/usr/include/trilinos/Kokkos_CrsMatrix_MP_Vector.hpp is in libtrilinos-stokhos-dev 12.10.1-3.
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// ***********************************************************************
//
// Stokhos Package
// Copyright (2009) Sandia Corporation
//
// Under terms of Contract DE-AC04-94AL85000, there is a non-exclusive
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// modification, are permitted provided that the following conditions are
// met:
//
// 1. Redistributions of source code must retain the above copyright
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//
// 2. Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
//
// 3. Neither the name of the Corporation nor the names of the
// contributors may be used to endorse or promote products derived from
// this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY
// EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE
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// @HEADER
#ifndef KOKKOS_CRSMATRIX_MP_VECTOR_HPP
#define KOKKOS_CRSMATRIX_MP_VECTOR_HPP
#include "Sacado_MP_Vector.hpp"
#include "Kokkos_View_MP_Vector.hpp"
#include "Kokkos_Sparse.hpp"
#include "Kokkos_Blas1_MP_Vector.hpp" // for some utilities
#include "Kokkos_Core.hpp"
#include "Stokhos_Multiply.hpp"
#include "Teuchos_TestForException.hpp"
//----------------------------------------------------------------------------
// Specializations of KokkosSparse::CrsMatrix for Sacado::MP::Vector scalar type
//----------------------------------------------------------------------------
namespace Stokhos {
namespace details {
template <typename Matrix, typename InputVector, typename OutputVector,
typename Update = MultiplyAssign,
typename Enabled = void>
class MPMultiply {};
// Kernel implementing y = A * x where
// A == KokkosSparse::CrsMatrix< Sacado::MP::Vector<...>,...>,
// x, y == Kokkos::View< Sacado::MP::Vector<...>*,...>,
// x and y are rank 1, any layout
// We spell everything out here to make sure the ranks and devices match.
//
// This implementation uses overloaded operators for MP::Vector.
template <typename MatrixDevice,
typename MatrixStorage,
typename MatrixOrdinal,
typename MatrixMemory,
typename MatrixSize,
typename InputStorage,
typename ... InputP,
typename OutputStorage,
typename ... OutputP,
typename Update>
class MPMultiply< KokkosSparse::CrsMatrix< Sacado::MP::Vector<MatrixStorage>,
MatrixOrdinal,
MatrixDevice,
MatrixMemory,
MatrixSize>,
Kokkos::View< Sacado::MP::Vector<InputStorage>*,
InputP... >,
Kokkos::View< Sacado::MP::Vector<OutputStorage>*,
OutputP... >,
Update
#ifdef KOKKOS_HAVE_CUDA
, typename std::enable_if<
!std::is_same<MatrixDevice,Kokkos::Cuda>::value >::type
#endif
>
{
public:
typedef Sacado::MP::Vector<MatrixStorage> MatrixValue;
typedef Sacado::MP::Vector<InputStorage> InputVectorValue;
typedef Sacado::MP::Vector<OutputStorage> OutputVectorValue;
typedef OutputVectorValue scalar_type;
typedef MatrixDevice execution_space;
typedef typename execution_space::size_type size_type;
typedef KokkosSparse::CrsMatrix< MatrixValue,
MatrixOrdinal,
MatrixDevice,
MatrixMemory,
MatrixSize > matrix_type;
typedef Kokkos::View< InputVectorValue*,
InputP... > input_vector_type;
typedef Kokkos::View< OutputVectorValue*,
OutputP... > output_vector_type;
typedef Update update_type;
const matrix_type m_A;
const input_vector_type m_x;
const output_vector_type m_y;
const update_type m_update;
MPMultiply( const matrix_type & A,
const input_vector_type & x,
const output_vector_type & y,
const update_type& update )
: m_A( A )
, m_x( x )
, m_y( y )
, m_update( update )
{}
KOKKOS_INLINE_FUNCTION
void operator()( const size_type iRow ) const
{
// Compute mat-vec for this row
const size_type iEntryBegin = m_A.graph.row_map[iRow];
const size_type iEntryEnd = m_A.graph.row_map[iRow+1];
scalar_type sum = 0.0;
for (size_type iEntry = iEntryBegin; iEntry < iEntryEnd; ++iEntry) {
size_type iCol = m_A.graph.entries(iEntry);
sum += m_A.values(iEntry) * m_x(iCol);
}
m_update( m_y(iRow), sum );
} // operator()
static void apply( const matrix_type & A,
const input_vector_type & x,
const output_vector_type & y,
const update_type & update )
{
const size_type row_count = A.graph.row_map.dimension_0()-1;
Kokkos::parallel_for( row_count, MPMultiply(A,x,y,update) );
}
};
// Kernel implementing y = A * x where
// A == KokkosSparse::CrsMatrix< Sacado::MP::Vector<...>,...>,
// x, y == Kokkos::View< Sacado::MP::Vector<...>**,...>,
// x and y are rank 2, any layout
// We spell everything out here to make sure the ranks and devices match.
