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How Julia Goes Faster

YOW! 2014 Melbourne

Julia is well-designed; it’s fun to write and easy to learn, especially for its niche of technical computing. However, one of the biggest draws for new users is its speed. Julia was designed from the beginning to run fast without heroic implementation efforts. This has allowed it to achieve near-C speeds despite still having only a handful of full-time developers. I’ll talk about some of the key things Julia does to be fast, from aggressive specialization to best-effort type inference and beyond. I’ll show what fast Julia code looks like, discuss what makes specific features fast (e.g. multiple-dispatch), and put this all in context with Julia’s “low-magic” design philosophy.

Leah Hanson

Software Engineer


United States

Leah is currently a software engineer at Google. She spent the Spring of 2013 at Hacker School, where she started learning Julia. Since then, she has written TypeCheck.jl (the first Julia package for static type checking), and spoken about Julia at several conferences, including JuliaCon, Strange Loop, and Strata NYC.