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src/ComputeSPMV_ref.cpp

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+
+//@HEADER
+// ***************************************************
+//
+// HPCG: High Performance Conjugate Gradient Benchmark
+//
+// Contact:
+// Michael A. Heroux ( maherou@sandia.gov)
+// Jack Dongarra     (dongarra@eecs.utk.edu)
+// Piotr Luszczek    (luszczek@eecs.utk.edu)
+//
+// ***************************************************
+//@HEADER
+
+/*!
+ @file ComputeSPMV_ref.cpp
+
+ HPCG routine
+ */
+
+#include "ComputeSPMV_ref.hpp"
+
+#ifndef HPCG_NO_MPI
+#include "ExchangeHalo.hpp"
+#endif
+
+#ifndef HPCG_NO_OPENMP
+#include <omp.h>
+#endif
+#include <cassert>
+
+/*!
+  Routine to compute matrix vector product y = Ax where:
+  Precondition: First call exchange_externals to get off-processor values of x
+
+  This is the reference SPMV implementation.  It CANNOT be modified for the
+  purposes of this benchmark.
+
+  @param[in]  A the known system matrix
+  @param[in]  x the known vector
+  @param[out] y the On exit contains the result: Ax.
+
+  @return returns 0 upon success and non-zero otherwise
+
+  @see ComputeSPMV
+*/
+int ComputeSPMV_ref(const SparseMatrix& A, Vector& x, Vector& y)
+{
+
+    assert(x.localLength >= A.localNumberOfColumns); // Test vector lengths
+    assert(y.localLength >= A.localNumberOfRows);
+
+#ifndef HPCG_NO_MPI
+    ExchangeHalo(A, x);
+#endif
+    const double* const xv = x.values;
+    double* const yv = y.values;
+    const local_int_t nrow = A.localNumberOfRows;
+#ifndef HPCG_NO_OPENMP
+#pragma omp parallel for
+#endif
+    for (local_int_t i = 0; i < nrow; i++)
+    {
+        double sum = 0.0;
+        const double* const cur_vals = A.matrixValues[i];
+        const local_int_t* const cur_inds = A.mtxIndL[i];
+        const int cur_nnz = A.nonzerosInRow[i];
+
+        for (int j = 0; j < cur_nnz; j++)
+            sum += cur_vals[j] * xv[cur_inds[j]];
+        yv[i] = sum;
+    }
+    return 0;
+}