//
// This implementation uses overloaded operators for MP::Vector.
template <typename MatrixDevice,
typename MatrixStorage,
typename MatrixOrdinal,
typename MatrixMemory,
typename MatrixSize,
typename InputStorage,
typename ... InputP,
typename OutputStorage,
typename ... OutputP,
typename Update>
class MPMultiply< KokkosSparse::CrsMatrix< Sacado::MP::Vector<MatrixStorage>,
MatrixOrdinal,
MatrixDevice,
MatrixMemory,
MatrixSize >,
Kokkos::View< Sacado::MP::Vector<InputStorage>**,
InputP... >,
Kokkos::View< Sacado::MP::Vector<OutputStorage>**,
OutputP... >,
Update
#ifdef KOKKOS_HAVE_CUDA
, typename std::enable_if<
!std::is_same<MatrixDevice,Kokkos::Cuda>::value >::type
#endif
>
{
public:
typedef Sacado::MP::Vector<MatrixStorage> MatrixValue;
typedef Sacado::MP::Vector<InputStorage> InputVectorValue;
typedef Sacado::MP::Vector<OutputStorage> OutputVectorValue;
typedef OutputVectorValue scalar_type;
typedef MatrixDevice execution_space;
typedef typename execution_space::size_type size_type;
typedef KokkosSparse::CrsMatrix< MatrixValue,
MatrixOrdinal,
MatrixDevice,
MatrixMemory,
MatrixSize > matrix_type;
typedef typename matrix_type::values_type matrix_values_type;
typedef Kokkos::View< InputVectorValue**,
InputP... > input_vector_type;
typedef Kokkos::View< OutputVectorValue**,
OutputP... > output_vector_type;
typedef Update update_type;
const matrix_type m_A;
const input_vector_type m_x;
const output_vector_type m_y;
const update_type m_update;
MPMultiply( const matrix_type & A,
const input_vector_type & x,
const output_vector_type & y,
const update_type& update )
: m_A( A )
, m_x( x )
, m_y( y )
, m_update( update )
{}
KOKKOS_INLINE_FUNCTION
void operator()( const size_type iRow ) const
{
scalar_type sum;
// Loop over columns of x, y
const size_type num_col = m_y.dimension_1();
for (size_type col=0; col<num_col; ++col) {
// Compute mat-vec for this row
const size_type iEntryBegin = m_A.graph.row_map[iRow];
const size_type iEntryEnd = m_A.graph.row_map[iRow+1];
sum = 0.0;
for (size_type iEntry = iEntryBegin; iEntry < iEntryEnd; ++iEntry) {
size_type iCol = m_A.graph.entries(iEntry);
sum += m_A.values(iEntry) * m_x(iCol,col);
}
m_update( m_y(iRow,col), sum );
} // x, y column loop
} // operator()
public:
static void apply( const matrix_type & A,
const input_vector_type & x,
const output_vector_type & y,
const update_type & update )
{
const size_type row_count = A.graph.row_map.dimension_0()-1;
Kokkos::parallel_for( row_count, MPMultiply(A,x,y,update) );
}
};
} // namespace details
// Kernel implementing y = A * x where
// A == KokkosSparse::CrsMatrix< Sacado::MP::Vector<...>,...>,
// x, y == Kokkos::View< Sacado::MP::Vector<...>*,...>,
// x and y are rank 1, any layout
// We spell everything out here to make sure the ranks and devices match.
//
// This implementation uses overloaded operators for MP::Vector.
