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arXiv:1209.5145cs.PL

Julia: A Fast Dynamic Language for Technical Computing

Jeff Bezanson, Stefan Karpinski, Viral B. Shah, Alan Edelman

Abstract

Dynamic languages have become popular for scientific computing. They are generally considered highly productive, but lacking in performance. This paper presents Julia, a new dynamic language for technical computing, designed for performance from the beginning by adapting and extending modern programming language techniques. A design based on generic functions and a rich type system simultaneously enables an expressive programming model and successful type inference, leading to good performance for a wide range of programs. This makes it possible for much of the Julia library to be written in Julia itself, while also incorporating best-of-breed C and Fortran libraries.

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Journal reference
DOI
Subjects
cs.PLProgramming Languages cs.CEComputational Engineering, Finance, and Science

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Linked by 3 identifiable commenters in 6 comments across 5 threads, from Apr 2013 to Aug 2018.

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Discussed in comments5 threads

  1. Julia 1.0 2 comments

    • I was watching live stream last night from the East coast and very impressed by the achievement by you scientists and grad students since 2012. https://arxiv.org/abs/1209.5145 As a former physicist, I have been through the Numerical Recipes/F77 stage myself two decades ago. In…

      ontouchstartView on HNParent context

    • > I was watching live stream last night from the East coast and very impressed by the achievement by you scientists and grad students since 2012. https://arxiv.org/abs/1209.5145 Thank you, that's very kind of you! To be fair, Jeff, Viral, Alan and I had many collective decades…

      StefanKarpinskiView on HNParent context

  2. Musings on AOT, JIT and Language Design 1 comment

    • Between this post and others like it [1], Maxime Chevalier-Boisvert's ideas sound like they're evolving towards something very much like Julia [2], a dynamic language carefully designed to make ahead-of-time data-flow-based type analysis easy. This analysis allows Julia to…

      StefanKarpinskiView on HNParent context

  3. Julia: A fresh approach to numerical computing 1 comment

    • Despite having a very similar title, this is a rather different paper from http://arxiv.org/abs/1209.5145. We had to upload a version of this paper for a grant application, but it's still somewhat in progress.

      StefanKarpinskiView on HNParent context

  4. Show HN: I'm building an open-source, high-frequency trading system 1 comment

    • Thanks for checking Julia out. I fear there is a fair amount of misinformation in your comment, however, so it seems that a few things were lost in your reading of Julia's code (some of which is admittedly quite tricky). I hope you don't mind if I address some of it. The first…

      StefanKarpinskiView on HNParent context

  5. Videos from the Julia tutorial at MIT 1 comment

    • The language is carefully constrained so that type inference can work in the majority of the cases, allowing efficient code generation. The details are in our julia design paper here. http://arxiv.org/abs/1209.5145 Also, a number of other language features include: `ccall` to…

      ViralBShahView on HNParent context

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