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Diffstat (limited to 'src/lib/netlist/solver/nld_ms_sm.h')
-rw-r--r-- | src/lib/netlist/solver/nld_ms_sm.h | 636 |
1 files changed, 636 insertions, 0 deletions
diff --git a/src/lib/netlist/solver/nld_ms_sm.h b/src/lib/netlist/solver/nld_ms_sm.h new file mode 100644 index 00000000000..c9ee083c54a --- /dev/null +++ b/src/lib/netlist/solver/nld_ms_sm.h @@ -0,0 +1,636 @@ +// license:GPL-2.0+ +// copyright-holders:Couriersud +/* + * nld_ms_direct.h + * + */ + +#ifndef NLD_MS_SM_H_ +#define NLD_MS_SM_H_ + +#include <algorithm> + +#include "solver/nld_solver.h" +#include "solver/vector_base.h" + +/* Disabling dynamic allocation gives a ~10% boost in performance + * This flag has been added to support continuous storage for arrays + * going forward in case we implement cuda solvers in the future. + */ + +NETLIB_NAMESPACE_DEVICES_START() + +//#define nl_ext_double __float128 // slow, very slow +//#define nl_ext_double long double // slightly slower +#define nl_ext_double nl_double + +template <unsigned m_N, unsigned _storage_N> +class matrix_solver_sm_t: public matrix_solver_t +{ +public: + + matrix_solver_sm_t(const solver_parameters_t *params, const int size); + matrix_solver_sm_t(const eSolverType type, const solver_parameters_t *params, const int size); + + virtual ~matrix_solver_sm_t(); + + virtual void vsetup(analog_net_t::list_t &nets) override; + virtual void reset() override { matrix_solver_t::reset(); } + +protected: + virtual void add_term(int net_idx, terminal_t *term) override; + virtual int vsolve_non_dynamic(const bool newton_raphson) override; + int solve_non_dynamic(const bool newton_raphson); + + inline const unsigned N() const { if (m_N == 0) return m_dim; else return m_N; } + + void build_LE_A(); + void build_LE_RHS(); + void LE_invert(); + + template <typename T> + void LE_compute_x(T * RESTRICT x); + + template <typename T> + T delta(const T * RESTRICT V); + + template <typename T> + void store(const T * RESTRICT V); + + virtual netlist_time compute_next_timestep() override; + + template <typename T1, typename T2> + inline nl_ext_double &A(const T1 &r, const T2 &c) { return m_A[r][c]; } + template <typename T1, typename T2> + inline nl_ext_double &W(const T1 &r, const T2 &c) { return m_W[r][c]; } + template <typename T1, typename T2> + inline nl_ext_double &Ainv(const T1 &r, const T2 &c) { return m_Ainv[r][c]; } + template <typename T1> + inline nl_ext_double &RHS(const T1 &r) { return m_RHS[r]; } + + + template <typename T1, typename T2> + inline nl_ext_double &lA(const T1 &r, const T2 &c) { return m_lA[r][c]; } + template <typename T1, typename T2> + inline nl_ext_double &lAinv(const T1 &r, const T2 &c) { return m_lAinv[r][c]; } + + ATTR_ALIGN nl_double m_last_RHS[_storage_N]; // right hand side - contains currents + ATTR_ALIGN nl_double m_last_V[_storage_N]; + + terms_t * m_terms[_storage_N]; + terms_t *m_rails_temp; + +private: + static const std::size_t m_pitch = ((( _storage_N) + 7) / 8) * 8; + ATTR_ALIGN nl_ext_double m_A[_storage_N][m_pitch]; + ATTR_ALIGN nl_ext_double m_Ainv[_storage_N][m_pitch]; + ATTR_ALIGN nl_ext_double m_W[_storage_N][m_pitch]; + ATTR_ALIGN nl_ext_double m_RHS[_storage_N]; // right hand side - contains currents + + ATTR_ALIGN nl_ext_double m_lA[_storage_N][m_pitch]; + ATTR_ALIGN