an introduction to julia
TRANSCRIPT
A introduction to
Jiahao Chen MIT CSAIL
Alan EdelmanJeff Bezanson Stefan Karpinski Viral B. Shah Andreas Noack Jake Bolewski
720 contributors + package writers
https://github.com/jiahao/ijulia-notebooks
The world of557 packages, 720 authors
345 contributors to julia repo5,239 stargazers436 watchers
What’s the big deal about Julia ?
A high level languagewith C-like speed
julialang.org/benchmarks
What’s the big deal about Julia ?
Normalized average lines of code (shortest = 0, longest = 1)
Execution time (C = 1)
https://groups.google.com/d/msg/julia-users/BYRAeQJuvTw/O7VK7-vp1EEJ
fast and expressive
A simple example
It bridges the divide between computer science and computational science
What’s the big deal about Julia ?
data abstraction
performance
What if you didn’t have to choose between data abstraction and performance?
Take home message
Types helps users express scientific computations and helps the compiler specialize code for performance
methods objects
Object-oriented programming with classes
What can I do with/to a thing?
top uppay fare
lose
buyclasses are more fundamental than methods
top uppay fare
lose
buy
pay farelose
buy
OOP with classes multi-methods
What can I do with/to a thing?
top up
pay fare
lose
buy
generic function
objectsmethods
multimethods
relationships between objects and functions
Multi-methods for linear algebra
What can I do with/to a thing?
compute spectral factorization
compute singular values
compute singular values and vectors
compute eigenvalues
generic function objectsmethods
Methods can take advantage of special matrix structures
eigvals
eigfact
svdvals
svdfact
Matrix
SymTridiagonal
Bidiagonal
easy to call external C functions, e.g. CLAPACK
sstev, dstev…
So how does this help us with linear algebra?
Multi-method dispatch with generic fallbacks
Matrix operations on general rings textbook algorithm
So how does this help us with linear algebra?
Multi-method dispatch with generic fallbacks
Matrix operations on general rings
Native parallelism constructs
JuMP: a domain specific language
Iain Dunning Miles LubinMIT
Operations Research
In summary,
Types helps users express scientific computations and helps the compiler specialize code for performance
Other advanced features for performance: code generation, native parallel computing, …
try it today! juliabox.org
JuliaCon - June 24-28 at MIT juliacon.org
Pure-‐Julia FFT performance
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spee
d (m
flops
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intel-mkl-dfti in-placeintel-mkl-dfti out-of-placefftw3 out-of-placefftw3 in-placefftw3-no-simd out-of-placefftw3-no-simd in-placedfftpackemayerjuliabloodworthcrosscwplibesrfft
double-precision complex, 1d transformspowers of two
already comparable to FFTPACK
[ actually was even a bit better; some recent inlining regressions in Julia snapshots ]
Steven Johnson, 2014-06 Presented at NAIS Codegen workshop