Announcing composable multi-threaded parallelism in Julia

Software performance depends more and more on exploiting multiple processor cores. The free lunch from Moore’s Law is still over. Well, we here in the Julia developer community have something of a reputation for caring about performance. In pursuit of it, we have already built a lot of functionality…

Julia User & Developer Survey 2019
We conducted the first annual Julia User & Developer Survey in June, and the results were presented…
Julia将支持可组合的多线程并行机制
摩尔定律带来的免费性能提升(free lunch)几近结束, 软件性能越来越依赖于利用多个处理器核心。 Julia社区一直以对计算性能的关注而出名。 为了追求性能,我们已经为多进程、分布式编程和 GPU…
Hello @DiffEqBot
Hi! Today we all got a new member to the DiffEq family. Say hi to our own DiffEqBot - A bot which helps…
A Summer of Julia 2019
Every summer, we welcome a large group of students working on Julia and its packages via the Google…
DiffEqFlux.jl – Julia 的神經微分方程套件
在這篇文章中,我們將會展示在 Julia 中使用微分方程解算器(DiffEq solver)搭配神經網路有多麼簡單、有效而且穩定。 Neural Ordinary Differential Equations,…
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