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#include <math.h>
#include <iostream>
#include "ml_include.h"
#ifdef ML_MPI
#include "mpi.h"
#endif
extern int Poisson_getrow(ML_Operator* mat_in, int N_requested_rows, int requested_rows[],
int allocated_space, int columns[], double values[], int row_lengths[]);
extern int Poisson_matvec(ML_Operator* mat_in, int in_length, double p[], int out_length,
double ap[]);
extern int Poisson_comm(double x[], void* A_data);
extern int send_msg(char* send_buffer, int length, int neighbor);
extern int recv_msg(char* recv_buffer, int length, int neighbor, USR_REQ* request);
extern int post_msg(char* recv_buffer, int length, int neighbor, USR_REQ* request);
int main(int argc, char* argv[]) {
ML* ml_object;
int i, N_grids = 3, N_levels;
double sol[5], rhs[5];
ML_Aggregate* agg_object;
int proc, nlocal, nlocal_allcolumns;
MPI_Init(&argc, &argv);
ML_Set_PrintLevel(15);
for (i = 0; i < 5; i++) sol[i] = 0.;
for (i = 0; i < 5; i++) rhs[i] = 2.;
ML_Create(&ml_object, N_grids);
proc = ml_object->comm->ML_mypid;
std::cout << "num_procs" << proc << std::endl;
if (ml_object->comm->ML_nprocs != 2) {
if (proc == 0) printf("Must be run on two processors\n");
ML_Destroy(&ml_object);
MPI_Finalize();
exit(1);
}
if (proc == 0) { nlocal = 2; nlocal_allcolumns = 4; }
else if (proc == 1) { nlocal = 3; nlocal_allcolumns = 5; }
else { nlocal = 0; nlocal_allcolumns = 0; }
ML_Init_Amatrix(ml_object, 0, nlocal, nlocal, &proc);
ML_Set_Amatrix_Getrow(ml_object, 0, Poisson_getrow, Poisson_comm,
nlocal_allcolumns);
ML_Set_Amatrix_Matvec(ml_object, 0, Poisson_matvec);
ML_Aggregate_Create(&agg_object);
ML_Aggregate_Set_MaxCoarseSize(agg_object, 1);
N_levels = ML_Gen_MGHierarchy_UsingAggregation(ml_object, 0,
ML_INCREASING, agg_object);
ML_Gen_Smoother_Jacobi(ml_object, ML_ALL_LEVELS, ML_PRESMOOTHER, 1, ML_DEFAULT);
ML_Gen_Solver(ml_object, ML_MGV, 0, N_levels - 1);
ML_Iterate(ml_object, sol, rhs);
if (proc == 0) {
printf("sol(0) = %e\n", sol[1]);
fflush(stdout);
}
ML_Comm_GsumInt(ml_object->comm, 1); /* just used for synchronization */
if (proc == 1) {
printf("sol(1) = %e\n", sol[0]);
printf("sol(2) = %e\n", sol[1]);
printf("sol(3) = %e\n", sol[2]);
fflush(stdout);
}
ML_Comm_GsumInt(ml_object->comm, 1); /* just used for synchronization */
if (proc == 0) {
printf("sol(4) = %e\n", sol[0]);
fflush(stdout);
}
ML_Aggregate_Destroy(&agg_object);
ML_Destroy(&ml_object);
#ifdef ML_MPI
MPI_Finalize();
#endif
exit(EXIT_SUCCESS);
}
/* Application specific getrow. */
int Poisson_getrow(ML_Operator* mat_in, int N_requested_rows, int requested_rows[],
int allocated_space, int cols[], double values[], int row_lengths[])
{
int m = 0, i, row, proc, * itemp, start;
itemp = (int*)ML_Get_MyGetrowData(mat_in);
proc = *itemp;
for (i = 0; i < N_requested_rows; i++) {
row = requested_rows[i];
if (allocated_space < m + 3) return(0);
values[m] = 2; values[m + 1] = -1; values[m + 2] = -1;
start = m;
if (proc == 0) {
if (row == 0) { cols[m++] = 0; cols[m++] = 2; }
if (row == 1) { cols[m++] = 1; cols[m++] = 3; }
}
if (proc == 1) {
if (row == 0) { cols[m++] = 0; cols[m++] = 1; cols[m++] = 4; }
if (row == 1) { cols[m++] = 1; cols[m++] = 0; cols[m++] = 2; }
if (row == 2) { cols[m++] = 2; cols[m++] = 1; cols[m++] = 3; }
}
row_lengths[i] = m - start;
}
return(1);
}
/* Application specific matrix-vector product. */
int Poisson_matvec(ML_Operator* mat_in, int in_length, double p[], int out_length,
double ap[])
{
int i, proc, * itemp;
double new_p[5];
itemp = (int*)ML_Get_MyMatvecData(mat_in);
proc = *itemp;
for (i = 0; i < in_length; i++) new_p[i] = p[i];
Poisson_comm(new_p, &proc);
for (i = 0; i < out_length; i++) ap[i] = 2. * new_p[i];
if (proc == 0) {
ap[0] -= new_p[2];
ap[1] -= new_p[3];
}
if (proc == 1) {
ap[0] -= new_p[1]; ap[0] -= new_p[4];
ap[1] -= new_p[2]; ap[1] -= new_p[0];
ap[2] -= new_p[3]; ap[2] -= new_p[1];
}
return 0;
}
/* Communication routine that should be performed before doing a matvec */
/* See ML Guide. */
int Poisson_comm(double x[], void* A_data)
{
int proc, neighbor, length, * itemp;
double send_buffer[2], recv_buffer[2];
MPI_Request request;
itemp = (int*)A_data;
proc = *itemp;
length = 2;
if (proc == 0) {
neighbor = 1;
send_buffer[0] = x[0]; send_buffer[1] = x[1];
post_msg((char*)recv_buffer, length, neighbor, &request);
send_msg((char*)send_buffer, length, neighbor);
recv_msg((char*)recv_buffer, length, neighbor, &request);
x[2] = recv_buffer[1]; x[3] = recv_buffer[0];
}
else {
neighbor = 0;
send_buffer[0] = x[0]; send_buffer[1] = x[2];
post_msg((char*)recv_buffer, length, neighbor, &request);
send_msg((char*)send_buffer, length, neighbor);
recv_msg((char*)recv_buffer, length, neighbor, &request);
x[3] = recv_buffer[1]; x[4] = recv_buffer[0];
}
return 0;
}
/* Simple communication wrappers for use with MPI */
int send_msg(char* send_buffer, int length, int neighbor)
{
ML_Comm_Send(send_buffer, length * sizeof(double), neighbor, 123,
MPI_COMM_WORLD);
return 0;
}
int recv_msg(char* recv_buffer, int length, int neighbor, USR_REQ* request)
{
MPI_Status status;
MPI_Wait(request, &status);
return 0;
}
int post_msg(char* recv_buffer, int length, int neighbor, USR_REQ* request)
{
int type = 123;
ML_Comm_Irecv(recv_buffer, length * sizeof(double), &neighbor,
&type, MPI_COMM_WORLD, request);
return 0;
}
//#else
//int main(int argc, char* argv[])
//{
// printf("In order to use this example, you must configure with the option\n--with-mpi-compilers=full_path_to_your_mpi_compilers and recompile.\n");
// /* returns ok not to break the test harness */
// return(EXIT_SUCCESS);
//}
//#endif /* ifdef ML_MPI */
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