I have a demo to answer your question, but I'd like to simply add it to the
documentation on SharedArrays. May I use some of your code in writing up the
demo? (MIT license, see
https://github.com/JuliaLang/julia/blob/master/CONTRIBUTING.md#improving-documentation)
--Tim
On Thursday, July 30, 2015 05:51:24 PM thr wrote:
> Hi all,
>
> I'm implementing a basic explicit advection algorithm of the form:
>
> for t = 1:T-1
> for j = 3:n-2
> for i = 3:m-2
> q[i,j,t+1]= timestep(q[i,j,t], u[i,j,t])
> end
> end
> end
>
>
> where q is a quantity and u a velocity field.
> I'd like to parallelize this by using sharded arrays and @parallel for, I
> tried the following:
>
> const n = 500
> const m = 500
> const T = 500
>
> @everywhere function timestep(x,y)
> #return x+y
> return x+y +x+y +x+y +x+y +x+y +x+y +x+y
> end
>
> function advection_ser(q, u)
> println("==============serial=================$n x $m x $T")
> for t = 1:T-1
> for j = 3:n-2
> for i = 3:m-2
> q[i,j,t+1]= timestep(q[i,j,t], u[i,j,t])
> end
> end
> end
> return q
> end
>
> function advection_par(q,u)
> println("==============parallel=================$n x $m x $T")
> for t = 1:T-1
> @sync @parallel for j = 3:n-2
> for i = 3:m-2
> q[i,j,t+1]= timestep(q[i,j,t], u[i,j,t])
> end
> end
> end
> return q
> end
>
> q = SharedArray(Float64, (m,n,T), init=false)
> u = SharedArray(Float64, (m,n,T), init=false)
>
> @time qs = advection_ser(q,u)
> @time qp = advection_par(q,u)
>
>
>
>
> But this yields only a very moderate speed gain: the parallel version is
> about 1/3 faster than the serial version for m,n,T=500,500,500 and -p 4.
> Is there a way I can improve on this?
>
> I have also seen some weird behaviour regarding shared arrays and I'd like
> to verify that I'm not just doing it wrong before opening issues:
>
> 1. When I construct q inside of the advection function, @code_warntype
> tells me that it's handled as an 'any' and the code is much slower.
> However, typeof(q) tells me it's of type SharedArray{Float64,3} as it
> should be.
>
> 2. I'm pretty sure there's a memory hole associated with SharedArrays, for
> when I start above program over and over eventually I get a bus error and
> julia crashes. Do I have to somehow release the shared memory from the
> workers?
>
> Thanks in advance, Johannes
