solver_BiCGStab_L_Cmplx.cpp

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#include "solver_BiCGStab_L_Cmplx.h"



#ifdef USE_FACTORY
namespace {
  Solver *create_object(Fopr *fopr)
  {
    return new Solver_BiCGStab_L_Cmplx(fopr);
  }


  bool init = Solver::Factory::Register("BiCGStab_L_Cmplx", create_object);
}
#endif

//- parameter entries
namespace {
  void append_entry(Parameters& param)
  {
    param.Register_int("maximum_number_of_iteration", 0);
    param.Register_double("convergence_criterion_squared", 0.0);

    param.Register_int("number_of_orthonormal_vectors", 0);

    param.Register_string("verbose_level", "NULL");
  }


#ifdef USE_PARAMETERS_FACTORY
  bool init_param = ParametersFactory::Register("Solver.BiCGStab_L_Cmplx", append_entry);
#endif
}
//- end

//- parameters class
Parameters_Solver_BiCGStab_L_Cmplx::Parameters_Solver_BiCGStab_L_Cmplx() { append_entry(*this); }
//- end

const std::string Solver_BiCGStab_L_Cmplx::class_name = "Solver_BiCGStab_L_Cmplx";

//====================================================================
void Solver_BiCGStab_L_Cmplx::set_parameters(const Parameters& params)
{
  const string str_vlevel = params.get_string("verbose_level");

  m_vl = vout.set_verbose_level(str_vlevel);

  //- fetch and check input parameters
  int    Niter;
  double Stop_cond;
  int    N_L;

  int err = 0;
  err += params.fetch_int("maximum_number_of_iteration", Niter);
  err += params.fetch_double("convergence_criterion_squared", Stop_cond);
  err += params.fetch_int("number_of_orthonormal_vectors", N_L);

  if (err) {
    vout.crucial(m_vl, "%s: fetch error, input parameter not found.\n", class_name.c_str());
    exit(EXIT_FAILURE);
  }


  set_parameters(Niter, Stop_cond);
  set_parameters_L(N_L);
}


//====================================================================
void Solver_BiCGStab_L_Cmplx::set_parameters(const int Niter, const double Stop_cond)
{
  ThreadManager_OpenMP::assert_single_thread(class_name);

  //- print input parameters
  vout.general(m_vl, "%s: input parameters\n", class_name.c_str());
  vout.general(m_vl, "  Niter     = %d\n", Niter);
  vout.general(m_vl, "  Stop_cond = %16.8e\n", Stop_cond);

  //- range check
  int err = 0;
  err += ParameterCheck::non_negative(Niter);
  err += ParameterCheck::square_non_zero(Stop_cond);

  if (err) {
    vout.crucial(m_vl, "%s: parameter range check failed.\n", class_name.c_str());
    exit(EXIT_FAILURE);
  }

  //- store values
  m_Niter     = Niter;
  m_Stop_cond = Stop_cond;
}


//====================================================================
void Solver_BiCGStab_L_Cmplx::set_parameters_L(const int N_L)
{
  //- print input parameters
  vout.general(m_vl, "  N_L   = %d\n", N_L);

  //- range check
  int err = 0;
  err += ParameterCheck::non_negative(N_L);

  if (err) {
    vout.crucial(m_vl, "%s: parameter range check failed.\n", class_name.c_str());
    exit(EXIT_FAILURE);
  }

  //- store values
  m_N_L = N_L;
}


//====================================================================
void Solver_BiCGStab_L_Cmplx::solve(Field& xq, const Field& b,
                                    int& Nconv, double& diff)
{
  double bnorm2 = b.norm2();
  double snorm  = 1.0 / bnorm2;
  int    bsize  = b.size();
  double rr;

  vout.paranoiac(m_vl, "%s: starts\n", class_name.c_str());
  vout.paranoiac(m_vl, "  norm of b = %16.8e\n", bnorm2);
  vout.paranoiac(m_vl, "  size of b = %d\n", bsize);

  reset_field(b);


