Mathieu, All communicator creation function in the MPI 2.2 standard are collective over the original communicator. For your specific case this means all processes in the worker communicator must call the communicator creation functions.
As this is true in all cases, and as a communicator creation function can return only a communicator per rank, if you want to create overlapping communicators the communicator creation function should be called as many times as there are overlaps by all processes in the original communicator. Based on my understanding of what you did, the first MPI_Comm_split is correct. For creating the second communicator, either you replace the second call (MPI_Comm_create) by a call to MPI_Comm_split with 2 and 4 using a key=MPI_UNDEFINED, or you force all your workers to call the MPI_Comm_create the same group with 2 and 4 using MPI_GROUP_EMPTY. However, based on the description of your issues I don't think is the right solution. If you know that each worker will execute the same number of tasks, i.e., you need the exact same number of MPI_Reduce, you might want to look into the non-blocking collective proposed in MPI 3.0. Otherwise you should implement your own based on non-blocking point-to-point communications. george. On Apr 5, 2012, at 06:02 , Mathieu westphal wrote: > Hello > > I got a problem with my code, wich run some kinf of a simulator. > > I get 4 worker (aka 4 mpi process ) wich process data. > > These data aren't available at the same time, so i get another process > (Splitter) wich send chunk of data to each process in round robin. > > This work well using MPI_Send and Receive but aftet that i need to reduce all > the data. > > I hope to be able to use MPI_Reduce to reduce all data from all worker but > there is a problem : > > 1. All results data aren't available at the same time, dut to the delay from > the original data delay. > 2. I cannot wait all data to be computed, i need to proceed the reduce a soon > as possible > > So when the first and second worker have finished, i can reduce the two > results data and keep the results on the first worker. > And when the third and the fourth have finished, i can reduce these two too, > and keep results on third worker. > At last i need to reduce data from first and third worker. > > The only way to do that using MPI_Reduce is to create "communicators". > > All i want is : > > commA : contain W1 W2 > commB : contain W3 W4 > commC : contain W1 W3 > > > Let's say i've already create a communicator only for my workers > I can easily add this line in all my workers : > > > MPI_Comm_Split(workers_comm,(int)(workerId/2),rank,CommAlpha) > > If i understand well i will get an communicator on W1 and W2 wich contains W1 > and W2, and a communicator on W3 and W4 wich contains W3 and W4. Am i right? > > > But next when i try to use (only on W1 and W3): > > MPI_Create_comm(MPI_Comm workers_comm,group,commC), > > I need also to call MPI_Create_comm on W2 and W4 or it will block. Why? > > After that, i got lot of non persistent error depending of the number of > worker i want to use. > So is this allowed to create and use overlapping communicator? and if so how > to do that? > > Thanks > > Mathieu > _______________________________________________ > users mailing list > us...@open-mpi.org > http://www.open-mpi.org/mailman/listinfo.cgi/users
