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Julia: A Fresh Approach to Technical Computing

Published on Oct 13, 20141954 Views

Stefan Karpinski

TCMM 2014 - Leuven

Related categories

Machine LearningOptimization MethodsProgramming LanguagesPythonOpen-Source SoftwareMathematics

Chapter list

A Fast Dynamic Language for Technical Computing00:00
What is a “technical/numerical" language?00:23
Are C and Scheme numerical?03:57
That's funny…05:15
The “niche hypothesis”05:39
History - 107:04
History - 208:15
History - 308:24
Before we go further08:36
Matlab-like08:43
Low-level11:03
Different11:08
Why are numbers hard?13:32
Other things that scientists want ...15:47
Julia design overview16:37
Dynamic typing19:15
Two language compromise34:39
Goldilocks36:12
Collatz42:51
Cumulative Collatz43:04
Microbenchmarks43:59
Reports from the real world46:14
Simplex Benchmarks47:09
Finite element programming47:55
Finite element programming - 148:05
Finite element programming - 248:15
How does Julia go fast?48:44
Other key performance tricks50:22
But Julia isn’t really about performance52:20
Multiple dispatch52:46
Multiple dispatch in action53:26
Multiple dispatch in Ruby01:04:34
Multiple dispatch in English01:05:14