template <typename MatrixDevice,
typename MatrixStorage,
typename MatrixOrdinal,
typename MatrixMemory,
typename MatrixSize,
typename InputStorage,
typename ... InputP,
typename OutputStorage,
typename ... OutputP>
class Multiply< KokkosSparse::CrsMatrix< Sacado::MP::Vector<MatrixStorage>,
MatrixOrdinal,
MatrixDevice,
MatrixMemory,
MatrixSize >,
Kokkos::View< Sacado::MP::Vector<InputStorage>*,
InputP... >,
Kokkos::View< Sacado::MP::Vector<OutputStorage>*,
OutputP... >
>
{
public:
typedef Sacado::MP::Vector<MatrixStorage> MatrixValue;
typedef Sacado::MP::Vector<InputStorage> InputVectorValue;
typedef Sacado::MP::Vector<OutputStorage> OutputVectorValue;
typedef MatrixDevice execution_space;
typedef typename execution_space::size_type size_type;
typedef KokkosSparse::CrsMatrix< MatrixValue,
MatrixOrdinal,
MatrixDevice,
MatrixMemory,
MatrixSize > matrix_type;
typedef typename matrix_type::values_type matrix_values_type;
typedef Kokkos::View< InputVectorValue*,
InputP... > input_vector_type;
typedef Kokkos::View< OutputVectorValue*,
OutputP... > output_vector_type;
public:
static void apply( const matrix_type & A,
const input_vector_type & x,
const output_vector_type & y )
{
typedef details::MPMultiply<matrix_type,input_vector_type,output_vector_type> multiply_type;
multiply_type::apply(A,x,y,details::MultiplyAssign());
}
};
// Kernel implementing y = A * x where
// A == KokkosSparse::CrsMatrix< Sacado::MP::Vector<...>,...>,
// x, y == Kokkos::View< Sacado::MP::Vector<...>**,...>,
// x and y are rank 2, any layout
// We spell everything out here to make sure the ranks and devices match.
//
// This implementation uses overloaded operators for MP::Vector.
template <typename MatrixDevice,
typename MatrixStorage,
typename MatrixOrdinal,
typename MatrixMemory,
typename MatrixSize,
typename InputStorage,
typename ... InputP,
typename OutputStorage,
typename ... OutputP>
class Multiply< KokkosSparse::CrsMatrix< Sacado::MP::Vector<MatrixStorage>,
MatrixOrdinal,
MatrixDevice,
MatrixMemory,
MatrixSize >,
Kokkos::View< Sacado::MP::Vector<InputStorage>**,
InputP... >,
Kokkos::View< Sacado::MP::Vector<OutputStorage>**,
OutputP... >
>
{
public:
typedef Sacado::MP::Vector<MatrixStorage> MatrixValue;
typedef Sacado::MP::Vector<InputStorage> InputVectorValue;
typedef Sacado::MP::Vector<OutputStorage> OutputVectorValue;
typedef MatrixDevice execution_space;
typedef typename execution_space::size_type size_type;
typedef KokkosSparse::CrsMatrix< MatrixValue,
MatrixOrdinal,
MatrixDevice,
MatrixMemory,
MatrixSize > matrix_type;
typedef typename matrix_type::values_type matrix_values_type;
typedef Kokkos::View< InputVectorValue**,
InputP... > input_vector_type;
typedef Kokkos::View< OutputVectorValue**,
OutputP... > output_vector_type;
public:
static void apply( const matrix_type & A,
const input_vector_type & x,
const output_vector_type & y )
{
typedef details::MPMultiply<matrix_type,input_vector_type,output_vector_type> multiply_type;
multiply_type::apply(A,x,y,details::MultiplyAssign());
}
};
} // namespace Stokhos
namespace KokkosSparse {
template <typename AlphaType,
typename BetaType,
typename MatrixType,
typename InputType,
typename ... InputP,
typename OutputType,
typename ... OutputP>
typename std::enable_if<
Kokkos::is_view_mp_vector< Kokkos::View< InputType, InputP... > >::value &&
Kokkos::is_view_mp_vector< Kokkos::View< OutputType, OutputP... > >::value
>::type
spmv(
const char mode[],
const AlphaType& a,
const MatrixType& A,
const Kokkos::View< InputType, InputP... >& x,
const BetaType& b,
const Kokkos::View< OutputType, OutputP... >& y,
const RANK_ONE)
{
typedef Kokkos::View< OutputType, OutputP... > OutputVectorType;
typedef Kokkos::View< InputType, InputP... > InputVectorType;
typedef typename InputVectorType::array_type::non_const_value_type value_type;
if(mode[0]!='N') {
Kokkos::Impl::raise_error(
"Stokhos spmv not implemented for transposed or conjugated matrix-vector multiplies");
}
if (!Sacado::is_constant(a) || !Sacado::is_constant(b)) {
Kokkos::Impl::raise_error(
"MV_Multiply not implemented for non-constant a or b");
}
value_type aa = Sacado::Value<AlphaType>::eval(a);
