ViennaCL - The Vienna Computing Library  1.5.1
Namespaces | Defines | Functions
viennacl/linalg/detail/spai/spai.hpp File Reference

Main implementation of SPAI (not FSPAI). Experimental. More...

#include <utility>
#include <iostream>
#include <fstream>
#include <string>
#include <algorithm>
#include <vector>
#include <math.h>
#include <map>
#include "viennacl/linalg/detail/spai/spai_tag.hpp"
#include "viennacl/linalg/qr.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 "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"
#include "viennacl/linalg/prod.hpp"
#include "viennacl/matrix.hpp"
#include "viennacl/compressed_matrix.hpp"
#include "viennacl/linalg/sparse_matrix_operations.hpp"
#include "viennacl/linalg/matrix_operations.hpp"
#include "viennacl/scalar.hpp"
#include "viennacl/linalg/inner_prod.hpp"
#include "viennacl/linalg/ilu.hpp"
#include "viennacl/ocl/backend.hpp"
#include "viennacl/linalg/opencl/kernels/spai.hpp"

Go to the source code of this file.

Namespaces

namespace  viennacl
 

Main namespace in ViennaCL. Holds all the basic types such as vector, matrix, etc. and defines operations upon them.


namespace  viennacl::linalg
 

Provides all linear algebra operations which are not covered by operator overloads.


namespace  viennacl::linalg::detail
 

Namespace holding implementation details for linear algebra routines. Usually not of interest for a library user.


namespace  viennacl::linalg::detail::spai
 

Implementation namespace for sparse approximate inverse preconditioner.


