Exercise 4 for the course "Parallel and distributed systems" of THMMY in AUTH university.
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/*
* =============================================================
* spmatvec_mult.c Compute a sparse matrix vector multiplication
* using a transposed matrix.
*
* David Gleich
* Stanford University
* 14 February 2006
* =============================================================
*/
#include "mex.h"
/*
* The mex function just computes one matrix-vector product.
*
* function y = A'*x
*/
void mexFunction(int nlhs, mxArray *plhs[],
int nrhs, const mxArray *prhs[])
{
int i, j, k;
int mrows, ncols;
/* sparse matrix */
int *A_row, *A_col;
double *A_val;
double *x;
double *y;
double yval;
if (nrhs != 2)
{
mexErrMsgTxt("2 inputs required.");
}
else if (nlhs > 1)
{
mexErrMsgTxt("Too many output arguments");
}
mrows = mxGetM(prhs[0]);
ncols = mxGetN(prhs[0]);
if (!mxIsSparse(prhs[0]) ||
!mxIsDouble(prhs[0]) ||
mxIsComplex(prhs[0]))
{
mexErrMsgTxt("Input must be a noncomplex sparse matrix.");
}
/* The second input must be a vector. */
if (mxGetM(prhs[1])*mxGetN(prhs[1]) != mrows ||
mxIsSparse(prhs[1]) || !mxIsDouble(prhs[1]))
{
mexErrMsgTxt("Invalid vector 2.");
}
/* Get the sparse matrix */
A_val = mxGetPr(prhs[0]);
A_row = mxGetIr(prhs[0]);
A_col = mxGetJc(prhs[0]);
/* Get the vector x */
x = mxGetPr(prhs[1]);
plhs[0] = mxCreateDoubleMatrix(ncols,1,mxREAL);
y = mxGetPr(plhs[0]);
for (i = 0; i < ncols; i++)
{
yval = 0.0;
for (j = A_col[i]; j < A_col[i+1]; ++j)
{
yval += A_val[j]*x[A_row[j]];
}
y[i] = yval;
}
}