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author | Alan Mishchenko <alanmi@berkeley.edu> | 2020-11-12 23:57:46 -0800 |
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committer | Alan Mishchenko <alanmi@berkeley.edu> | 2020-11-12 23:57:46 -0800 |
commit | b3d3f7dd3aeb5c7648caf9c424f6dc341ad27ac0 (patch) | |
tree | 5992530768352a723b03e17698845b8aca6e9649 /src/sat/glucose2/Glucose2.cpp | |
parent | 890aa684ab44a09c2e6af4ec50d438506a8fbecb (diff) | |
download | abc-b3d3f7dd3aeb5c7648caf9c424f6dc341ad27ac0.tar.gz abc-b3d3f7dd3aeb5c7648caf9c424f6dc341ad27ac0.tar.bz2 abc-b3d3f7dd3aeb5c7648caf9c424f6dc341ad27ac0.zip |
Duplicating Glucose package.
Diffstat (limited to 'src/sat/glucose2/Glucose2.cpp')
-rw-r--r-- | src/sat/glucose2/Glucose2.cpp | 1503 |
1 files changed, 1503 insertions, 0 deletions
diff --git a/src/sat/glucose2/Glucose2.cpp b/src/sat/glucose2/Glucose2.cpp new file mode 100644 index 00000000..00d8b57a --- /dev/null +++ b/src/sat/glucose2/Glucose2.cpp @@ -0,0 +1,1503 @@ +/***************************************************************************************[Solver.cc] + Glucose -- Copyright (c) 2013, Gilles Audemard, Laurent Simon + CRIL - Univ. Artois, France + LRI - Univ. Paris Sud, France + +Glucose sources are based on MiniSat (see below MiniSat copyrights). Permissions and copyrights of +Glucose are exactly the same as Minisat on which it is based on. (see below). + +--------------- + +Copyright (c) 2003-2006, Niklas Een, Niklas Sorensson +Copyright (c) 2007-2010, Niklas Sorensson + +Permission is hereby granted, free of charge, to any person obtaining a copy of this software and +associated documentation files (the "Software"), to deal in the Software without restriction, +including without limitation the rights to use, copy, modify, merge, publish, distribute, +sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all copies or +substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT +NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND +NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, +DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT +OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. +**************************************************************************************************/ + +#include <math.h> + +#include "sat/glucose2/Sort.h" +#include "sat/glucose2/Solver.h" +#include "sat/glucose2/Constants.h" +#include "sat/glucose2/System.h" + +ABC_NAMESPACE_IMPL_START + +using namespace Gluco2; + +//================================================================================================= +// Options: + +static const char* _cat = "CORE"; +static const char* _cr = "CORE -- RESTART"; +static const char* _cred = "CORE -- REDUCE"; +static const char* _cm = "CORE -- MINIMIZE"; +static const char* _certified = "CORE -- CERTIFIED UNSAT"; + + + + +static BoolOption opt_incremental (_cat,"incremental", "Use incremental SAT solving", false); +static DoubleOption opt_K (_cr, "K", "The constant used to force restart", 0.8, DoubleRange(0, false, 1, false)); +static DoubleOption opt_R (_cr, "R", "The constant used to block restart", 1.4, DoubleRange(1, false, 5, false)); +static IntOption opt_size_lbd_queue (_cr, "szLBDQueue", "The size of moving average for LBD (restarts)", 50, IntRange(10, INT32_MAX)); +static IntOption opt_size_trail_queue (_cr, "szTrailQueue", "The size of moving average for trail (block restarts)", 5000, IntRange(10, INT32_MAX)); + +static IntOption opt_first_reduce_db (_cred, "firstReduceDB", "The number of conflicts before the first reduce DB", 2000, IntRange(0, INT32_MAX)); +static