HPC_sparsemv.cpp

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//               HPCCG: Simple Conjugate Gradient Benchmark Code
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/////////////////////////////////////////////////////////////////////////

// Routine to compute matrix vector product y = Ax where:
// First call exchange_externals to get off-processor values of x

// A - known matrix 
// x - known vector
// y - On exit contains Ax.

/////////////////////////////////////////////////////////////////////////

#include <iostream>
using std::cout;
using std::cerr;
using std::endl;
#include <cstdio>
#include <cstdlib>
#include <cctype>
#include <cassert>
#include <string>
#include <cmath>
#include "HPC_sparsemv.hpp"

#if defined(USE_ARMPL)
#include <armpl.h>
#define LIBRARY_NAME "ArmPL"
#endif

int HPC_sparsemv( HPC_Sparse_Matrix *A, 
		 const double * const x, double * const y)
{

  const int nrow = (const int) A->local_nrow;

#if defined(USE_ARMPL)
  double alpha = 1.0, beta = 0.0;
  armpl_status_t info = armpl_spmv_exec_d(ARMPL_SPARSE_OPERATION_NOTRANS, alpha, A->mat_armpl, x, beta, y);
	if (info!=ARMPL_STATUS_SUCCESS) 
  {
    cerr << "ERROR: armpl_spmv_exec_d returned %d\n";
    exit(1);
  }

#else
#ifdef USING_OMP
#pragma omp parallel for
#endif
  for (int i=0; i< nrow; i++)
    {
      double sum = 0.0;
      const double * const cur_vals = 
     (const double * const) A->ptr_to_vals_in_row[i];

      const int    * const cur_inds = 
     (const int    * const) A->ptr_to_inds_in_row[i];

      const int cur_nnz = (const int) A->nnz_in_row[i];

      for (int j=0; j< cur_nnz; j++)
          sum += cur_vals[j]*x[cur_inds[j]];
      y[i] = sum;
    }
#endif
  return(0);
}