nl_ext_double m_lAinv[_storage_N][m_pitch]; + + //ATTR_ALIGN nl_ext_double m_RHSx[_storage_N]; + + const unsigned m_dim; + +}; + +// ---------------------------------------------------------------------------------------- +// matrix_solver_direct +// ---------------------------------------------------------------------------------------- + +template <unsigned m_N, unsigned _storage_N> +matrix_solver_sm_t<m_N, _storage_N>::~matrix_solver_sm_t() +{ + for (unsigned k = 0; k < N(); k++) + { + pfree(m_terms[k]); + } + pfree_array(m_rails_temp); +#if (NL_USE_DYNAMIC_ALLOCATION) + pfree_array(m_A); +#endif +} + +template <unsigned m_N, unsigned _storage_N> +netlist_time matrix_solver_sm_t<m_N, _storage_N>::compute_next_timestep() +{ + nl_double new_solver_timestep = m_params.m_max_timestep; + + if (m_params.m_dynamic) + { + /* + * FIXME: We should extend the logic to use either all nets or + * only output nets. + */ + for (unsigned k = 0, iN=N(); k < iN; k++) + { + analog_net_t *n = m_nets[k]; + + const nl_double DD_n = (n->Q_Analog() - m_last_V[k]); + const nl_double hn = current_timestep(); + + nl_double DD2 = (DD_n / hn - n->m_DD_n_m_1 / n->m_h_n_m_1) / (hn + n->m_h_n_m_1); + nl_double new_net_timestep; + + n->m_h_n_m_1 = hn; + n->m_DD_n_m_1 = DD_n; + if (nl_math::abs(DD2) > NL_FCONST(1e-30)) // avoid div-by-zero + new_net_timestep = nl_math::sqrt(m_params.m_lte / nl_math::abs(NL_FCONST(0.5)*DD2)); + else + new_net_timestep = m_params.m_max_timestep; + + if (new_net_timestep < new_solver_timestep) + new_solver_timestep = new_net_timestep; + + m_last_V[k] = n->Q_Analog(); + } + if (new_solver_timestep < m_params.m_min_timestep) + new_solver_timestep = m_params.m_min_timestep; + } + //if (new_solver_timestep > 10.0 * hn) + // new_solver_timestep = 10.0 * hn; + return netlist_time::from_double(new_solver_timestep); +} + +template <unsigned m_N, unsigned _storage_N> +ATTR_COLD void matrix_solver_sm_t<m_N, _storage_N>::add_term(int k, terminal_t *term) +{ + if (term->m_otherterm->net().isRailNet()) + { + m_rails_temp[k].add(term, -1, false); + } + else + { + int ot = get_net_idx(&term->m_otherterm->net()); + if (ot>=0) + { + m_terms[k]->add(term, ot, true); + } + /* Should this be allowed ? */ + else // if (ot<0) + { + m_rails_temp[k].add(term, ot, true); + log().fatal("found term with missing othernet {1}\n", term->name()); + } + } +} + + +template <unsigned m_N, unsigned _storage_N> +ATTR_COLD void matrix_solver_sm_t<m_N, _storage_N>::vsetup(analog_net_t::list_t &nets) +{ + if (m_dim < nets.size()) + log().fatal("Dimension {1} less than {2}", m_dim, nets.size()); + + for (unsigned k = 0; k < N(); k++) + { + m_terms[k]->clear(); + m_rails_temp[k].clear(); + } + + matrix_solver_t::setup_base(nets); + + for (unsigned k = 0; k < N(); k++) + { + m_terms[k]->m_railstart = m_terms[k]->count(); + for (unsigned i = 0; i < m_rails_temp[k].count(); i++) + this->m_terms[k]->add(m_rails_temp[k].terms()[i], m_rails_temp[k].net_other()[i], false); + + m_rails_temp[k].clear(); // no longer needed + m_terms[k]->set_pointers(); + } + +#if 1 + + /* Sort in descending order by number of connected matrix voltages. + * The idea is, that for Gauss-Seidel algo the first voltage computed + * depends on the greatest number of previous voltages thus taking into + * account the maximum amout of