On 2 Nov 2010, at 10:21, Jerome Reybert wrote: > - in my implementation, is MPI_Bcast aware that it should use shared memory > memory communication? Is data go through the network? It seems it is the case, > considering the first results. > - is there any other methods to group task by machine, OpenMPI being aware > that it is grouping task by shared memory? > - is it possible to assign a policy (in this case, a shared memory policy) to > a Bcast or a Barrier call? > - do you have any better idea for this problem? :)
Interesting stuff, two points quickly spring to mind from the above: MPI_Comm_split() is an expensive operation, sure the manual says it's low cost but it shouldn't be used inside any critical loops so be sure you are doing the Comm_Split() at startup and then re-using it as and when needed. Any blocking call into OpenMPI will poll consuming CPU cycles until the call is complete, you can mitigate against this by telling OpenMPI to aggressively call yield whilst polling which would mean that your parallel Lapack function could get the CPU resources it required. Have a look at this FAQ entry for details of the option and what you can expect it to do. http://www.open-mpi.org/faq/?category=running#force-aggressive-degraded Ashley. -- Ashley Pittman, Bath, UK. Padb - A parallel job inspection tool for cluster computing http://padb.pittman.org.uk
