Hello Vijay,
Thank you for your fast reply.
I have implemented the code that you send me, but I have yet another
problem. Because, regardless of the number of threads that I have in each
place (X10_NTHERADS), the first async task (with the parallel function)
ends first than the async task with the kill variable update. Then, the
algorithm always waits for the end in all places.
I guess that is how the x10 activities scheduler works, unfortunately with
this behavior I don't have any speedup with the parallelism.
Is there a way for this part of the code creates a priority async task?
for (p in Place.places() if (home.id != p.id) at(p) async
root().killed=true;
Regards,
Danny Múnera
On Tue, Apr 2, 2013 at 1:04 PM, Vijay Saraswat <vi...@saraswat.org> wrote:
> On 4/2/13 5:06 AM, Danny Munera wrote:
>
> Hello all,
>
> I’m trying to implement an algorithm in parallel. The idea is using each
> place as an algorithm independent instance, then, finishing the program
> when the first place reaches the solution. So far, I have something like
> this:
>
> finish for (p in Place.places()) at(p)async{
> sol = parallel_function();
> //kill other places
> }
>
> Currently, I don’t have any idea about how to kill the other place, I
> have searched in x10 tutorials, language specification and the API, and I
> have not found anything.
>
> Do you have any idea to how to do that?
>
>
> You don't "kill" a place, you kill the activities running at a place.
> Have them periodically check for a variable being set. e.g.
>
> class C {
> var killed:Boolean=false;
>
> static def compute() {
> val roots= PlaceLocalHandle.make[C](Dist.makeUnique(), ()=> new C());
>
> finish for (p in Place.places()) at(p)async{
> sol = roots().parallel_function();
> val home =here;
> for (p in Place.places() if (home.id != p.id) at(p) async
> root().killed=true;
> }
> }
> def parallel_function() {
> while (! killed) continueComputing();
> // store the result of computing in state on C, now retrieve it
> return result();
> }
> }
>
>
>
>
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