/usr/include/viennacl/linalg/spai.hpp is in libviennacl-dev 1.7.1+dfsg1-2.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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#define VIENNACL_LINALG_SPAI_HPP
/* =========================================================================
Copyright (c) 2010-2016, Institute for Microelectronics,
Institute for Analysis and Scientific Computing,
TU Wien.
Portions of this software are copyright by UChicago Argonne, LLC.
-----------------
ViennaCL - The Vienna Computing Library
-----------------
Project Head: Karl Rupp rupp@iue.tuwien.ac.at
(A list of authors and contributors can be found in the manual)
License: MIT (X11), see file LICENSE in the base directory
============================================================================= */
/** @file viennacl/linalg/spai.hpp
@brief Main include file for the sparse approximate inverse preconditioner family (SPAI and FSPAI). Experimental.
Most implementation contributed by Nikolay Lukash.
*/
#include <utility>
#include <iostream>
#include <fstream>
#include <string>
#include <algorithm>
#include <vector>
#include <math.h>
#include <map>
// ViennaCL includes
#include "viennacl/linalg/detail/spai/spai_tag.hpp"
#include "viennacl/linalg/qr.hpp"
#include "viennacl/linalg/prod.hpp"
#include "viennacl/linalg/detail/spai/spai-dynamic.hpp"
#include "viennacl/linalg/detail/spai/spai-static.hpp"
#include "viennacl/linalg/detail/spai/sparse_vector.hpp"
#include "viennacl/linalg/detail/spai/block_matrix.hpp"
#include "viennacl/linalg/detail/spai/block_vector.hpp"
#include "viennacl/linalg/detail/spai/fspai.hpp"
#include "viennacl/linalg/detail/spai/spai.hpp"
//boost includes
#include "boost/numeric/ublas/vector.hpp"
#include "boost/numeric/ublas/matrix.hpp"
#include "boost/numeric/ublas/matrix_proxy.hpp"
#include "boost/numeric/ublas/vector_proxy.hpp"
#include "boost/numeric/ublas/storage.hpp"
#include "boost/numeric/ublas/io.hpp"
#include "boost/numeric/ublas/lu.hpp"
#include "boost/numeric/ublas/triangular.hpp"
#include "boost/numeric/ublas/matrix_expression.hpp"
namespace viennacl
{
namespace linalg
{
typedef viennacl::linalg::detail::spai::spai_tag spai_tag;
typedef viennacl::linalg::detail::spai::fspai_tag fspai_tag;
/** @brief Implementation of the SParse Approximate Inverse Algorithm for a generic, uBLAS-compatible matrix type.
* @param Matrix matrix that is used for computations
* @param Vector vector that is used for computations
*/
//UBLAS version
template<typename MatrixType>
class spai_precond
{
public:
typedef typename MatrixType::value_type ScalarType;
typedef typename boost::numeric::ublas::vector<ScalarType> VectorType;
/** @brief Constructor
* @param A matrix whose approximate inverse is calculated. Must be quadratic.
* @param tag spai tag
*/
spai_precond(const MatrixType& A,
const spai_tag& tag): tag_(tag){
//VCLMatrixType vcl_Ap((unsigned int)A.size2(), (unsigned int)A.size1()), vcl_A((unsigned int)A.size1(), (unsigned int)A.size2()),
//vcl_At((unsigned int)A.size1(), (unsigned int)A.size2());
//UBLASDenseMatrixType dA = A;
MatrixType pA(A.size1(), A.size2());
MatrixType At;
//std::cout<<A<<std::endl;
if (!tag_.getIsRight()){
viennacl::linalg::detail::spai::sparse_transpose(A, At);
}else{
At = A;
}
pA = At;
viennacl::linalg::detail::spai::initPreconditioner(pA, spai_m_);
viennacl::linalg::detail::spai::computeSPAI(At, spai_m_, tag_);
//(At, pA, tag_.getIsRight(), tag_.getIsStatic(), (ScalarType)_tag.getResidualNormThreshold(), (unsigned int)_tag.getIterationLimit(),
//_spai_m);
}
/** @brief Application of current preconditioner, multiplication on the right-hand side vector
* @param vec rhs vector
*/
void apply(VectorType& vec) const {
vec = viennacl::linalg::prod(spai_m_, vec);
}
private:
// variables
spai_tag tag_;
// result of SPAI
MatrixType spai_m_;
};
//VIENNACL version
/** @brief Implementation of the SParse Approximate Inverse Algorithm for a ViennaCL compressed_matrix.
* @param Matrix matrix that is used for computations
* @param Vector vector that is used for computations
*/
template<typename ScalarType, unsigned int MAT_ALIGNMENT>
class spai_precond< viennacl::compressed_matrix<ScalarType, MAT_ALIGNMENT> >
{
typedef viennacl::compressed_matrix<ScalarType, MAT_ALIGNMENT> MatrixType;
typedef boost::numeric::ublas::compressed_matrix<ScalarType> UBLASSparseMatrixType;
typedef viennacl::vector<ScalarType> VectorType;
typedef viennacl::matrix<ScalarType> VCLDenseMatrixType;
typedef boost::numeric::ublas::vector<ScalarType> UBLASVectorType;
public:
/** @brief Constructor
* @param A matrix whose approximate inverse is calculated. Must be quadratic.