information. + * + * This actually improves performance on popeye slightly. Average + * GS computations reduce from 2.509 to 2.370 + * + * Smallest to largest : 2.613 + * Unsorted : 2.509 + * Largest to smallest : 2.370 + * + * Sorting as a general matrix pre-conditioning is mentioned in + * literature but I have found no articles about Gauss Seidel. + * + * For Gaussian Elimination however increasing order is better suited. + * FIXME: Even better would be to sort on elements right of the matrix diagonal. + * + */ + + int sort_order = (type() == GAUSS_SEIDEL ? 1 : -1); + + for (unsigned k = 0; k < N() / 2; k++) + for (unsigned i = 0; i < N() - 1; i++) + { + if ((m_terms[i]->m_railstart - m_terms[i+1]->m_railstart) * sort_order < 0) + { + std::swap(m_terms[i], m_terms[i+1]); + std::swap(m_nets[i], m_nets[i+1]); + } + } + + for (unsigned k = 0; k < N(); k++) + { + int *other = m_terms[k]->net_other(); + for (unsigned i = 0; i < m_terms[k]->count(); i++) + if (other[i] != -1) + other[i] = get_net_idx(&m_terms[k]->terms()[i]->m_otherterm->net()); + } + +#endif + + /* create a list of non zero elements right of the diagonal + * These list anticipate the population of array elements by + * Gaussian elimination. + */ + for (unsigned k = 0; k < N(); k++) + { + terms_t * t = m_terms[k]; + /* pretty brutal */ + int *other = t->net_other(); + + t->m_nz.clear(); + + if (k==0) + t->m_nzrd.clear(); + else + { + t->m_nzrd = m_terms[k-1]->m_nzrd; + unsigned j=0; + while(j < t->m_nzrd.size()) + { + if (t->m_nzrd[j] < k + 1) + t->m_nzrd.remove_at(j); + else + j++; + } + } + + for (unsigned j = 0; j < N(); j++) + { + for (unsigned i = 0; i < t->m_railstart; i++) + { + if (!t->m_nzrd.contains(other[i]) && other[i] >= (int) (k + 1)) + t->m_nzrd.push_back(other[i]); + if (!t->m_nz.contains(other[i])) + t->m_nz.push_back(other[i]); + } + } + /* and sort */ + psort_list(t->m_nzrd); + + t->m_nz.push_back(k); // add diagonal + + psort_list(t->m_nz); + } + + /* create a list of non zero elements below diagonal k + * This should reduce cache misses ... + */ + + bool touched[_storage_N][_storage_N] = { { false } }; + for (unsigned k = 0; k < N(); k++) + { + m_terms[k]->m_nzbd.clear(); + for (unsigned j = 0; j < m_terms[k]->m_nz.size(); j++) + touched[k][m_terms[k]->m_nz[j]] = true; + } + + for (unsigned k = 0; k < N(); k++) + { + for (unsigned row = k + 1; row < N(); row++) + { + if (touched[row][k]) + { + if (!m_terms[k]->m_nzbd.contains(row)) + m_terms[k]->m_nzbd.push_back(row); + for (unsigned col = k; col < N(); col++) + if (touched[k][col]) + touched[row][col] = true; + } + } + } + + if (0) + for (unsigned k = 0; k < N(); k++) + { + pstring line = pfmt("{1}")(k, "3"); + for (unsigned j = 0; j < m_terms[k]->m_nzrd.size(); j++) + line += pfmt(" {1}")(m_terms[k]->m_nzrd[j], "3"); + log().verbose("{1}", line); + } + + /* + * save states + */ + save(NLNAME(m_last_RHS)); + save(NLNAME(m_last_V)); + + for (unsigned k = 0; k < N(); k++) + { + pstring num = pfmt("{1}")(k); + + save(RHS(k), "RHS" + num); + + save(m_terms[k]->go(),"GO" + num, m_terms[k]->count()); + save(m_terms[k]->gt(),"GT" + num, m_terms[k]->count()); + save(m_terms[k]->Idr(),"IDR" + num , m_terms[k]->count()); + } + +} + + +template <unsigned m_N, unsigned _storage_N> +void matrix_solver_sm_t<m_N, _storage_N>::build_LE_A() +{ + const