Julia

https://github.com/sumiya11/Groebner.jl claims quite fast

LiftedTrajectoryGames

bare metal julia arduino

println("hello world")
using Plots
using JuMP
using LinearAlgebra
x = [1,2,3,5]
print(x)
using Metatheory

hmm if I want julia to work good, I need to make a command that is valid julia but also valid bash

#= =# multiline julia is not a bash comment

#= 
bash code julia won't run
# =# julia code bash won't run

#= 
julia
# =# julia code bash won't run

"julia": "#=\njulia\n# =#\ninclude($dir * \"$fileName\")",

Yes, that’s right, Mr. Vice President. I am a genius.

packagecompiler make sys images so that packages load faster

Metaheuristics.jl

If you want just linear problems, you can also try Tulip (this is me self-advertising; I wrote it). It’s pure Julia, and should give you decent performance. If you want nonlinear problems, among the open-source pure Julia solvers, you have: COSMO, which supports several cones & quadratic objective. It’s based on ADMM, same as SCS/OSQP Hypatia, which supports the largest variety of cones (especially the ones you’ve never heard of). It’s based on interior-point, same as ECOS/Mosek. For LP and convex QP, there is also https://github.com/JuliaSmoothOptimizers/RipQP.jl

JuliaSmoothOptimizers https://www.youtube.com/watch?v=FsQJ6NEUF6g&ab_channel=TheJuliaProgrammingLanguage

• Fellisson course Nice description of expression problem and multiple dispatch
• Rackauckas comments on paper about julia types
• Gotchas
• Type Stability in Julia: Avoiding Performance Pathologies in JIT Compilation (Extended Version)
• World Age in Julia: Optimizing Method Dispatch in the Presence of Eval (Extended Version)
• Keno describing his lens AD thing diffractor
• What scientists must know about hardware to write fast code Interesting topics:
• World Age
• Multiple dispatch
• Subtyping and most specific type
• Max_methods = 1 as a good default?
• Type ambiguity?
• Function barriers

Runtimegeneratedfunctions.jl

Evan’s new talk. Seems really cool. Categories for multiphysics?

Interesting project ideas:

• PyRes translation
• That prolog engine
• SMT modulo Convex
• Interactive Proofs
• probabilistic games use homotopy continuation
• Guarded rewrite rules
• Constraint programming compilation
• CHC from SSA
• WP
• anyon
• linear relations / modules

Scientific Computing in Julia. Numerical Computing in Julia HPC in Julia Data Science in Julia Deep Learning in Julia Algorithm Design in Julia Physics for Programmers

Audience: Someone at my level or higher? People who do scientific computing? At labs? Engineers? Grad students? Hobbyists?

End Expectations: ? No one actually reads books

that optimization book in julia

Strang Book

Fluid Solver Wave Solver Fitting Data - An Inverse Problem Particle simulation Convnet ODE and PDE

Function Breaks, Type Stability Examining Code, llvm and native Fast Loops SIMD Parallelism GPU DSLs Partial Evaluation / Macros. generative functions Dispatch - Fast matrix overloading

Minimal: you can activate a environment.

From a julia repl, you can press ] to put it into Pkg mode

<code>pkg> activate .</code>

Revise.jl - You can use Revise.jl. If you’re editting a one off file, you can bring it into the repl with includet so that it automatically reloads anytime you change the file.

<code>julia> using Revise
julia> includet("myfile.jl")
julia> myfunction(7)
</code>

You should take a gander

https://docs.julialang.org/en/v1/stdlib/Pkg/

https://julialang.github.io/Pkg.jl/v1/

https://github.com/invenia/PkgTemplates.jl https://invenia.github.io/PkgTemplates.jl/stable/user/

This is how you get those slick little badges for documentation and

https://www.youtube.com/watch?v=QVmU29rCjaA&t=1157s&ab_channel=TheJuliaProgrammingLanguage

Unit testing. I don’t write tests for my code often enough, I know it’s a good thing to do. Here’s how you do it.

<code>using MyPkg
using Test

@testset "MyPkg.jl" begin
    # Write your tests here.
    @test true
    @test MyPkg.foo(2) == 4
end</code>


<code>pkg> test MyPkg</code>