value_type bb = Sacado::Value<BetaType>::eval(b);
if (bb == value_type(0)) {
if (aa == value_type(1)) {
// y = A*x
typedef Stokhos::details::MultiplyAssign UpdateType;
typedef Stokhos::details::MPMultiply<MatrixType,
InputVectorType,OutputVectorType,UpdateType> multiply_type;
multiply_type::apply( A, x, y, UpdateType() );
}
else {
// y = a*A*x
typedef Stokhos::details::MultiplyScaledAssign<value_type> UpdateType;
typedef Stokhos::details::MPMultiply<MatrixType,
InputVectorType,OutputVectorType,UpdateType> multiply_type;
multiply_type::apply( A, x, y, UpdateType(aa) );
}
}
else if (bb == value_type(1)) {
if (aa == value_type(1)) {
// y += A*x
typedef Stokhos::details::MultiplyUpdate UpdateType;
typedef Stokhos::details::MPMultiply<MatrixType,
InputVectorType,OutputVectorType,UpdateType> multiply_type;
multiply_type::apply( A, x, y, UpdateType() );
}
else {
// y += a*A*x
typedef Stokhos::details::MultiplyScaledUpdate<value_type> UpdateType;
typedef Stokhos::details::MPMultiply<MatrixType,
InputVectorType,OutputVectorType,UpdateType> multiply_type;
multiply_type::apply( A, x, y, UpdateType(aa) );
}
}
else {
// y = a*A*x + b*y
typedef Stokhos::details::MultiplyScaledUpdate2<value_type> UpdateType;
typedef Stokhos::details::MPMultiply<MatrixType,
InputVectorType,OutputVectorType,UpdateType> multiply_type;
multiply_type::apply( A, x, y, UpdateType(aa,bb) );
}
}
template <typename AlphaType,
typename BetaType,
typename MatrixType,
typename InputType,
typename ... InputP,
typename OutputType,
typename ... OutputP>
typename std::enable_if<
Kokkos::is_view_mp_vector< Kokkos::View< InputType, InputP... > >::value &&
Kokkos::is_view_mp_vector< Kokkos::View< OutputType, OutputP... > >::value
>::type
spmv(
const char mode[],
const AlphaType& a,
const MatrixType& A,
const Kokkos::View< InputType, InputP... >& x,
const BetaType& b,
const Kokkos::View< OutputType, OutputP... >& y,
const RANK_TWO)
{
if(mode[0]!='N') {
Kokkos::Impl::raise_error(
"Stokhos spmv not implemented for transposed or conjugated matrix-vector multiplies");
}
if (y.dimension_1() == 1) {
auto y_1D = subview(y, Kokkos::ALL(), 0);
auto x_1D = subview(x, Kokkos::ALL(), 0);
spmv(mode, a, A, x_1D, b, y_1D, RANK_ONE());
}
else {
typedef Kokkos::View< OutputType, OutputP... > OutputVectorType;
typedef Kokkos::View< InputType, InputP... > InputVectorType;
typedef typename InputVectorType::array_type::non_const_value_type value_type;
if (!Sacado::is_constant(a) || !Sacado::is_constant(b)) {
Kokkos::Impl::raise_error(
"Stokhos spmv not implemented for non-constant a or b");
}
value_type aa = Sacado::Value<AlphaType>::eval(a);
value_type bb = Sacado::Value<BetaType>::eval(b);
if (bb == value_type(0)) {
if (aa == value_type(1)) {
// y = A*x
typedef Stokhos::details::MultiplyAssign UpdateType;
typedef Stokhos::details::MPMultiply<MatrixType,
InputVectorType,OutputVectorType,UpdateType> multiply_type;
multiply_type::apply( A, x, y, UpdateType() );
}
else {
// y = a*A*x
typedef Stokhos::details::MultiplyScaledAssign<value_type> UpdateType;
typedef Stokhos::details::MPMultiply<MatrixType,
InputVectorType,OutputVectorType,UpdateType> multiply_type;
multiply_type::apply( A, x, y, UpdateType(aa) );
}
}
else if (bb == value_type(1)) {
if (aa == value_type(1)) {
// y += A*x
typedef Stokhos::details::MultiplyUpdate UpdateType;
typedef Stokhos::details::MPMultiply<MatrixType,
InputVectorType,OutputVectorType,UpdateType> multiply_type;
multiply_type::apply( A, x, y, UpdateType() );
}
else {
// y += a*A*x
typedef Stokhos::details::MultiplyScaledUpdate<value_type> UpdateType;
typedef Stokhos::details::MPMultiply<MatrixType,
InputVectorType,OutputVectorType,UpdateType> multiply_type;
multiply_type::apply( A, x, y, UpdateType(aa) );
}
}
else {
// y = a*A*x + b*y
typedef Stokhos::details::MultiplyScaledUpdate2<value_type> UpdateType;
typedef Stokhos::details::MPMultiply<MatrixType,
InputVectorType,OutputVectorType,UpdateType> multiply_type;
multiply_type::apply( A, x, y, UpdateType(aa,bb) );
}
}
}
}
#endif /* #ifndef KOKKOS_CRSMATRIX_MP_VECTOR_HPP */
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