Hi all, I am working on parallelization of a Data Clustering Algorithm in which I am following MPMD pattern of MPI (i.e. 1 master process and p slave processes in same communicator). It is an iterative algorithm where 2 loops inside iteration are separately parallelized.
The first loop is parallelized by partitioning the N size input data into (almost) equal parts between p slaves. Each slave produces a contiguous chunk of about (p * N/p) double values as result of its local processing. This local chunk from each slave is collected back on master process where it is merged with chunks from other slaves. If a blocking call (MPI_Send / Recv) is put in a loop on master such that it receives the data one by one in order of their rank from slaves, then each slave takes about 75 seconds for its local computation (as calculated by MPI_Wtime() ) and about 1.5 seconds for transferring its chunk to master. But, as the transfer happens in order, by the time last slave process is done, the total time becomes 75 seconds for computation and 50 seconds for communication. These timings are for a cluster of 31 machines where a single process executes in each machine. All these machines are connected directly via a private Gigabit network switch. In order to be effectively parallelize the algorithm, the overall execution time needs to come below 80 seconds. I have tried following strategies to solve this problem: 0. Ordered transfer, as explained above. 1. Collecting data through MPI_Gatherv and assuming that internally it will transfer data in parallel. 2. Creating p threads at master using OpenMP and calling MPI_Recv (or MPI_Irecv with MPI_Wait) by threads. The received data by each process is put in a separate buffer. My installation support MPI_THREAD_MULTIPLE. The problem is that strategies 1 & 2 are taking almost similar time as compared to strategy 0. *Is there a way through which I can receive data in parallel and substantially decrease the overall execution time?* Hoping to get your help soon. Sorry for the long question. Regards, Saiyedul Islam PS: Specifications of the cluster: GCC 5.10, OpenMP 2.0.1, CentOS 6.5 (as part of Rockscluster).
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