bisect_gpu.hpp

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#ifndef VIENNACL_LINALG_BISECT_GPU
#define VIENNACL_LINALG_BISECT_GPU

/* =========================================================================
   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
============================================================================= */


// includes, system
#include <stdlib.h>
#include <stdio.h>
#include <string.h>

#include "viennacl/scalar.hpp"
#include "viennacl/vector.hpp"
#include "viennacl/matrix.hpp"

// includes, project
#include "viennacl/linalg/detail/bisect/structs.hpp"
#include "viennacl/linalg/detail/bisect/gerschgorin.hpp"
#include "viennacl/linalg/detail/bisect/bisect_large.hpp"
#include "viennacl/linalg/detail/bisect/bisect_small.hpp"


namespace viennacl
{
namespace linalg
{
template<typename NumericT>
bool
bisect(const std::vector<NumericT> & diagonal, const std::vector<NumericT> & superdiagonal, std::vector<NumericT> & eigenvalues)
{
  assert(diagonal.size() == superdiagonal.size() &&
         diagonal.size() == eigenvalues.size()   &&
         bool("Input vectors do not have the same sizes!"));
  bool bResult = false;
  // flag if the matrix size is due to explicit user request
  // desired precision of eigenvalues
  NumericT  precision = static_cast<NumericT>(0.00001);
  const unsigned int mat_size = static_cast<unsigned int>(diagonal.size());

  // set up input
  viennacl::linalg::detail::InputData<NumericT> input(diagonal, superdiagonal, mat_size);

  NumericT lg =  FLT_MAX;
  NumericT ug = -FLT_MAX;
  // compute Gerschgorin interval
  viennacl::linalg::detail::computeGerschgorin(input.std_a, input.std_b, mat_size, lg, ug);

  // decide wheter the algorithm for small or for large matrices will be started
  if (mat_size <= VIENNACL_BISECT_MAX_SMALL_MATRIX)
  {
    // initialize memory for result
    viennacl::linalg::detail::ResultDataSmall<NumericT> result(mat_size);

    // run the kernel
    viennacl::linalg::detail::computeEigenvaluesSmallMatrix(input, result, mat_size, lg, ug, precision);

    // get the result from the device and do some sanity checks,
    viennacl::linalg::detail::processResultSmallMatrix(result, mat_size);
    eigenvalues = result.std_eigenvalues;
    bResult = true;
  }

  else
  {
    // initialize memory for result
    viennacl::linalg::detail::ResultDataLarge<NumericT> result(mat_size);

    // run the kernel
    viennacl::linalg::detail::computeEigenvaluesLargeMatrix(input, result, mat_size, lg, ug, precision);

    // get the result from the device and do some sanity checks
    bResult = viennacl::linalg::detail::processResultDataLargeMatrix(result, mat_size);

    eigenvalues = result.std_eigenvalues;
  }
  return bResult;
}


template<typename NumericT>
bool
bisect(const viennacl::vector<NumericT> & diagonal, const viennacl::vector<NumericT> & superdiagonal, viennacl::vector<NumericT> & eigenvalues)
{
  assert(diagonal.size() == superdiagonal.size() &&
         diagonal.size() == eigenvalues.size()   &&
         bool("Input vectors do not have the same sizes!"));
  bool bResult = false;
  // flag if the matrix size is due to explicit user request
  // desired precision of eigenvalues
  NumericT  precision = static_cast<NumericT>(0.00001);
  const unsigned int mat_size = static_cast<unsigned int>(diagonal.size());

  // set up input
  viennacl::linalg::detail::InputData<NumericT> input(diagonal, superdiagonal, mat_size);

  NumericT lg =  FLT_MAX;
  NumericT ug = -FLT_MAX;
  // compute Gerschgorin interval
  viennacl::linalg::detail::computeGerschgorin(input.std_a, input.std_b, mat_size, lg, ug);

  // decide wheter the algorithm for small or for large matrices will be started
  if (mat_size <= VIENNACL_BISECT_MAX_SMALL_MATRIX)
  {
    // initialize memory for result
    viennacl::linalg::detail::ResultDataSmall<NumericT> result(mat_size);

    // run the kernel
    viennacl::linalg::detail::computeEigenvaluesSmallMatrix(input, result, mat_size, lg, ug, precision);

    // get the result from the device and do some sanity checks,
    viennacl::linalg::detail::processResultSmallMatrix(result, mat_size);
    copy(result.std_eigenvalues, eigenvalues);
    bResult = true;
  }

  else
  {
    // initialize memory for result
    viennacl::linalg::detail::ResultDataLarge<NumericT> result(mat_size);

    // run the kernel
    viennacl::linalg::detail::computeEigenvaluesLargeMatrix(input, result, mat_size, lg, ug, precision);

    // get the result from the device and do some sanity checks
    bResult = viennacl::linalg::detail::processResultDataLargeMatrix(result, mat_size);

    copy(result.std_eigenvalues, eigenvalues);
  }
  return bResult;
}
} // namespace linalg
} // namespace viennacl
#endif