mame/src/lib/netlist/solver/nld_ms_gmres.h
couriersud 60379b658a netlist: code maintenance. (nw)
- Separate code out into pmath.h and pstonum.h.
- Fix VC build error
- optimize pfmtlog.h a bit
2019-11-03 23:19:52 +01:00

140 lines
3.5 KiB
C++

// license:GPL-2.0+
// copyright-holders:Couriersud
/*
* nld_ms_gmres.h
*
*/
#ifndef NLD_MS_GMRES_H_
#define NLD_MS_GMRES_H_
#include "nld_ms_direct.h"
#include "nld_solver.h"
#include "plib/gmres.h"
#include "plib/mat_cr.h"
#include "plib/parray.h"
#include "plib/vector_ops.h"
#include <algorithm>
namespace netlist
{
namespace solver
{
template <typename FT, int SIZE>
class matrix_solver_GMRES_t: public matrix_solver_direct_t<FT, SIZE>
{
public:
using float_type = FT;
/* Sort rows in ascending order. This should minimize fill-in and thus
* maximize the efficiency of the incomplete LUT.
* This is already preconditioning.
*/
matrix_solver_GMRES_t(netlist_state_t &anetlist, const pstring &name,
analog_net_t::list_t &nets,
const solver_parameters_t *params,
const std::size_t size)
: matrix_solver_direct_t<FT, SIZE>(anetlist, name, nets, params, size)
, m_ops(size, 0)
, m_gmres(size)
{
const std::size_t iN = this->size();
std::vector<std::vector<unsigned>> fill(iN);
for (std::size_t k=0; k<iN; k++)
{
fill[k].resize(iN, decltype(m_ops.m_mat)::FILL_INFINITY);
terms_for_net_t & row = this->m_terms[k];
for (const auto &nz_j : row.m_nz)
{
fill[k][static_cast<mattype>(nz_j)] = 0;
}
}
m_ops.build(fill);
this->log_fill(fill, m_ops.m_mat);
/* build pointers into the compressed row format matrix for each terminal */
for (std::size_t k=0; k<iN; k++)
{
std::size_t cnt = 0;
for (std::size_t j=0; j< this->m_terms[k].railstart();j++)
{
for (std::size_t i = m_ops.m_mat.row_idx[k]; i<m_ops.m_mat.row_idx[k+1]; i++)
if (this->m_terms[k].m_connected_net_idx[j] == static_cast<int>(m_ops.m_mat.col_idx[i]))
{
this->m_mat_ptr[k][j] = &m_ops.m_mat.A[i];
cnt++;
break;
}
}
nl_assert(cnt == this->m_terms[k].railstart());
this->m_mat_ptr[k][this->m_terms[k].railstart()] = &m_ops.m_mat.A[m_ops.m_mat.diag[k]];
}
}
unsigned vsolve_non_dynamic(const bool newton_raphson) override;
private:
using mattype = typename plib::pmatrix_cr_t<FT, SIZE>::index_type;
//plib::mat_precondition_none<FT, SIZE> m_ops;
plib::mat_precondition_ILU<FT, SIZE> m_ops;
//plib::mat_precondition_diag<FT, SIZE> m_ops;
plib::gmres_t<FT, SIZE> m_gmres;
};
// ----------------------------------------------------------------------------------------
// matrix_solver - GMRES
// ----------------------------------------------------------------------------------------
template <typename FT, int SIZE>
unsigned matrix_solver_GMRES_t<FT, SIZE>::vsolve_non_dynamic(const bool newton_raphson)
{
const std::size_t iN = this->size();
m_ops.m_mat.set_scalar(plib::constants<FT>::zero());
/* populate matrix and V for first estimate */
this->fill_matrix_and_rhs();
for (std::size_t k = 0; k < iN; k++)
{
this->m_new_V[k] = this->m_terms[k].template getV<float_type>();
}
const float_type accuracy = static_cast<float_type>(this->m_params.m_accuracy);
auto iter = std::max(plib::constants<std::size_t>::one(), this->m_params.m_gs_loops());
auto gsl = m_gmres.solve(m_ops, this->m_new_V, this->m_RHS, iter, accuracy);
this->m_iterative_total += gsl;
this->m_stat_calculations++;
if (gsl > iter)
{
this->m_iterative_fail++;
return matrix_solver_direct_t<FT, SIZE>::vsolve_non_dynamic(newton_raphson);
}
bool err(false);
if (newton_raphson)
err = this->check_err();
this->store();
return (err) ? 2 : 1;
}
} // namespace solver
} // namespace netlist
#endif /* NLD_MS_GMRES_H_ */