unsigned iN = N(); + for (unsigned k = 0; k < iN; k++) + { + for (unsigned i=0; i < iN; i++) + A(k,i) = 0.0; + + const unsigned terms_count = m_terms[k]->count(); + const unsigned railstart = m_terms[k]->m_railstart; + const nl_double * RESTRICT gt = m_terms[k]->gt(); + + { + nl_double akk = 0.0; + for (unsigned i = 0; i < terms_count; i++) + akk += gt[i]; + + A(k,k) = akk; + } + + const nl_double * RESTRICT go = m_terms[k]->go(); + const int * RESTRICT net_other = m_terms[k]->net_other(); + + for (unsigned i = 0; i < railstart; i++) + A(k,net_other[i]) -= go[i]; + } +} + +template <unsigned m_N, unsigned _storage_N> +void matrix_solver_sm_t<m_N, _storage_N>::build_LE_RHS() +{ + const unsigned iN = N(); + for (unsigned k = 0; k < iN; k++) + { + nl_double rhsk_a = 0.0; + nl_double rhsk_b = 0.0; + + const int terms_count = m_terms[k]->count(); + const nl_double * RESTRICT go = m_terms[k]->go(); + const nl_double * RESTRICT Idr = m_terms[k]->Idr(); + const nl_double * const * RESTRICT other_cur_analog = m_terms[k]->other_curanalog(); + + for (int i = 0; i < terms_count; i++) + rhsk_a = rhsk_a + Idr[i]; + + for (int i = m_terms[k]->m_railstart; i < terms_count; i++) + //rhsk = rhsk + go[i] * terms[i]->m_otherterm->net().as_analog().Q_Analog(); + rhsk_b = rhsk_b + go[i] * *other_cur_analog[i]; + + RHS(k) = rhsk_a + rhsk_b; + } +} + +template <unsigned m_N, unsigned _storage_N> +void matrix_solver_sm_t<m_N, _storage_N>::LE_invert() +{ + const unsigned kN = N(); + + for (unsigned i = 0; i < kN; i++) + { + for (unsigned j = 0; j < kN; j++) + { + W(i,j) = lA(i,j) = A(i,j); + Ainv(i,j) = 0.0; + } + Ainv(i,i) = 1.0; + } + /* down */ + for (unsigned i = 0; i < kN; i++) + { + /* FIXME: Singular matrix? */ + const nl_double f = 1.0 / W(i,i); + const unsigned * RESTRICT const p = m_terms[i]->m_nzrd.data(); + const unsigned e = m_terms[i]->m_nzrd.size(); + + /* Eliminate column i from row j */ + + const unsigned * RESTRICT const pb = m_terms[i]->m_nzbd.data(); + const unsigned eb = m_terms[i]->m_nzbd.size(); + for (unsigned jb = 0; jb < eb; jb++) + { + const unsigned j = pb[jb]; + const nl_double f1 = - W(j,i) * f; + if (f1 != 0.0) + { + for (unsigned k = 0; k < e; k++) + W(j,p[k]) += W(i,p[k]) * f1; + for (unsigned k = 0; k <= i; k ++) + Ainv(j,k) += Ainv(i,k) * f1; + } + } + } + /* up */ + for (int i = kN - 1; i >= 0; i--) + { + /* FIXME: Singular matrix? */ + const nl_double f = 1.0 / W(i,i); + for (int j = i - 1; j>=0; j--) + { + const nl_double f1 = - W(j,i) * f; + if (f1 != 0.0) + { + for (unsigned k = i; k < kN; k++) + W(j,k) += W(i,k) * f1; + for (unsigned k = 0; k < kN; k++) + Ainv(j,k) += Ainv(i,k) * f1; + } + } + for (unsigned k = 0; k < kN; k++) + { + Ainv(i,k) *= f; + lAinv(i,k) = Ainv(i,k); + } + } +} + +template <unsigned m_N, unsigned _storage_N> +template <typename T> +void matrix_solver_sm_t<m_N, _storage_N>::LE_compute_x( + T * RESTRICT x) +{ + const unsigned kN = N(); + + for (int i=0; i<kN; i++) + x[i] = 0.0; + + for (int k=0; k<kN; k++) + { + for (int i=0; i<kN; i++) + x[i] += Ainv(i,k) * RHS(k); + } +} + + +template <unsigned m_N, unsigned _storage_N> +template <typename T> +T matrix_solver_sm_t<m_N, _storage_N>::delta( + const T * RESTRICT V) +{ + /* FIXME: Ideally we should also include currents (RHS) here. This would + * need a revaluation of the right