Re: [julia-users] Re: Advice for parallel computing

2016-08-10 Thread Islam Badreldin 


You can also try `DistributedArrays` and `map`. Basically, you first distribute 
the array of your composite type on multiple Julia processes, then you call 
`map` on the distributed array.
See the first talk by Andreas Noack in the Parallel Computing workshop for more 
details http://youtu.be/euZkvgx0fG8
  -Islam
_
From: André Lage <prof.al...@gmail.com>
Sent: Wednesday, August 10, 2016 8:04 PM
Subject: [julia-users] Re: Advice for parallel computing
To: julia-users <julia-users@googlegroups.com>


hi Dupont,
I would first check if ParallelAccelerator.jl does what you need:
https://github.com/IntelLabs/ParallelAccelerator.jl
Best,

André Lage.
On Wednesday, July 6, 2016 at 7:26:10 AM UTC-3, Dupont wrote:Hi,

I have an array of composite type

A = Array{MyType}(N)
that have been initialized somewhere else.

Currently, I am doing this operation

for i=1:N
    doit!(A[i])
end

I would like to perform this operation in parallel (threads if possible on a 
single computer) but SharedArray does not accept composite types.

Thank you for your suggestions,

R

[julia-users] Re: Advice for parallel computing

2016-08-10 Thread André Lage 
hi Dupont,

I would first check if ParallelAccelerator.jl does what you need:

https://github.com/IntelLabs/ParallelAccelerator.jl

Best,


André Lage.

On Wednesday, July 6, 2016 at 7:26:10 AM UTC-3, Dupont wrote:
>
> Hi,
>
> I have an array of composite type
>
> A = Array{MyType}(N)
>
> that have been initialized somewhere else.
>
> Currently, I am doing this operation
>
> for i=1:N
> doit!(A[i])
> end
>
> I would like to perform this operation in parallel (threads if possible on 
> a single computer) but SharedArray does not accept composite types.
>
> Thank you for your suggestions,
>
> R
>
>