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# 20170807 julia的簡單而高效資料處理

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### 20170807 julia的簡單而高效資料處理

1. 1. • • • • • • • 2
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6. 6. x = 10 function foo(x) return x^2 + 2x + 1 end for i=1:100 a = foo(i) println(a) end
7. 7. • • •
8. 8. 11
9. 9. • • • https://juliacomputing.com/case-studies/thomas-sargent.html 12
10. 10. • https://juliacomputing.com/case-studies/ny-fed.html 13
11. 11. • • • • https://juliacomputing.com/case-studies/nature.html 14
12. 12. • • https://juliacomputing.com/case-studies/ibm.html 15
13. 13. • • https://juliacomputing.com/case-studies/intel-astro.html 16
14. 14. • • • • • • • • • • • • • • • • 50
15. 15. • • • • • • • • • • • • • • • • • • • • • •
16. 16. • • • • • • • • • • https://github.com/svaksha/Julia.jl/blob/master/AI.md
17. 17. • • • • • • • • • • • • • 76
18. 18. • • @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
19. 19. • args = [i for i in 1:1000] result = pmap(heavy_work, args)
20. 20. • • future = remotecall(rand, 2, 1000, 1000) result = fetch(future)
21. 21. 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)
22. 22. • https://juliacomputing.com/press/2017/05/25/github-top-ten.html
23. 23. https://juliohm.github.io/science/where-are-the-julians/
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