1 / 11

PP Lab

PP Lab. MPI programming VI. Program 1. Break up a long vector into subvectors of equal length. Distribute subvectors to processes. Let them compute the partial sums. Collect the partial sums from the processes and add them, to deliver the final sum to the user. Functions to be used.

amanda
Download Presentation

PP Lab

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. PP Lab MPI programming VI

  2. Program 1 Break up a long vector into subvectors of equal length. Distribute subvectors to processes. Let them compute the partial sums. Collect the partial sums from the processes and add them, to deliver the final sum to the user.

  3. Functions to be used • MPI_Reduce: Reduces values on all processes to a single value • Synopsis #include "mpi.h" int MPI_Reduce ( void *sendbuf, void *recvbuf, int count, MPI_Datatype datatype, MPI_Op op, int root, MPI_Comm comm ) • Input Parameters: • sendbuf: address of send buffer • count: number of elements in send buffer • datatype: data type of elements of send buffer • op: reduce operation • root: rank of root process • comm: communicator • Output Parameter: • recvbuf: address of receive buffer (significant only at root)

  4. Reduction Operations

  5. Functions to be used • MPI_Scatter: Sends data from one task to all other tasks in a group. • Synopsis: #include "mpi.h" int MPI_Scatter ( void *sendbuf, int sendcnt, MPI_Datatype sendtype, void *recvbuf, int recvcnt, MPI_Datatype recvtype, int root, MPI_Comm comm ) • Input Parameters: • sendbuf: address of send buffer • sendcount: number of elements sent to each process • sendtype: data type of send buffer elements the above three arguments are significant only at root. • recvcount: number of elements in receive buffer • recvtype: data type of receive buffer elements • root: rank of sending process • comm: communicator • Output Parameter: • recvbuf: address of receive buffer

  6. Code #include <mpi.h> #include <stdio.h> main (int argc,char *argv[]){ int i, rank, b[3], psum, tsum; int a[9]={1,2,3,4,5,6,7,8,9}; MPI_Init (&argc,&argv); MPI_Comm_rank (MPI_COMM_WORLD, &rank); MPI_Scatter (a, 3, MPI_INT, b, 3, MPI_INT, 0, MPI_COMM_WORLD); psum=0; for(i=0;i<3;i++) psum+=b[i]; MPI_Reduce (&psum, &tsum, 1, MPI_INT, MPI_SUM, 0, MPI_COMM_WORLD); If(rank==0) printf (“sum of the vector is %d\n”,tsum); MPI_Finalize();}

  7. Program 2 Execute the prefix sum problem on 8 processes. s0=x0 s1=x0+x1=s0+x1 s2=x0+x1+x2=s1+x2 s3=x0+x1+x2+x3=s2+x3 … s7=x0+x1+x2+…+x7=s6+x7

  8. Function to be used • MPI_Scan: Computes the scan (partial reductions) of data on a collection of processes • Synopsis: #include "mpi.h" int MPI_Scan (void *sendbuf, void *recvbuf, int count, MPI_Datatype datatype, MPI_Op op, MPI_Comm comm) • Input Parameters • sendbuf: starting address of send buffer • count: number of elements in input buffer • datatype: data type of elements of input buffer • op: operation • comm: communicator • Output Parameter: • recvbuf: starting address of receive buffer

  9. 0 3 4 7 1 2 5 6 0 1 2 3 4 5 6 7 0 3 4 7 1 2 5 6 1 3 6 0 10 15 21 28

  10. Code #include <mpi.h> #include <stdio.h> main(int argc, char**argv){ int id, a, b; MPI_Init(&argc,&argv); MPI_Comm_rank (MPI_COMM_WORLD, &id); a=id; MPI_Scan (&a, &b, 1, MPI_INT, MPI_SUM, MPI_COMM_WORLD); printf (“process=%d\tprefix sum=%d\n”,id, b); MPI_Finalize ();}

  11. Assignment • Write and explain the argument lists of the following and say how they are different from the two functions you have seen: • MPI_Allreduce • MPI_Reduce_scatter

More Related