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#include <stdioh> #include <mpih> // Update a distributed field with a local N by N block on each process // (held in the array U) The point of this example is to show // communication overlapped with computation, so code for other // functions is not included #define N 100 // size of an edge in the square field void extern initialize(int, double*); void extern extract_boundary(int, double*, double*); void extern update_interior(int, double*); void extern update_edge(int,double*, double*); int main(int argc, char **argv) { double *U, *B, *inB; int i, num_procs, ID, left, right, Nsteps = 100; MPI_Status status; MPI_Request req_recv, req_send; // Initialize the MPI environment MPI_Init(&argc,&argv); MPI_Comm_rank(MPI_COMM_WORLD, &ID); MPI_Comm_size(MPI_COMM_WORLD, &num_procs); // allocate space for the field (U), and the buffers // to send and receive the edges (B, inB) U = (double*)malloc(N*N * sizeof(double)); B = (double*)malloc(N * sizeof(double)); inB = (double*)malloc(N * sizeof(double)); // Initialize the field and set up a ring communication pattern initialize (N, U); right = ID + 1; if (right > (num_procs-1)) right = 0; left = ID - 1; if (left < 0 ) left = num_procs-1; // Iteratively update the field U for(i=0; i<Nsteps; i++){ MPI_Irecv(inB, N, MPI_DOUBLE, left, i, MPI_COMM_WORLD, &req_recv); extract_boundary(N, U, B); //Copy the edge of U into B MPI_Isend(B, N, MPI_DOUBLE, right, i, MPI_COMM_WORLD, &req_send); update_interior(N, U); MPI_Wait(&req_recv, &status); MPI_Wait(&req_send, &status); update_edge(ID, inB, U); } MPI_Finalize(); }
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The function returns as soon as the system sets up resources to hold the message incoming from the left The handle req_recv provides a mechanism to inquire about the status of the communication The edge of the field is then extracted and sent to the neighbor on the right:
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MPI_Isend(B, N, MPI_DOUBLE, right, i, MPI_COMM_WORLD, &req_send);
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While the communication is taking place, the program updates the interior of the field (the interior refers to that part of the update that does not require edge information from the neighboring processes) After that work is complete, each process must wait until the communication is complete
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MPI_Wait(&req_send, &status); MPI_Wait(&req_recv, &status);
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at which point, the field edges are updated and the program continues to the next iteration Another technique for reducing parallel overhead in an MPI program is persistent communication This approach is used when a problem is dominated by repeated use of a communication pattern The idea is to set up the communication once and then use it multiple times to pass the actual messages The functions used in persistent communication are
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MPI_Send_init(outbuff, count, MPI_type, dest, tag, MPI_COMM, &request); MPI_Recv_init(inbuff, count, MPI_type, src, tag, MPI_COMM, &request); MPI_Start(&request); MPI_Wait(&request, &status);
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MPI_Send_init and MPI_Recv_init are called to set up the communication A request handle is returned to manipulate the actual communication events The communication is initiated with a call to MPI_Start, at which point, the process is free to continue with any computation When no further work can be done until the communication is complete, the processes can wait on a call to MPI_Wait A function using persistent communication for the ring communication pattern used in Fig B8 is shown in Fig B11 In addition to nonblocking and persistent communication, MPI defines several communication modes corresponding to different ways the sends work with the communication buffers:
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Standard mode (MPI_Send) The standard MPI send; the send will not complete until the send buffer is empty and ready to reuse Synchronous mode (MPI_Ssend) The send does not complete until after a matching receive has been posted This makes it possible to use the communication as a pairwise synchronization event Buffered mode (MPI_Bsend) User supplied buffer space is used to buffer the messages The send will complete as soon as the send buffer is copied to the system buffer
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