An Introduction to Julia
summary
Quick, concrete signals: Julia claims “looks like Python, feels like Lisp, runs like C” and shows it — benchmark: 10 million elements → handwritten Julia ~11 ms, SIMD/optimized ~4 ms, numpy and optimized C comparable. Tooling demonstrated includes Jupyter on JuliaBox, BenchmarkTools, PyCall/Conda, Plots (GR backend). A major deployed result is Celeste: 178 TB input → catalog of ~188 million stars and galaxies, petaflop run on ~9,000 nodes / >1M threads, produced and used successfully.
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chapters (14)
- 0:00Introduction
- 2:01Why Julia was developed
- 9:00Celeste project impact
- 13:42Setting up JuliaBox
- 15:13Julia syntax basics
- 22:39Working with strings
- 27:16Julia data structures
- 36:55Control flow basics
- 41:46Declaring functions
- 1:00:43Using Julia packages
- 1:05:47Plotting with Plots.jl
- 1:11:54Benchmarking Julia
- 1:23:07Multiple dispatch
- 1:37:16Q&A
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