IntOption opt_inc_reduce_db (_cred, "incReduceDB", "Increment for reduce DB", 300, IntRange(0, INT32_MAX)); +static IntOption opt_spec_inc_reduce_db (_cred, "specialIncReduceDB", "Special increment for reduce DB", 1000, IntRange(0, INT32_MAX)); +static IntOption opt_lb_lbd_frozen_clause (_cred, "minLBDFrozenClause", "Protect clauses if their LBD decrease and is lower than (for one turn)", 30, IntRange(0, INT32_MAX)); + +static IntOption opt_lb_size_minimzing_clause (_cm, "minSizeMinimizingClause", "The min size required to minimize clause", 30, IntRange(3, INT32_MAX)); +static IntOption opt_lb_lbd_minimzing_clause (_cm, "minLBDMinimizingClause", "The min LBD required to minimize clause", 6, IntRange(3, INT32_MAX)); + + +static DoubleOption opt_var_decay (_cat, "var-decay", "The variable activity decay factor", 0.8, DoubleRange(0, false, 1, false)); +static DoubleOption opt_clause_decay (_cat, "cla-decay", "The clause activity decay factor", 0.999, DoubleRange(0, false, 1, false)); +static DoubleOption opt_random_var_freq (_cat, "rnd-freq", "The frequency with which the decision heuristic tries to choose a random variable", 0, DoubleRange(0, true, 1, true)); +static DoubleOption opt_random_seed (_cat, "rnd-seed", "Used by the random variable selection", 91648253, DoubleRange(0, false, HUGE_VAL, false)); +static IntOption opt_ccmin_mode (_cat, "ccmin-mode", "Controls conflict clause minimization (0=none, 1=basic, 2=deep)", 2, IntRange(0, 2)); +static IntOption opt_phase_saving (_cat, "phase-saving", "Controls the level of phase saving (0=none, 1=limited, 2=full)", 2, IntRange(0, 2)); +static BoolOption opt_rnd_init_act (_cat, "rnd-init", "Randomize the initial activity", false); +/* +static IntOption opt_restart_first (_cat, "rfirst", "The base restart interval", 100, IntRange(1, INT32_MAX)); +static DoubleOption opt_restart_inc (_cat, "rinc", "Restart interval increase factor", 2, DoubleRange(1, false, HUGE_VAL, false)); +*/ +static DoubleOption opt_garbage_frac (_cat, "gc-frac", "The fraction of wasted memory allowed before a garbage collection is triggered", 0.20, DoubleRange(0, false, HUGE_VAL, false)); + + +BoolOption opt_certified_ (_certified, "certified", "Certified UNSAT using DRUP format", false ); +StringOption opt_certified_file_ (_certified, "certified-output", "Certified UNSAT output file", "NULL"); + + +//================================================================================================= +// Constructor/Destructor: + + +Solver::Solver() : + + // Parameters (user settable): + // + SolverType(0) + , pCnfFunc(NULL) + , nCallConfl(1000) + , terminate_search_early(false) + , pstop(NULL) + , nRuntimeLimit(0) + + , verbosity (0) + , verbEveryConflicts(10000) + , showModel (0) + , K (opt_K) + , R (opt_R) + , sizeLBDQueue (opt_size_lbd_queue) + , sizeTrailQueue (opt_size_trail_queue) + , firstReduceDB (opt_first_reduce_db) + , incReduceDB (opt_inc_reduce_db) + , specialIncReduceDB (opt_spec_inc_reduce_db) + , lbLBDFrozenClause (opt_lb_lbd_frozen_clause) + , lbSizeMinimizingClause (opt_lb_size_minimzing_clause) + , lbLBDMinimizingClause (opt_lb_lbd_minimzing_clause) + , var_decay (opt_var_decay) + , clause_decay (opt_clause_decay) + , random_var_freq (opt_random_var_freq) + , random_seed (opt_random_seed) + , ccmin_mode (opt_ccmin_mode) + , phase_saving (opt_phase_saving) + , rnd_pol (false) + , rnd_init_act (opt_rnd_init_act) + , garbage_frac (opt_garbage_frac) + , certifiedOutput (NULL) + , certifiedUNSAT (opt_certified_) + // Statistics: (formerly in 