Defines

#define VIENNACL_SPAI_K_b   20

Functions

template<typename SparseVectorType >
void print_sparse_vector (const SparseVectorType &v)
template<typename DenseMatrixType >
void print_matrix (DenseMatrixType &m)
template<typename SparseVectorType , typename ScalarType >
void add_sparse_vectors (const SparseVectorType &v, const ScalarType b, SparseVectorType &res_v)
 Add two sparse vectors res_v = b*v.
template<typename SparseVectorType , typename ScalarType >
void compute_spai_residual (const std::vector< SparseVectorType > &A_v_c, const SparseVectorType &v, const unsigned int ind, SparseVectorType &res)
 Computation of residual res = A*v - e.
template<typename SparseVectorType >
void build_index_set (const std::vector< SparseVectorType > &A_v_c, const SparseVectorType &v, std::vector< unsigned int > &J, std::vector< unsigned int > &I)
 Setting up index set of columns and rows for certain column.
template<typename SparseMatrixType , typename DenseMatrixType >
void initProjectSubMatrix (const SparseMatrixType &A_in, const std::vector< unsigned int > &J, std::vector< unsigned int > &I, DenseMatrixType &A_out)
 Initializes a dense matrix from a sparse one.
template<typename SparseMatrixType , typename DenseMatrixType , typename SparseVectorType , typename VectorType >
void block_set_up (const SparseMatrixType &A, const std::vector< SparseVectorType > &A_v_c, const std::vector< SparseVectorType > &M_v, std::vector< std::vector< unsigned int > > &g_I, std::vector< std::vector< unsigned int > > &g_J, std::vector< DenseMatrixType > &g_A_I_J, std::vector< VectorType > &g_b_v)
 Setting up blocks and QR factorizing them on CPU.
template<typename SparseVectorType >
void index_set_up (const std::vector< SparseVectorType > &A_v_c, const std::vector< SparseVectorType > &M_v, std::vector< std::vector< unsigned int > > &g_J, std::vector< std::vector< unsigned int > > &g_I)
 Setting up index set of columns and rows for all columns.
template<typename ScalarType , unsigned int MAT_ALIGNMENT, typename SparseVectorType >
void block_set_up (const viennacl::compressed_matrix< ScalarType, MAT_ALIGNMENT > &A, const std::vector< SparseVectorType > &A_v_c, const std::vector< SparseVectorType > &M_v, std::vector< cl_uint > g_is_update, std::vector< std::vector< unsigned int > > &g_I, std::vector< std::vector< unsigned int > > &g_J, block_matrix &g_A_I_J, block_vector &g_bv)
 Setting up blocks and QR factorizing them on GPU.
template<typename ScalarType , typename SparseVectorType >
void custom_fan_out (const std::vector< ScalarType > &m_in, unsigned int start_m_ind, const std::vector< unsigned int > &J, SparseVectorType &m)
 Elicitation of sparse vector m for particular column from m_in - contigious vector for all columns.
template<typename SparseVectorType , typename ScalarType >
void least_square_solve (std::vector< SparseVectorType > &A_v_c, std::vector< SparseVectorType > &M_v, std::vector< std::vector< unsigned int > > &g_I, std::vector< std::vector< unsigned int > > &g_J, block_matrix &g_A_I_J_vcl, block_vector &g_bv_vcl, std::vector< SparseVectorType > &g_res, std::vector< cl_uint > &g_is_update, const spai_tag &tag, viennacl::context ctx)
 Solution of Least square problem on GPU.
template<typename SparseVectorType , typename DenseMatrixType , typename VectorType >
void least_square_solve (const std::vector< SparseVectorType > &A_v_c, std::vector< DenseMatrixType > &g_R, std::vector< VectorType > &g_b_v, std::vector< std::vector< unsigned int > > &g_I, std::vector< std::vector< unsigned int > > &g_J, std::vector< SparseVectorType > &g_res, std::vector< bool > &g_is_update, std::vector< SparseVectorType > &M_v, const spai_tag &tag)
 Solution of Least square problem on CPU.
template<typename VectorType >
bool is_all_update (VectorType &parallel_is_update)
template<typename SparseMatrixType , typename SparseVectorType >
void vectorize_column_matrix (const SparseMatrixType &M_in, std::vector< SparseVectorType > &M_v)
 Solution of Least square problem on CPU.
template<typename SparseMatrixType , typename SparseVectorType >
void vectorize_row_matrix (const SparseMatrixType &M_in, std::vector< SparseVectorType > &M_v)
template<typename SizeType >
void write_set_to_array (const std::vector< std::vector< SizeType > > &ind_set, std::vector< cl_uint > &a)
template<typename ScalarType , unsigned int MAT_ALIGNMENT>
void block_assembly (const viennacl::compressed_matrix< ScalarType, MAT_ALIGNMENT > &A, const std::vector< std::vector< unsigned int > > &g_J, const std::vector< std::vector< unsigned int > > &g_I, block_matrix &g_A_I_J_vcl, std::vector< cl_uint > &g_is_update, bool &is_empty_block)
 Assembly of blocks on GPU by a gived set of row indices: g_I and column indices: g_J.
template<typename SparseMatrixType , typename SparseVectorType >
void insert_sparse_columns (const std::vector< SparseVectorType > &M_v, SparseMatrixType &M, bool is_right)
 Insertion of vectorized matrix column into original sparse matrix.
template<typename MatrixType >
void sparse_transpose (const MatrixType &A_in, MatrixType &A)
 Transposition of sparse matrix.
template<typename MatrixType >
void computeSPAI (const MatrixType &A, MatrixType &M, spai_tag &tag)
 Construction of SPAI preconditioner on CPU.
template<typename ScalarType , unsigned int MAT_ALIGNMENT>
void computeSPAI (const viennacl::compressed_matrix< ScalarType, MAT_ALIGNMENT > &A, const boost::numeric::ublas::compressed_matrix< ScalarType > &cpu_A, boost::numeric::ublas::compressed_matrix< ScalarType > &cpu_M, viennacl::compressed_matrix< ScalarType, MAT_ALIGNMENT > &M, const spai_tag &tag)
 Construction of SPAI preconditioner on GPU.

Detailed Description

Main implementation of SPAI (not FSPAI). Experimental.


Define Documentation

#define VIENNACL_SPAI_K_b   20