Whitaker - Harnessing the Power of Multiple Dispatch in Julia Programming

• Steven Whitaker - Exploring Modules and Variable Scope in Julia Programming

• Steven Whitaker - Delving into Open Source Packages for Julia

• Great Lakes Consulting - Julia’s Parallel Processing

• Alec Loudenback - How to (Almost) Never Lose A Game

• Kjartan Thor Wikfeldt - A brief tour of Julia for High Performance Computing

Packages¶

• ACAFact.jl : A simple adaptive cross approximation (ACA) factorization in Julia.

• AutoPrettyPrinting.jl : Pretty printing in Julia without all that annoying “writing code” business.

• Bumper.jl : Creating and garbage-collecting arrays in the middle of a performance sensitive piece of code is one of the most common performance pitfalls in the julia language. Bumper.jl provides users with a way to create and destroy intermediate arrays with zero performance compromises, and useful features for developers.

• ChebParticleMesh.jl : Using Chebyshev polynomials to interpolate/gather particles onto mesh grids.

• ComplexityMeasures.jl : Estimators for probabilities, entropies, and other complexity measures derived from observations in the context of nonlinear dynamics and complex systems.

• ElementaryPDESolutions.jl : Compute closed form solutions to certain PDEs with an elementary (polynomial) source term.

• FMM3D : Flatiron Institute Fast Multipole Libraries.

• IteratorSampling.jl : Sampling methods for arbitrary iterators.

• JustPIC.jl : Particle-in-Cell advection ready to rock the GPU.

• KSVD.jl : Highly optimized K-SVD implementation in Julia, with several parallelization techniques available..

• MixedStructTypes.jl : Pack multiple types in a single one.

• MusicTheory.jl

• OpenFHE.jl : Fully homomorphic encryption in Julia using OpenFHE.

• QuartoNotebookRunner.jl : Run Quarto notebooks containing Julia code and save the results to Jupyter notebooks..

• SIAMFANLEquations.jl : This is a Julia package of nonlinear solvers. These codes are used in book, Solving Nonlinear Equations with Iterative Methods: Solvers and Examples in Julia.

• SimpleArgParse.jl : Simple command-line argument parsing.

Vidéos¶

• Jim Pivarski - Three garbage collectors: Java, Python, and Julia

• Nils Niggemann - Testing with Julia

• Lilith Hafner - Julia’s Latest in High Performance Sorting

Tutoriels, Documentation¶

• Example Accelerating Linear Algebra PDE Semi-Discretization.

• Autogenerated package constructed using BinaryBuilder.jl.

• A tutorial on Julia DataFrames package

Abonnez-vous à la liste Julia du CNRS

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