CODEWITHSUNDEEP
parallel-processingjulia
Kira
Kira

Reputation: 343

How to write a parallel loop in julia?

I have the following Julia code and I would like to parallelize it.

using DistributedArrays

function f(x)
    return x^2;
end
y = DArray[]
@parallel for i in 1:100
    y[i] = f(i)
end
println(y)

The output is DistributedArrays.DArray[]. I would like to have the value of y as follows: y=[1,4,9,16,...,10000]

Upvotes: 15

Views: 6914

Answers (2)

HarmonicaMuse
HarmonicaMuse

Reputation: 7893

You can use n-dimensional distributed array comprehensions:

First you need to add some more processes, either local or remote:

julia> addprocs(CPU_CORES - 1);

Then you must use DistributedArrays at every one of the spawned processes:

julia> @everywhere using DistributedArrays

Finally you can use the @DArray macro, like this:

julia> x = @DArray [@show x^2 for x = 1:10];
        From worker 2:  x ^ 2 = 1
        From worker 2:  x ^ 2 = 4
        From worker 4:  x ^ 2 = 64
        From worker 2:  x ^ 2 = 9
        From worker 4:  x ^ 2 = 81
        From worker 4:  x ^ 2 = 100
        From worker 3:  x ^ 2 = 16
        From worker 3:  x ^ 2 = 25
        From worker 3:  x ^ 2 = 36
        From worker 3:  x ^ 2 = 49

You can see it does what you expect:

julia> x
10-element DistributedArrays.DArray{Int64,1,Array{Int64,1}}:
   1
   4
   9
  16
  25
  36
  49
  64
  81
 100

Remember it works with an arbitrary number of dimensions:

julia> y = @DArray [@show i + j for i = 1:3, j = 4:6];
        From worker 4:  i + j = 7
        From worker 4:  i + j = 8
        From worker 4:  i + j = 9
        From worker 2:  i + j = 5
        From worker 2:  i + j = 6
        From worker 2:  i + j = 7
        From worker 3:  i + j = 6
        From worker 3:  i + j = 7
        From worker 3:  i + j = 8

julia> y
3x3 DistributedArrays.DArray{Int64,2,Array{Int64,2}}:
 5  6  7
 6  7  8
 7  8  9

julia>

This is the most julian way to do what you intended IMHO.

We can look at macroexpand output in order to see what's going on:

Note: this output has been slightly edited for readability, T stands for:

DistributedArrays.Tuple{DistributedArrays.Vararg{DistributedArrays.UnitRange{DistributedArrays.Int}}}

julia> macroexpand(:(@DArray [i^2 for i = 1:10]))
  :(
    DistributedArrays.DArray(
      (
        #231#I::T -> begin
          [i ^ 2 for i = (1:10)[#231#I[1]]]
        end
      ),
      DistributedArrays.tuple(DistributedArrays.length(1:10))
    )
  )

Which basically is the same as manually typing:

julia> n = 10; dims = (n,);

julia> DArray(x -> [i^2 for i = (1:n)[x[1]]], dims)
10-element DistributedArrays.DArray{Any,1,Array{Any,1}}:
   1
   4
   9
  16
  25
  36
  49
  64
  81
 100

julia>

Upvotes: 14

RgrNormand
RgrNormand

Reputation: 530

Hi Kira,

I am new on Julia, but facing the same problem. Try this approach and see if it fits your needs.

function f(x)
  return x^2;
end

y=@parallel vcat for i= 1:100
 f(i);
end;

println(y)

Regards, RN

Upvotes: 3

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