'SolverStats') + // + , nbRemovedClauses(0),nbReducedClauses(0), nbDL2(0),nbBin(0),nbUn(0) , nbReduceDB(0) + , solves(0), starts(0), decisions(0), rnd_decisions(0), propagations(0),conflicts(0),conflictsRestarts(0),nbstopsrestarts(0),nbstopsrestartssame(0),lastblockatrestart(0) + , dec_vars(0), clauses_literals(0), learnts_literals(0), max_literals(0), tot_literals(0) + , curRestart(1) + + , ok (true) + , cla_inc (1) + , var_inc (1) + , watches (WatcherDeleted(ca)) + , watchesBin (WatcherDeleted(ca)) + , qhead (0) + , simpDB_assigns (-1) + , simpDB_props (0) + , order_heap (VarOrderLt(activity)) + , progress_estimate (0) + , remove_satisfied (true) + + // Resource constraints: + // + , conflict_budget (-1) + , propagation_budget (-1) + , asynch_interrupt (false) + , incremental(opt_incremental) + , nbVarsInitialFormula(INT32_MAX) +{ + MYFLAG=0; + // Initialize only first time. Useful for incremental solving, useless otherwise + lbdQueue.initSize(sizeLBDQueue); + trailQueue.initSize(sizeTrailQueue); + sumLBD = 0; + nbclausesbeforereduce = firstReduceDB; + totalTime4Sat=0;totalTime4Unsat=0; + nbSatCalls=0;nbUnsatCalls=0; + + + if(certifiedUNSAT) { + if(!strcmp(opt_certified_file_,"NULL")) { + certifiedOutput = fopen("/dev/stdout", "wb"); + } else { + certifiedOutput = fopen(opt_certified_file_, "wb"); + } + // fprintf(certifiedOutput,"o proof DRUP\n"); + } +} + + +Solver::~Solver() +{ +} + + +/**************************************************************** + Set the incremental mode +****************************************************************/ + +// This function set the incremental mode to true. +// You can add special code for this mode here. + +void Solver::setIncrementalMode() { + incremental = true; +} + +// Number of variables without selectors +void Solver::initNbInitialVars(int nb) { + nbVarsInitialFormula = nb; +} + + +//================================================================================================= +// Minor methods: + + +// Creates a new SAT variable in the solver. If 'decision' is cleared, variable will not be +// used as a decision variable (NOTE! This has effects on the meaning of a SATISFIABLE result). +// +Var Solver::newVar(bool sign, bool dvar) +{ + int v = nVars(); + watches .init(mkLit(v, false)); + watches .init(mkLit(v, true )); + watchesBin .init(mkLit(v, false)); + watchesBin .init(mkLit(v, true )); + assigns .push(l_Undef); + vardata .push(mkVarData(CRef_Undef, 0)); + //activity .push(0); + activity .push(rnd_init_act ? drand(random_seed) * 0.00001 : 0); + seen .push(0); + permDiff .push(0); + polarity .push(sign); + decision .push(); + trail .capacity(v+1); + setDecisionVar(v, dvar); + return v; +} + + + +bool Solver::addClause_(vec<Lit>& ps) +{ + assert(decisionLevel() == 0); + if (!ok) return false; + + if ( 0 ) { + for ( int i = 0; i < ps.size(); i++ ) + printf( "%s%d ", (toInt(ps[i]) & 1) ? "-":"", toInt(ps[i]) >> 1 ); + printf( "\n" ); + } + + // Check if clause is satisfied and remove false/duplicate literals: + sort(ps); + + vec<Lit> oc; + oc.clear(); + + Lit p; int i, j, flag = 0; + if(certifiedUNSAT) { + for (i = j = 0, p = lit_Undef; i < ps.size(); i++) { + oc.push(ps[i]); + if (value(ps[i]) == l_True || ps[i] == ~p || value(ps[i]) == l_False) + flag = 1; + } + } + + for (i = j = 0, p = lit_Undef; i < ps.size(); i++) + if (value(ps[i]) == l_True || ps[i] == ~p) + return true; + else if (value(ps[i]) != l_False && ps[i] != p) + ps[j++] = p = ps[i]; + ps.shrink(i - j); + + if ( 0 ) { + for ( int i = 0; i < ps.size(); i++ ) + printf( "%s%d ", (toInt(ps[i]) & 1) ? "-":"", toInt(ps[i]) >> 1 ); + printf( "\n" ); + } + + if (flag && (certifiedUNSAT)) { + for (i = j = 0, p = lit_Undef; i < ps.size(); i++) + fprintf(certifiedOutput, "%i ", (var(ps[i]) + 1) * (-2 * sign(ps[i]) + 1)); + fprintf(certifiedOutput, "0\n"); + + fprintf(certifiedOutput, "d "); + for (i = j = 0, p = lit_Undef; i < oc.size(); i++) + fprintf(certifiedOutput, "%i ", (var(oc[i]) + 1) * (-2 * sign(oc[i]) + 1)); + fprintf(certifiedOutput, "0\n"); + } + + if (ps.size() == 0) + return ok = false; + else if (ps.size() == 1){ + uncheckedEnqueue(ps[0]); + return ok = (propagate() == CRef_Undef); + }else{ + CRef cr = ca.alloc(ps, false); + clauses.push(cr); + attachClause(cr); + } + + return true; +} + + +void Solver::attachClause(CRef cr) { + const Clause& c = ca[cr]; + + assert(c.size() > 1); + if(c.size()==2) { + watchesBin[~c[0]].push(Watcher(cr, c[1])); + watchesBin[~c[1]].push(Watcher(cr, c[0])); + } else { + watches[~c[0]].push(Watcher(cr, c[1])); + watches[~c[1]].push(Watcher(cr, c[0])); + } + if (c.learnt()) learnts_literals += c.size(); + else clauses_literals += c.size(); } + + + + +void Solver::detachClause(CRef cr, bool strict) { + const Clause& c = ca[cr]; + + assert(c.size() > 1); + if(c.size()==2) { + if (strict){ + remove(watchesBin[~c[0]], Watcher(cr, c[1])); + remove(watchesBin[~c[1]], Watcher(cr, c[0])); + }else{ + // Lazy detaching: (NOTE! Must clean all watcher lists before garbage collecting this clause) + watchesBin.smudge(~c[0]); + watchesBin.smudge(~c[1]); + } + } else { + if (strict){ + remove(watches[~c[0]], Watcher(cr, c[1])); + remove(watches[~c[1]], Watcher(cr, c[0])); + }else{ + // Lazy detaching: (NOTE! Must clean all watcher lists before garbage collecting this clause) + watches.smudge(~c[0]); + watches.smudge(~c[1]); + } + } + if (c.learnt()) learnts_literals -= c.size(); + else clauses_literals -= c.size(); } + + +void Solver::removeClause(CRef cr) { + + Clause& c = ca[cr]; + + if (certifiedUNSAT) { + fprintf(certifiedOutput, "d "); + for (int i = 0; i < c.size(); i++) + fprintf(certifiedOutput, "%i ", (var(c[i]) + 1) * (-2 * sign(c[i]) + 1)); + fprintf(certifiedOutput, "0\n"); + } + + detachClause(cr); + // Don't leave pointers to free'd memory! + if (locked(c)) vardata[var(c[0])].reason = CRef_Undef; + c.mark(1); + ca.free_(cr); +} + + +bool Solver::satisfied(const Clause& c) const { + if(incremental) // Check clauses with many selectors is too time consuming + return (value(c[0]) == l_True) || (value(c[1]) == l_True); + + // Default mode. + for (int i = 0; i < c.size(); i++) + if (value(c[i]) == l_True) + return true; + return false; +} + +/************************************************************ + * Compute LBD functions + *************************************************************/ + +inline unsigned int Solver::computeLBD(const vec<Lit> & lits,int end) { + int nblevels = 0; + MYFLAG++; + + if(incremental) { // ----------------- INCREMENTAL MODE + if(end==-1) end = lits.size(); + unsigned int nbDone = 0; + for(int i=0;i<lits.size();i++) { + if(nbDone>=end) break; + if(isSelector(var(lits[i]))) continue; + nbDone++; + int l = level(var(lits[i])); + if (permDiff[l] != MYFLAG) { + permDiff[l] = MYFLAG; + nblevels++; + } + } + } else { // -------- DEFAULT MODE. NOT A LOT OF DIFFERENCES... BUT EASIER TO READ + for(int i=0;i<lits.size();i++) { + int l = level(var(lits[i])); + if (permDiff[l] != MYFLAG) { + permDiff[l] = MYFLAG; + nblevels++; + } + } + } + + return nblevels; +} + +inline unsigned int Solver::computeLBD(const Clause &c) { + int nblevels = 0; + MYFLAG++; + + if(incremental) { // ----------------- INCREMENTAL MODE + int nbDone = 0; + for(int i=0;i<c.size();i++) { + if(nbDone>=c.sizeWithoutSelectors()) break; + if(isSelector(var(c[i]))) continue; + nbDone++; + int