hand side after voltages have been updated + * and thus belong into a different calculation. This applies to all solvers. + */ + + const unsigned iN = this->N(); + T cerr = 0; + for (unsigned i = 0; i < iN; i++) + cerr = std::fmax(cerr, nl_math::abs(V[i] - (T) this->m_nets[i]->m_cur_Analog)); + return cerr; +} + +template <unsigned m_N, unsigned _storage_N> +template <typename T> +void matrix_solver_sm_t<m_N, _storage_N>::store( + const T * RESTRICT V) +{ + for (unsigned i = 0, iN=N(); i < iN; i++) + { + this->m_nets[i]->m_cur_Analog = V[i]; + } +} + + +template <unsigned m_N, unsigned _storage_N> +int matrix_solver_sm_t<m_N, _storage_N>::solve_non_dynamic(ATTR_UNUSED const bool newton_raphson) +{ + static uint cnt = 0; + + nl_double new_V[_storage_N]; // = { 0.0 }; + + if (0 || (cnt % 100 == 0)) + { + /* complete calculation */ + this->LE_invert(); + } + else + { + const auto iN = N(); + for (int row = 0; row < iN; row ++) + for (int k = 0; k < iN; k++) + Ainv(row,k) = lAinv(row, k); + + for (int row = 0; row < N(); row ++) + { + nl_double v[m_pitch]; + bool changed = false; + for (int k = 0; k < N(); k++) + v[k] = A(row,k) - lA(row,k); + for (int k = 0; k < N(); k++) + if (v[k] != 0.0) + { + changed = true; + break; + } + + if (changed) + { + nl_double lamba = 0.0; + nl_double w[m_pitch] = {0}; + nl_double z[m_pitch] = {0}; + /* compute w and lamba */ + for (int k = 0; k < N(); k++) + { + for (int j=0; j<N(); j++) + w[k] += Ainv(j,k) * v[j]; /* Transpose(Ainv) * v */ + z[k] = Ainv(k, row); /* u is row'th column */ + lamba += v[k] * z[k]; + } + lamba = -1.0 / (1.0 + lamba); + for (int i=0; i<N(); i++) + for (int k = 0; k < N(); k++) + Ainv(i,k) += lamba * z[i] * w[k]; + } + + } + } + + cnt++; + + this->LE_compute_x(new_V); + + if (newton_raphson) + { + nl_double err = delta(new_V); + + store(new_V); + + return (err > this->m_params.m_accuracy) ? 2 : 1; + } + else + { + store(new_V); + return 1; + } +} + +template <unsigned m_N, unsigned _storage_N> +inline int matrix_solver_sm_t<m_N, _storage_N>::vsolve_non_dynamic(const bool newton_raphson) +{ + this->build_LE_A(); + this->build_LE_RHS(); + + for (unsigned i=0, iN=N(); i < iN; i++) + m_last_RHS[i] = RHS(i); + + this->m_stat_calculations++; + return this->solve_non_dynamic(newton_raphson); +} + +template <unsigned m_N, unsigned _storage_N> +matrix_solver_sm_t<m_N, _storage_N>::matrix_solver_sm_t(const solver_parameters_t *params, const int size) +: matrix_solver_t(GAUSSIAN_ELIMINATION, params) +, m_dim(size) +{ + m_rails_temp = palloc_array(terms_t, N()); +#if (NL_USE_DYNAMIC_ALLOCATION) + m_A = palloc_array(nl_ext_double, N() * m_pitch); +#endif + for (unsigned k = 0; k < N(); k++) + { + m_terms[k] = palloc(terms_t); + m_last_RHS[k] = 0.0; + m_last_V[k] = 0.0; + } +} + +template <unsigned m_N, unsigned _storage_N> +matrix_solver_sm_t<m_N, _storage_N>::matrix_solver_sm_t(const eSolverType type, const solver_parameters_t *params, const int size) +: matrix_solver_t(type, params) +, m_dim(size) +{ + m_rails_temp = palloc_array(terms_t, N()); +#if (NL_USE_DYNAMIC_ALLOCATION) + m_A = palloc_array(nl_ext_double, N() * m_pitch); +#endif + for (unsigned k = 0; k < N(); k++) + { + m_terms[k] = palloc(terms_t); + m_last_RHS[k] = 0.0; + m_last_V[k] = 0.0; + } +} + +NETLIB_NAMESPACE_DEVICES_END() + +#endif /* NLD_MS_DIRECT_H_ */ |