  // Nconv = -1;
  int Nconv2 = 0;
  copy(s, b); // s = b;

  solve_init(b, rr);

  bool is_converged = false;

  vout.detailed(m_vl, "    iter: %8d  %22.15e\n", 0, rr * snorm);


  for (int iter = 0; iter < m_Niter; iter++) {
    if (is_converged) break;

    solve_step(rr);

    Nconv2 += 2 * m_N_L;

    vout.detailed(m_vl, "    iter: %8d  %22.15e\n", Nconv2, rr * snorm);

    if (rr * snorm < m_Stop_cond) {
      m_fopr->mult(s, x); // s  = m_fopr->mult(x);
      axpy(s, -1.0, b);   // s -= b;

      double diff2 = s.norm2();

      if (diff2 * snorm < m_Stop_cond) {
        // NB. Nconv is calculated above.
        is_converged = true;
      } else {
        copy(s, x); // s = x;
        solve_init(b, rr);
      }
    }
  }


  m_fopr->mult(s, x); // s  = m_fopr->mult(x);
  axpy(s, -1.0, b);   // s -= b;

  copy(xq, x);        // xq = x;

  double diff2 = s.norm2();

  if (diff2 * snorm > m_Stop_cond) {
    vout.crucial(m_vl, "%s: not converged.\n", class_name.c_str());
    exit(EXIT_FAILURE);
  }


#pragma omp barrier
#pragma omp master
  {
    diff  = sqrt(diff2);
    Nconv = Nconv2;
  }
#pragma omp barrier
}


//====================================================================
void Solver_BiCGStab_L_Cmplx::reset_field(const Field& b)
{
#pragma omp barrier
#pragma omp master
  {
    int Nin  = b.nin();
    int Nvol = b.nvol();
    int Nex  = b.nex();

    if ((s.nin() != Nin) || (s.nvol() != Nvol) || (s.nex() != Nex)) {
      s.reset(Nin, Nvol, Nex);
      x.reset(Nin, Nvol, Nex);
      r_init.reset(Nin, Nvol, Nex);
      v_tmp.reset(Nin, Nvol, Nex);
    }

    u.resize(m_N_L + 1);
    r.resize(m_N_L + 1);

    for (int i = 0; i < m_N_L + 1; ++i) {
      u[i].reset(Nin, Nvol, Nex);
      r[i].reset(Nin, Nvol, Nex);
    }
  }
#pragma omp barrier

  vout.paranoiac(m_vl, "    %s: field size reset.\n", class_name.c_str());
}


//====================================================================
void Solver_BiCGStab_L_Cmplx::solve_init(const Field& b, double& rr)
{
  copy(x, s);  // x = s;

  //- r[0] = b - A x_0
  m_fopr->mult(v_tmp, s);   // v_tmp = m_fopr->mult(s);
  copy(r[0], b);            // r[0]  = b;
  axpy(r[0], -1.0, v_tmp);  // r[0] -= v_tmp;

  copy(r_init, r[0]);       // r_init = r[0];
  rr = r[0].norm2();        // rr     = r[0] * r[0];

  u[0].set(0.0);            // u[0] = 0.0;

#pragma omp barrier
#pragma omp master
  {
    rho_prev = cmplx(-1.0, 0.0);

    // NB. alpha_prev = 0.0 \neq 1.0
    alpha_prev = cmplx(0.0, 0.0);
  }
#pragma omp barrier
}


//====================================================================
void Solver_BiCGStab_L_Cmplx::solve_step(double& rr)
{
  dcomplex rho_prev2   = rho_prev;
  dcomplex alpha_prev2 = alpha_prev;

  for (int j = 0; j < m_N_L; ++j) {
    dcomplex rho = dotc(r[j], r_init);   // dcomplex rho  = r[j] * r_init;
    rho = conj(rho);

    dcomplex beta = alpha_prev2 * (rho / rho_prev2);

    rho_prev2 = rho;

    for (int i = 0; i < j + 1; ++i) {
      aypx(-beta, u[i], r[i]);   // u[i] = - beta * u[i] + r[i];
    }