l = level(var(c[i])); + if (permDiff[l] != MYFLAG) { + permDiff[l] = MYFLAG; + nblevels++; + } + } + } else { // -------- DEFAULT MODE. NOT A LOT OF DIFFERENCES... BUT EASIER TO READ + for(int i=0;i<c.size();i++) { + int l = level(var(c[i])); + if (permDiff[l] != MYFLAG) { + permDiff[l] = MYFLAG; + nblevels++; + } + } + } + return nblevels; +} + + +/****************************************************************** + * Minimisation with binary reolution + ******************************************************************/ +void Solver::minimisationWithBinaryResolution(vec<Lit> &out_learnt) { + + // Find the LBD measure + unsigned int lbd = computeLBD(out_learnt); + Lit p = ~out_learnt[0]; + + if(lbd<=lbLBDMinimizingClause){ + MYFLAG++; + + for(int i = 1;i<out_learnt.size();i++) { + permDiff[var(out_learnt[i])] = MYFLAG; + } + + vec<Watcher>& wbin = watchesBin[p]; + int nb = 0; + for(int k = 0;k<wbin.size();k++) { + Lit imp = wbin[k].blocker; + if(permDiff[var(imp)]==MYFLAG && value(imp)==l_True) { + nb++; + permDiff[var(imp)]= MYFLAG-1; + } + } + int l = out_learnt.size()-1; + if(nb>0) { + nbReducedClauses++; + for(int i = 1;i<out_learnt.size()-nb;i++) { + if(permDiff[var(out_learnt[i])]!=MYFLAG) { + Lit p = out_learnt[l]; + out_learnt[l] = out_learnt[i]; + out_learnt[i] = p; + l--;i--; + } + } + + out_learnt.shrink(nb); + + } + } +} + +// Revert to the state at given level (keeping all assignment at 'level' but not beyond). +// +void Solver::cancelUntil(int level) { + if (decisionLevel() > level){ + for (int c = trail.size()-1; c >= trail_lim[level]; c--){ + Var x = var(trail[c]); + assigns [x] = l_Undef; + if (phase_saving > 1 || ((phase_saving == 1) && c > trail_lim.last())) + polarity[x] = sign(trail[c]); + insertVarOrder(x); } + qhead = trail_lim[level]; + trail.shrink(trail.size() - trail_lim[level]); + trail_lim.shrink(trail_lim.size() - level); + } +} + + +//================================================================================================= +// Major methods: + + +Lit Solver::pickBranchLit() +{ + Var next = var_Undef; + + // Random decision: + if (drand(random_seed) < random_var_freq && !order_heap.empty()){ + next = order_heap[irand(random_seed,order_heap.size())]; + if (value(next) == l_Undef && decision[next]) + rnd_decisions++; } + + // Activity based decision: + while (next == var_Undef || value(next) != l_Undef || !decision[next]) + if (order_heap.empty()){ + next = var_Undef; + break; + }else + next = order_heap.removeMin(); + + return next == var_Undef ? lit_Undef : mkLit(next, rnd_pol ? drand(random_seed) < 0.5 : (polarity[next] != 0)); +} + + +/*_________________________________________________________________________________________________ +| +| analyze : (confl : Clause*) (out_learnt : vec<Lit>&) (out_btlevel : int&) -> [void] +| +| Description: +| Analyze conflict and produce a reason clause. +| +| Pre-conditions: +| * 'out_learnt' is assumed to be cleared. +| * Current decision level must be greater than root level. +| +| Post-conditions: +| * 'out_learnt[0]' is the asserting literal at level 'out_btlevel'. +| * If out_learnt.size() > 1 then 'out_learnt[1]' has the greatest decision level of the +| rest of literals. There may be others from the same level though. +| +|________________________________________________________________________________________________@*/ +void Solver::analyze(CRef confl, vec<Lit>& out_learnt,vec<Lit>&selectors, int& out_btlevel,unsigned int &lbd,unsigned int &szWithoutSelectors) +{ + int pathC = 0; + Lit p = lit_Undef; + + // Generate conflict clause: + // + out_learnt.push(); // (leave