/usr/include/viennacl/linalg/qr-method-common.hpp is in libviennacl-dev 1.5.2-2.
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_QR_METHOD_COMMON_HPP
/* =========================================================================
Copyright (c) 2010-2014, 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 PDF manual)
License: MIT (X11), see file LICENSE in the base directory
============================================================================= */
#include <cmath>
#include "viennacl/ocl/device.hpp"
#include "viennacl/ocl/handle.hpp"
#include "viennacl/ocl/kernel.hpp"
#include "viennacl/linalg/opencl/kernels/svd.hpp"
#include "viennacl/meta/result_of.hpp"
#include "viennacl/vector.hpp"
#include "viennacl/matrix.hpp"
#include <boost/numeric/ublas/vector.hpp>
#include <boost/numeric/ublas/io.hpp>
/** @file viennacl/linalg/qr-method-common.hpp
@brief Common routines used for the QR method and SVD. Experimental.
*/
namespace viennacl
{
namespace linalg
{
const std::string SVD_BIDIAG_PACK_KERNEL = "bidiag_pack";
const std::string SVD_HOUSEHOLDER_UPDATE_A_LEFT_KERNEL = "house_update_A_left";
const std::string SVD_HOUSEHOLDER_UPDATE_A_RIGHT_KERNEL = "house_update_A_right";
const std::string SVD_HOUSEHOLDER_UPDATE_QL_KERNEL = "house_update_QL";
const std::string SVD_HOUSEHOLDER_UPDATE_QR_KERNEL = "house_update_QR";
const std::string SVD_COPY_COL_KERNEL = "copy_col";
const std::string SVD_COPY_ROW_KERNEL = "copy_row";
const std::string SVD_MATRIX_TRANSPOSE_KERNEL = "transpose_inplace";
const std::string SVD_INVERSE_SIGNS_KERNEL = "inverse_signs";
const std::string SVD_GIVENS_PREV_KERNEL = "givens_prev";
const std::string SVD_GIVENS_NEXT_KERNEL = "givens_next";
const std::string SVD_FINAL_ITER_UPDATE_KERNEL = "final_iter_update";
const std::string SVD_UPDATE_QR_COLUMN_KERNEL = "update_qr_column";
namespace detail
{
//static const float EPS = 0.00001f;
//static const vcl_size_t ITER_MAX = 50;
static const double EPS = 1e-10;
static const vcl_size_t ITER_MAX = 50;
template <typename SCALARTYPE>
SCALARTYPE pythag(SCALARTYPE a, SCALARTYPE b)
{
return std::sqrt(a*a + b*b);
}
template <typename SCALARTYPE>
SCALARTYPE sign(SCALARTYPE val)
{
return (val >= 0) ? SCALARTYPE(1) : SCALARTYPE(-1);
}
// DEPRECATED: Replace with viennacl::linalg::norm_2
template <typename VectorType>
typename VectorType::value_type norm_lcl(VectorType const & x, vcl_size_t size)
{
typename VectorType::value_type x_norm = 0.0;
for(vcl_size_t i = 0; i < size; i++)
x_norm += std::pow(x[i], 2);
return std::sqrt(x_norm);
}
template <typename VectorType>
void normalize(VectorType & x, vcl_size_t size)
{
typename VectorType::value_type x_norm = norm_lcl(x, size);
for(vcl_size_t i = 0; i < size; i++)
x[i] /= x_norm;
}
template <typename VectorType>
void householder_vector(VectorType & v, vcl_size_t start)
{
typedef typename VectorType::value_type ScalarType;
ScalarType x_norm = norm_lcl(v, v.size());
ScalarType alpha = -sign(v[start]) * x_norm;
v[start] += alpha;
normalize(v, v.size());
}
template <typename MatrixType>
void transpose(MatrixType & A)
{
typedef typename MatrixType::value_type ScalarType;
typedef typename viennacl::result_of::cpu_value_type<ScalarType>::type CPU_ScalarType;
viennacl::ocl::kernel & kernel = viennacl::ocl::get_kernel(viennacl::linalg::opencl::kernels::svd<CPU_ScalarType>::program_name(), SVD_MATRIX_TRANSPOSE_KERNEL);
viennacl::ocl::enqueue(kernel(A,
static_cast<cl_uint>(A.internal_size1()),
static_cast<cl_uint>(A.internal_size2())
)
);
}
template <typename T>
void cdiv(T xr, T xi, T yr, T yi, T& cdivr, T& cdivi)
{
// Complex scalar division.
