int main(int argc, char **argv)
{
//Input matrix and vector declaration
double *mat, *vec;
double spectral_radius;
double start,stop;
MPI_Init(&argc,&argv);
// Determine the size of the matrix and number of iterations from the
// command line arguments.
int size = atoi(argv[1]);
int iter = atoi(argv[2]);
// Determine the rank of the current process, and the total number of processes.
int myrank,nprocs;
MPI_Comm_rank(MPI_COMM_WORLD, &myrank);
MPI_Comm_size(MPI_COMM_WORLD, &nprocs);
// Allocate memory for the matrix and the vector of appropriate size here.
mat = (double *)malloc(size*size/nprocs*sizeof(double));
vec = (double *)malloc(size*sizeof(double));
// Use process 0 for all the print statements.
if( myrank == 0)
{
printf("\nThis program generates a matrix of dimensions %d x %d and runs the powermethod\non it for %d iterations. If you are using the input matrix from the given example,\nthe result should be 6\n\n",size,size,iter);
}
// Generate matrix
generatematrix(mat,size);
//Generate a random vector
generatevec(vec,size);
// Power Method to generate the spectral radius of the matrix.
start = MPI_Wtime();
spectral_radius = powerMethod(mat,vec,size,iter);
stop = MPI_Wtime();
// Free all the variables
free(mat);
free(vec);
// Print the radius and execution time using thread 0.
// You can change the print format anyway you want.
if(myrank == 0)
{
printf("Spectral radius is : %lf\n",spectral_radius);
printf("Time in seconds : %lf\n", stop - start);
// myprintouts
}
MPI_Finalize();
}
bool testinvldlt(bool silent)
{
bool result;
ap::real_2d_array a;
ap::real_2d_array a2;
ap::real_2d_array a3;
ap::integer_1d_array p;
int n;
int pass;
int mtask;
int i;
int j;
int k;
int minij;
bool upperin;
bool cr;
double v;
double err;
bool waserrors;
int passcount;
int maxn;
int htask;
double threshold;
err = 0;
passcount = 10;
maxn = 20;
threshold = 100000*ap::machineepsilon;
waserrors = false;
//
// Test
//
for(n = 1; n <= maxn; n++)
{
a.setbounds(0, n-1, 0, n-1);
a2.setbounds(0, n-1, 0, n-1);
a3.setbounds(0, n-1, 0, n-1);
for(mtask = 2; mtask <= 2; mtask++)
{
for(htask = 0; htask <= 1; htask++)
{
for(pass = 1; pass <= passcount; pass++)
{
upperin = htask==0;
//
// Prepare task:
// * A contains symmetric matrix
// * A2, A3 contains its upper (or lower) half
//
generatematrix(a, n, mtask);
for(i = 0; i <= n-1; i++)
{
for(j = 0; j <= n-1; j++)
{
a2(i,j) = a(i,j);
a3(i,j) = a(i,j);
}
}
for(i = 0; i <= n-1; i++)
{
for(j = 0; j <= n-1; j++)
{
if( upperin )
{
if( j<i )
{
a2(i,j) = 0;
a3(i,j) = 0;
}
}
else
{
if( i<j )
{
a2(i,j) = 0;
a3(i,j) = 0;
}
}
}
}
//
// Test 1: inv(A2)
//
smatrixinverse(a2, n, upperin);
restorematrix(a2, n, upperin);
for(i = 0; i <= n-1; i++)
{
for(j = 0; j <= n-1; j++)
{
v = ap::vdotproduct(a.getrow(i, 0, n-1), a2.getcolumn(j, 0, n-1));
if( i==j )
{
v = v-1;
}
err = ap::maxreal(err, fabs(v));
}
}
//
// Test 2: inv(LDLt(A3))
//
smatrixldlt(a3, n, upperin, p);
smatrixldltinverse(a3, p, n, upperin);
restorematrix(a3, n, upperin);
for(i = 0; i <= n-1; i++)
{
for(j = 0; j <= n-1; j++)
{
v = ap::vdotproduct(a.getrow(i, 0, n-1), a3.getcolumn(j, 0, n-1));
if( i==j )
{
v = v-1;
}
err = ap::maxreal(err, fabs(v));
}
}
}
}
}
}
//
// report
//
waserrors = err>threshold;
if( !silent )
{
printf("TESTING LDLT INVERSE\n");
printf("ERROR: %5.3le\n",
double(err));
if( waserrors )
{
printf("TEST FAILED\n");
}
else
{
printf("TEST PASSED\n");
}
printf("\n\n");
}
result = !waserrors;
return result;
}