* @param tag spai tag
*/
spai_precond(const MatrixType& A,
const spai_tag& tag): tag_(tag), spai_m_(viennacl::traits::context(A))
{
viennacl::ocl::context & ctx = const_cast<viennacl::ocl::context &>(viennacl::traits::opencl_handle(A).context());
viennacl::linalg::opencl::kernels::spai<ScalarType>::init(ctx);
MatrixType At(A.size1(), A.size2(), viennacl::context(ctx));
UBLASSparseMatrixType ubls_A(A.size1(), A.size2()), ubls_spai_m;
UBLASSparseMatrixType ubls_At;
viennacl::copy(A, ubls_A);
if (!tag_.getIsRight()){
viennacl::linalg::detail::spai::sparse_transpose(ubls_A, ubls_At);
}
else{
ubls_At = ubls_A;
}
//current pattern is A
//pA = ubls_At;
//execute SPAI with ublas matrix types
viennacl::linalg::detail::spai::initPreconditioner(ubls_At, ubls_spai_m);
viennacl::copy(ubls_At, At);
viennacl::linalg::detail::spai::computeSPAI(At, ubls_At, ubls_spai_m, spai_m_, tag_);
//viennacl::copy(ubls_spai_m, spai_m_);
tmp_.resize(A.size1(), viennacl::traits::context(A), false);
}
/** @brief Application of current preconditioner, multiplication on the right-hand side vector
* @param vec rhs vector
*/
void apply(VectorType& vec) const {
tmp_ = viennacl::linalg::prod(spai_m_, vec);
vec = tmp_;
}
private:
// variables
spai_tag tag_;
// result of SPAI
MatrixType spai_m_;
mutable VectorType tmp_;
};
//
// FSPAI
//
/** @brief Implementation of the Factored SParse Approximate Inverse Algorithm for a generic, uBLAS-compatible matrix type.
* @param Matrix matrix that is used for computations
* @param Vector vector that is used for computations
*/
//UBLAS version
template<typename MatrixType>
class fspai_precond
{
typedef typename MatrixType::value_type ScalarType;
typedef typename boost::numeric::ublas::vector<ScalarType> VectorType;
typedef typename boost::numeric::ublas::matrix<ScalarType> UBLASDenseMatrixType;
typedef typename viennacl::matrix<ScalarType> VCLMatrixType;
public:
/** @brief Constructor
* @param A matrix whose approximate inverse is calculated. Must be quadratic.
* @param tag SPAI configuration tag
*/
fspai_precond(const MatrixType& A,
const fspai_tag& tag): tag_(tag)
{
MatrixType pA = A;
viennacl::linalg::detail::spai::computeFSPAI(A, pA, L, L_trans, tag_);
}
/** @brief Application of current preconditioner, multiplication on the right-hand side vector
* @param vec rhs vector
*/
void apply(VectorType& vec) const
{
VectorType temp = viennacl::linalg::prod(L_trans, vec);
vec = viennacl::linalg::prod(L, temp);
}
private:
// variables
const fspai_tag & tag_;
// result of SPAI
MatrixType L;
MatrixType L_trans;
};
//
// ViennaCL version
//
/** @brief Implementation of the Factored SParse Approximate Inverse Algorithm for a ViennaCL compressed_matrix.
* @param Matrix matrix that is used for computations
* @param Vector vector that is used for computations
*/
template<typename ScalarType, unsigned int MAT_ALIGNMENT>
class fspai_precond< viennacl::compressed_matrix<ScalarType, MAT_ALIGNMENT> >
{
typedef viennacl::compressed_matrix<ScalarType, MAT_ALIGNMENT> MatrixType;
typedef viennacl::vector<ScalarType> VectorType;
typedef viennacl::matrix<ScalarType> VCLDenseMatrixType;
typedef boost::numeric::ublas::compressed_matrix<ScalarType> UBLASSparseMatrixType;
typedef boost::numeric::ublas::vector<ScalarType> UBLASVectorType;
public:
/** @brief Constructor
* @param A matrix whose approximate inverse is calculated. Must be quadratic.
* @param tag SPAI configuration tag
*/
fspai_precond(const MatrixType & A,
const fspai_tag & tag) : tag_(tag), L(viennacl::traits::context(A)), L_trans(viennacl::traits::context(A)), temp_apply_vec_(A.size1(), viennacl::traits::context(A))
{
//UBLASSparseMatrixType ubls_A;
UBLASSparseMatrixType ublas_A(A.size1(), A.size2());
UBLASSparseMatrixType pA(A.size1(), A.size2());
UBLASSparseMatrixType ublas_L(A.size1(), A.size2());
UBLASSparseMatrixType ublas_L_trans(A.size1(), A.size2());
viennacl::copy(A, ublas_A);
//viennacl::copy(ubls_A, vcl_A);
//vcl_At = viennacl::linalg::prod(vcl_A, vcl_A);
//vcl_pA = viennacl::linalg::prod(vcl_A, vcl_At);
//viennacl::copy(vcl_pA, pA);
pA = ublas_A;
//execute SPAI with ublas matrix types
viennacl::linalg::detail::spai::computeFSPAI(ublas_A, pA, ublas_L, ublas_L_trans, tag_);
//copy back to GPU
viennacl::copy(ublas_L, L);
viennacl::copy(ublas_L_trans, L_trans);
}
/** @brief Application of current preconditioner, multiplication on the right-hand side vector
* @param vec rhs vector
*/
void apply(VectorType& vec) const
{
temp_apply_vec_ = viennacl::linalg::prod(L_trans, vec);
vec = viennacl::linalg::prod(L, temp_apply_vec_);
}
private:
// variables
const fspai_tag & tag_;
MatrixType L;
MatrixType L_trans;
mutable VectorType temp_apply_vec_;
};
}
}
#endif
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