This document provides links to case studies and examples of how Julia is being used for various applications such as economics modeling, financial modeling, scientific computing, and more. It also provides examples of how to perform parallel and distributed computing in Julia using features like @parallel, pmap, remotecall, and spawn.

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8. x = 10
function foo(x)
return x^2 + 2x + 1
end
for i=1:100
a = foo(i)
println(a)
end

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https://juliacomputing.com/case-studies/thomas-sargent.html 12

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https://juliacomputing.com/case-studies/ny-fed.html 13

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https://juliacomputing.com/case-studies/nature.html 14

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https://juliacomputing.com/case-studies/ibm.html 15

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https://juliacomputing.com/case-studies/intel-astro.html 16

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50

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https://github.com/svaksha/Julia.jl/blob/master/AI.md

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@parallel for i in 1:10000
# do something
end
result = @parallel (+) for i in 1:10000
y = f(i)
y
end
results = @parallel (vcat) for i in 1:10000
y = f(i)
[y]
end

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args = [i for i in 1:1000]
result = pmap(heavy_work, args)

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future = remotecall(rand, 2, 1000, 1000)
result = fetch(future)

79. future = @spawnat 2 rand(1000, 1000)
result = fetch(future)
future = @spawn rand(1000, 1000)
result = fetch(future)
future = remotecall(rand, 2, 1000, 1000)
result = fetch(future)

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https://juliacomputing.com/press/2017/05/25/github-top-ten.html

84. https://juliohm.github.io/science/where-are-the-julians/

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