KOKKOS_INLINE_FUNCTION
  int
  Gemm<Trans::ConjTranspose,Trans::NoTranspose,
       AlgoGemm::SparseSparseSuperNodes,Variant::One>
  ::invoke(PolicyType &policy,
           MemberType &member,
           const ScalarType alpha,
           CrsExecViewTypeA &A,
           CrsExecViewTypeB &B,
           const ScalarType beta,
           CrsExecViewTypeC &C) {

    if (member.team_rank() == 0) {
      DenseMatrixView<typename CrsExecViewTypeA::flat_mat_base_type> AA(A.Flat());
      DenseMatrixView<typename CrsExecViewTypeA::flat_mat_base_type> BB(B.Flat());
      DenseMatrixView<typename CrsExecViewTypeA::flat_mat_base_type> CC(C.Flat());
      
      Gemm<Trans::ConjTranspose,Trans::NoTranspose,
        AlgoGemm::ExternalBlas,Variant::One>
        ::invoke(policy, member,
                 alpha, AA, BB, beta, CC);
    }

    return 0;
  }
  KOKKOS_INLINE_FUNCTION
  int
  Gemm<Trans::ConjTranspose,Trans::NoTranspose,
       AlgoGemm::SparseSparseUnblocked,Variant::One>
  ::invoke(PolicyType &policy,
           MemberType &member,
           const ScalarType alpha,
           CrsExecViewTypeA &A,
           CrsExecViewTypeB &B,
           const ScalarType beta,
           CrsExecViewTypeC &C) {
    typedef typename CrsExecViewTypeA::ordinal_type  ordinal_type;
    typedef typename CrsExecViewTypeA::value_type    value_type;
    typedef typename CrsExecViewTypeA::row_view_type row_view_type;



    // scale the matrix C with beta
    ScaleCrsMatrix::invoke(policy, member,
                           beta, C);

    // C(i,j) += alpha*A'(i,k)*B(k,j)
    const ordinal_type mA = A.NumRows();
    for (ordinal_type k=0;k<mA;++k) {
      row_view_type &a = A.RowView(k);
      const ordinal_type nnz_a = a.NumNonZeros();

      row_view_type &b = B.RowView(k);
      const ordinal_type nnz_b = b.NumNonZeros();

      if (nnz_a > 0 && nnz_b) {
        Kokkos::parallel_for(Kokkos::TeamThreadRange(member, 0, nnz_a),
                             [&](const ordinal_type i) {
                               const ordinal_type row_at_i  = a.Col(i);
                               const value_type   val_at_ik = Util::conj(a.Value(i));

                               row_view_type &c = C.RowView(row_at_i);

                               ordinal_type idx = 0;
                               for (ordinal_type j=0;j<nnz_b && (idx > -2);++j) {
                                 const ordinal_type col_at_j  = b.Col(j);
                                 const value_type   val_at_kj = b.Value(j);

                                 idx = c.Index(col_at_j, idx);
                                 if (idx >= 0)
                                   c.Value(idx) += alpha*val_at_ik*val_at_kj;
                               }
                             });
        member.team_barrier();
      }
    }

    return 0;
  }
Пример #3
0
  KOKKOS_INLINE_FUNCTION
  int
  Gemm<Trans::ConjTranspose,Trans::NoTranspose,
       AlgoGemm::ForFactorBlocked>
  ::invoke(typename CrsExecViewTypeA::policy_type &policy,
           const typename CrsExecViewTypeA::policy_type::member_type &member,
           const ScalarType alpha,
           CrsExecViewTypeA &A,
           CrsExecViewTypeB &B,
           const ScalarType beta,
           CrsExecViewTypeC &C) {
    typedef typename CrsExecViewTypeA::ordinal_type      ordinal_type;
    typedef typename CrsExecViewTypeA::value_type        value_type;
    typedef typename CrsExecViewTypeA::row_view_type     row_view_type;
    typedef typename CrsExecViewTypeA::team_factory_type team_factory_type;

    // scale the matrix C with beta
    scaleCrsMatrix<ParallelForType>(member, beta, C);

    // C(i,j) += alpha*A'(i,k)*B(k,j)
    const ordinal_type mA = A.NumRows();
    for (ordinal_type k=0;k<mA;++k) {
      row_view_type &a = A.RowView(k);
      const ordinal_type nnz_a = a.NumNonZeros();

      row_view_type &b = B.RowView(k);
      const ordinal_type nnz_b = b.NumNonZeros();

      if (nnz_a > 0 && nnz_b) {
        ParallelForType(team_factory_type::createThreadLoopRegion(member, 0, nnz_a),
                        [&](const ordinal_type i) {
                          const ordinal_type row_at_i  = a.Col(i);
                          const value_type   val_at_ik = conj(a.Value(i));

                          row_view_type &c = C.RowView(row_at_i);

                          ordinal_type idx = 0;
                          for (ordinal_type j=0;j<nnz_b && (idx > -2);++j) {
                            const ordinal_type col_at_j  = b.Col(j);
                            const value_type   val_at_kj = b.Value(j);

                            idx = c.Index(col_at_j, idx);
                            if (idx >= 0)
                              c.Value(idx) += alpha*val_at_ik*val_at_kj;
                          }
                        });
        member.team_barrier();
      }
    }

    return 0;
  }
 inline
 Stat
 Gemm<Trans::ConjTranspose,Trans::NoTranspose,
      AlgoGemm::SparseSparseSuperNodes,Variant::One>
 ::stat(const ScalarType alpha,
        CrsExecViewTypeA &A,
        CrsExecViewTypeB &B,
        const ScalarType beta,
        CrsExecViewTypeC &C) {    
   DenseMatrixView<typename CrsExecViewTypeA::flat_mat_base_type> AA(A.Flat());
   DenseMatrixView<typename CrsExecViewTypeA::flat_mat_base_type> BB(B.Flat());
   DenseMatrixView<typename CrsExecViewTypeA::flat_mat_base_type> CC(C.Flat());
   
   return Gemm<Trans::ConjTranspose,Trans::NoTranspose,
     AlgoGemm::ExternalBlas,Variant::One>
     ::stat(alpha, AA, BB, beta, CC);
 }