28 Numerics library [numerics]

28.9 Basic linear algebra algorithms [linalg]

28.9.14 BLAS 2 algorithms [linalg.algs.blas2]

28.9.14.1 General matrix-vector product [linalg.algs.blas2.gemv]

[Note 1: 
These functions correspond to the BLAS function xGEMV.
— end note]
The following elements apply to all functions in [linalg.algs.blas2.gemv].
Mandates:
  • possibly-multipliable<decltype(A), decltype(x), decltype(y)>() is true, and
  • possibly-addable<decltype(x), decltype(y), decltype(z)>() is true for those overloads that take a z parameter.
Preconditions:
  • multipliable(A,x,y) is true, and
  • addable(x,y,z) is true for those overloads that take a z parameter.
Complexity: .
template<in-matrix InMat, in-vector InVec, out-vector OutVec> void matrix_vector_product(InMat A, InVec x, OutVec y); template<class ExecutionPolicy, in-matrix InMat, in-vector InVec, out-vector OutVec> void matrix_vector_product(ExecutionPolicy&& exec, InMat A, InVec x, OutVec y);
These functions perform an overwriting matrix-vector product.
Effects: Computes .
[Example 1: constexpr size_t num_rows = 5; constexpr size_t num_cols = 6; // y = 3.0 * A * x void scaled_matvec_1(mdspan<double, extents<size_t, num_rows, num_cols>> A, mdspan<double, extents<size_t, num_cols>> x, mdspan<double, extents<size_t, num_rows>> y) { matrix_vector_product(scaled(3.0, A), x, y); } // z = 7.0 times the transpose of A, times y void scaled_transposed_matvec(mdspan<double, extents<size_t, num_rows, num_cols>> A, mdspan<double, extents<size_t, num_rows>> y, mdspan<double, extents<size_t, num_cols>> z) { matrix_vector_product(scaled(7.0, transposed(A)), y, z); } — end example]
template<in-matrix InMat, in-vector InVec1, in-vector InVec2, out-vector OutVec> void matrix_vector_product(InMat A, InVec1 x, InVec2 y, OutVec z); template<class ExecutionPolicy, in-matrix InMat, in-vector InVec1, in-vector InVec2, out-vector OutVec> void matrix_vector_product(ExecutionPolicy&& exec, InMat A, InVec1 x, InVec2 y, OutVec z);
These functions performs an updating matrix-vector product.
Effects: Computes .
Remarks: z may alias y.
[Example 2: // y = 3.0 * A * x + 2.0 * y void scaled_matvec_2(mdspan<double, extents<size_t, num_rows, num_cols>> A, mdspan<double, extents<size_t, num_cols>> x, mdspan<double, extents<size_t, num_rows>> y) { matrix_vector_product(scaled(3.0, A), x, scaled(2.0, y), y); } — end example]