room for the asserting literal) + int index = trail.size() - 1; + + do{ + assert(confl != CRef_Undef); // (otherwise should be UIP) + Clause& c = ca[confl]; + + // Special case for binary clauses + // The first one has to be SAT + if( p != lit_Undef && c.size()==2 && value(c[0])==l_False) { + + assert(value(c[1])==l_True); + Lit tmp = c[0]; + c[0] = c[1], c[1] = tmp; + } + + if (c.learnt()) + claBumpActivity(c); + +#ifdef DYNAMICNBLEVEL + // DYNAMIC NBLEVEL trick (see competition'09 companion paper) + if(c.learnt() && c.lbd()>2) { + unsigned int nblevels = computeLBD(c); + if(nblevels+1<c.lbd() ) { // improve the LBD + if(c.lbd()<=lbLBDFrozenClause) { + c.setCanBeDel(false); + } + // seems to be interesting : keep it for the next round + c.setLBD(nblevels); // Update it + } + } +#endif + + + for (int j = (p == lit_Undef) ? 0 : 1; j < c.size(); j++){ + Lit q = c[j]; + + if (!seen[var(q)] && level(var(q)) > 0){ + if(!isSelector(var(q))) + varBumpActivity(var(q)); + seen[var(q)] = 1; + if (level(var(q)) >= decisionLevel()) { + pathC++; +#ifdef UPDATEVARACTIVITY + // UPDATEVARACTIVITY trick (see competition'09 companion paper) + if(!isSelector(var(q)) && (reason(var(q))!= CRef_Undef) && ca[reason(var(q))].learnt()) + lastDecisionLevel.push(q); +#endif + + } else { + if(isSelector(var(q))) { + assert(value(q) == l_False); + selectors.push(q); + } else + out_learnt.push(q); + } + } + } + + // Select next clause to look at: + while (!seen[var(trail[index--])]); + p = trail[index+1]; + confl = reason(var(p)); + seen[var(p)] = 0; + pathC--; + + }while (pathC > 0); + out_learnt[0] = ~p; + + // Simplify conflict clause: + // + int i, j; + + for(i = 0;i<selectors.size();i++) + out_learnt.push(selectors[i]); + + out_learnt.copyTo(analyze_toclear); + if (ccmin_mode == 2){ + uint32_t abstract_level = 0; + for (i = 1; i < out_learnt.size(); i++) + abstract_level |= abstractLevel(var(out_learnt[i])); // (maintain an abstraction of levels involved in conflict) + + for (i = j = 1; i < out_learnt.size(); i++) + if (reason(var(out_learnt[i])) == CRef_Undef || !litRedundant(out_learnt[i], abstract_level)) + out_learnt[j++] = out_learnt[i]; + + }else if (ccmin_mode == 1){ + for (i = j = 1; i < out_learnt.size(); i++){ + Var x = var(out_learnt[i]); + + if (reason(x) == CRef_Undef) + out_learnt[j++] = out_learnt[i]; + else{ + Clause& c = ca[reason(var(out_learnt[i]))]; + // Thanks to Siert Wieringa for this bug fix! + for (int k = ((c.size()==2) ? 0:1); k < c.size(); k++) + if (!seen[var(c[k])] && level(var(c[k])) > 0){ + out_learnt[j++] = out_learnt[i]; + break; } + } + } + }else + i = j = out_learnt.size(); + + max_literals += out_learnt.size(); + out_learnt.shrink(i - j); + tot_literals += out_learnt.size(); + + + /* *************************************** + Minimisation with binary clauses of the asserting clause + First of all : we look for small clauses + Then, we reduce clauses with small LBD. + Otherwise, this can be useless + */ + if(!incremental && out_learnt.size()<=lbSizeMinimizingClause) { + minimisationWithBinaryResolution(out_learnt); + } + // Find correct backtrack level: + // + if (out_learnt.size() == 1) + out_btlevel = 0; + else{ + int max_i = 1; + // Find the first literal assigned at the next-highest level: + for (int i = 2; i < out_learnt.size(); i++) + if (level(var(out_learnt[i])) > level(var(out_learnt[max_i]))) + max_i = i; + // Swap-in this literal at index 1: + Lit p = out_learnt[max_i]; + out_learnt[max_i] = out_learnt[1]; + out_learnt[1] = p; + out_btlevel = level(var(p)); + } + + + // Compute the size of the clause without selectors (incremental