T r;
T d;
if (std::fabs(yr) > std::fabs(yi))
{
r = yi / yr;
d = yr + r * yi;
cdivr = (xr + r * xi) / d;
cdivi = (xi - r * xr) / d;
}
else
{
r = yr / yi;
d = yi + r * yr;
cdivr = (r * xr + xi) / d;
cdivi = (r * xi - xr) / d;
}
}
template <typename SCALARTYPE, unsigned int ALIGNMENT>
void copy_vec(viennacl::matrix<SCALARTYPE, row_major, ALIGNMENT>& A,
viennacl::vector<SCALARTYPE, ALIGNMENT>& V,
vcl_size_t row_start,
vcl_size_t col_start,
bool copy_col
)
{
std::string kernel_name = copy_col ? SVD_COPY_COL_KERNEL : SVD_COPY_ROW_KERNEL;
viennacl::ocl::context & ctx = const_cast<viennacl::ocl::context &>(viennacl::traits::opencl_handle(A).context());
viennacl::ocl::kernel& kernel = ctx.get_kernel(viennacl::linalg::opencl::kernels::svd<SCALARTYPE>::program_name(), kernel_name);
viennacl::ocl::enqueue(kernel(
A,
V,
static_cast<cl_uint>(row_start),
static_cast<cl_uint>(col_start),
copy_col ? static_cast<cl_uint>(A.size1())
: static_cast<cl_uint>(A.size2()),
static_cast<cl_uint>(A.internal_size2())
));
}
template<typename SCALARTYPE, unsigned int ALIGNMENT>
void prepare_householder_vector(
viennacl::matrix<SCALARTYPE, row_major, ALIGNMENT>& A,
viennacl::vector<SCALARTYPE, ALIGNMENT>& D,
vcl_size_t size,
vcl_size_t row_start,
vcl_size_t col_start,
vcl_size_t start,
bool is_column
)
{
boost::numeric::ublas::vector<SCALARTYPE> tmp = boost::numeric::ublas::scalar_vector<SCALARTYPE>(size, 0);
copy_vec(A, D, row_start, col_start, is_column);
fast_copy(D.begin(), D.begin() + vcl_ptrdiff_t(size - start), tmp.begin() + start);
//std::cout << "1: " << tmp << "\n";
detail::householder_vector(tmp, start);
fast_copy(tmp, D);
//std::cout << "2: " << D << "\n";
}
template <typename SCALARTYPE, unsigned int ALIGNMENT, typename VectorType>
void bidiag_pack(viennacl::matrix<SCALARTYPE, row_major, ALIGNMENT>& A,
VectorType & dh,
VectorType & sh
)
{
viennacl::vector<SCALARTYPE, ALIGNMENT> D(dh.size());
viennacl::vector<SCALARTYPE, ALIGNMENT> S(sh.size());
viennacl::ocl::context & ctx = const_cast<viennacl::ocl::context &>(viennacl::traits::opencl_handle(A).context());
viennacl::ocl::kernel& kernel = ctx.get_kernel(viennacl::linalg::opencl::kernels::svd<SCALARTYPE>::program_name(), SVD_BIDIAG_PACK_KERNEL);
viennacl::ocl::enqueue(kernel(
A,
D,
S,
static_cast<cl_uint>(A.size1()),
static_cast<cl_uint>(A.size2()),
static_cast<cl_uint>(A.internal_size2())
));
fast_copy(D, dh);
fast_copy(S, sh);
}
}
}
}
#endif
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