    m_fopr->mult(u[j + 1], u[j]);  // u[j+1] = m_fopr->mult(u[j]);

    dcomplex gamma = dotc(u[j + 1], r_init);
    alpha_prev2 = rho_prev2 / conj(gamma);

    for (int i = 0; i < j + 1; ++i) {
      axpy(r[i], -alpha_prev2, u[i + 1]);  // r[i] -= alpha_prev * u[i+1];
    }

    m_fopr->mult(r[j + 1], r[j]);        // r[j+1] = m_fopr->mult(r[j]);

    axpy(x, alpha_prev2, u[0]);          // x += alpha_prev * u[0];
  }


  std::vector<double>   sigma(m_N_L + 1);
  std::vector<dcomplex> gamma_prime(m_N_L + 1);

  // NB. tau(m_N_L,m_N_L+1), not (m_N_L+1,m_N_L+1)
  std::vector<dcomplex> tau(m_N_L * (m_N_L + 1));
  int ij, ji;

  for (int j = 1; j < m_N_L + 1; ++j) {
    for (int i = 1; i < j; ++i) {
      ij = index_ij(i, j);

      dcomplex r_ji = dotc(r[j], r[i]);
      tau[ij] = conj(r_ji) / sigma[i];  // tau[ij]  = (r[j] * r[i]) / sigma[i];
      axpy(r[j], -tau[ij], r[i]);       // r[j]    -= tau[ij] * r[i];
    }

    sigma[j] = r[j].norm2();  // sigma[j] = r[j] * r[j];

    dcomplex r_0j = dotc(r[0], r[j]);
    gamma_prime[j] = conj(r_0j) / sigma[j]; // gamma_prime[j] = (r[0] * r[j]) / sigma[j];
  }


  std::vector<dcomplex> gamma(m_N_L + 1);
  dcomplex              c_tmp;

  gamma[m_N_L] = gamma_prime[m_N_L];

  for (int j = m_N_L - 1; j > 0; --j) {
    c_tmp = cmplx(0.0, 0.0);

    for (int i = j + 1; i < m_N_L + 1; ++i) {
      ji     = index_ij(j, i);
      c_tmp += tau[ji] * gamma[i];
    }

    gamma[j] = gamma_prime[j] - c_tmp;
  }


  // NB. gamma_double_prime(m_N_L), not (m_N_L+1)
  std::vector<dcomplex> gamma_double_prime(m_N_L);

  for (int j = 1; j < m_N_L; ++j) {
    c_tmp = cmplx(0.0, 0.0);

    for (int i = j + 1; i < m_N_L; ++i) {
      ji     = index_ij(j, i);
      c_tmp += tau[ji] * gamma[i + 1];
    }

    gamma_double_prime[j] = gamma[j + 1] + c_tmp;
  }


  axpy(x, gamma[1], r[0]);                    // x    += gamma[          1] * r[    0];
  axpy(r[0], -gamma_prime[m_N_L], r[m_N_L]);  // r[0] -= gamma_prime[m_N_L] * r[m_N_L];
  axpy(u[0], -gamma[m_N_L], u[m_N_L]);        // u[0] -= gamma[      m_N_L] * u[m_N_L];

  for (int j = 1; j < m_N_L; ++j) {
    axpy(x, gamma_double_prime[j], r[j]);      // x    += gamma_double_prime[j] * r[j];
    axpy(r[0], -gamma_prime[j], r[j]);         // r[0] -= gamma_prime[       j] * r[j];
    axpy(u[0], -gamma[j], u[j]);               // u[0] -= gamma[             j] * u[j];
  }

  rr = r[0].norm2();  // rr = r[0] * r[0];

#pragma omp barrier
#pragma omp master
  {
    rho_prev   = rho_prev2;
    alpha_prev = alpha_prev2;
    rho_prev  *= -gamma_prime[m_N_L];
  }
#pragma omp barrier
}


//====================================================================
//============================================================END=====