mode) + if(incremental) { + szWithoutSelectors = 0; + for(int i=0;i<out_learnt.size();i++) { + if(!isSelector(var((out_learnt[i])))) szWithoutSelectors++; + else if(i>0) break; + } + } else + szWithoutSelectors = out_learnt.size(); + + // Compute LBD + lbd = computeLBD(out_learnt,out_learnt.size()-selectors.size()); + + +#ifdef UPDATEVARACTIVITY + // UPDATEVARACTIVITY trick (see competition'09 companion paper) + if(lastDecisionLevel.size()>0) { + for(int i = 0;i<lastDecisionLevel.size();i++) { + if(ca[reason(var(lastDecisionLevel[i]))].lbd()<lbd) + varBumpActivity(var(lastDecisionLevel[i])); + } + lastDecisionLevel.clear(); + } +#endif + + + + for (j = 0; j < analyze_toclear.size(); j++) seen[var(analyze_toclear[j])] = 0; // ('seen[]' is now cleared) + for(j = 0 ; j<selectors.size() ; j++) seen[var(selectors[j])] = 0; +} + + +// Check if 'p' can be removed. 'abstract_levels' is used to abort early if the algorithm is +// visiting literals at levels that cannot be removed later. +bool Solver::litRedundant(Lit p, uint32_t abstract_levels) +{ + analyze_stack.clear(); analyze_stack.push(p); + int top = analyze_toclear.size(); + while (analyze_stack.size() > 0){ + assert(reason(var(analyze_stack.last())) != CRef_Undef); + Clause& c = ca[reason(var(analyze_stack.last()))]; analyze_stack.pop(); + if(c.size()==2 && value(c[0])==l_False) { + assert(value(c[1])==l_True); + Lit tmp = c[0]; + c[0] = c[1], c[1] = tmp; + } + + for (int i = 1; i < c.size(); i++){ + Lit p = c[i]; + if (!seen[var(p)] && level(var(p)) > 0){ + if (reason(var(p)) != CRef_Undef && (abstractLevel(var(p)) & abstract_levels) != 0){ + seen[var(p)] = 1; + analyze_stack.push(p); + analyze_toclear.push(p); + }else{ + for (int j = top; j < analyze_toclear.size(); j++) + seen[var(analyze_toclear[j])] = 0; + analyze_toclear.shrink(analyze_toclear.size() - top); + return false; + } + } + } + } + + return true; +} + + +/*_________________________________________________________________________________________________ +| +| analyzeFinal : (p : Lit) -> [void] +| +| Description: +| Specialized analysis procedure to express the final conflict in terms of assumptions. +| Calculates the (possibly empty) set of assumptions that led to the assignment of 'p', and +| stores the result in 'out_conflict'. +|________________________________________________________________________________________________@*/ +void Solver::analyzeFinal(Lit p, vec<Lit>& out_conflict) +{ + out_conflict.clear(); + out_conflict.push(p); + + if (decisionLevel() == 0) + return; + + seen[var(p)] = 1; + + for (int i = trail.size()-1; i >= trail_lim[0]; i--){ + Var x = var(trail[i]); + if (seen[x]){ + if (reason(x) == CRef_Undef){ + assert(level(x) > 0); + out_conflict.push(~trail[i]); + }else{ + Clause& c = ca[reason(x)]; + // for (int j = 1; j < c.size(); j++) Minisat (glucose 2.0) loop + // Bug in case of assumptions due to special data structures for Binary. + // Many thanks to Sam Bayless (sbayless@cs.ubc.ca) for discover this bug. + for (int j = ((c.size()==2) ? 0:1); j < c.size(); j++) + if (level(var(c[j])) > 0) + seen[var(c[j])] = 1; + } + + seen[x] = 0; + } + } + + seen[var(p)] = 0; +} + + +void Solver::uncheckedEnqueue(Lit p, CRef from) +{ + assert(value(p) == l_Undef); + assigns[var(p)] = lbool(!sign(p)); + vardata[var(p)] = mkVarData(from, decisionLevel()); + trail.push_(p); +} + + +/*_________________________________________________________________________________________________ +| +| propagate : [void] -> [Clause*] +| +| Description: +| Propagates all enqueued facts. If a conflict arises, the conflicting clause is returned, +| otherwise CRef_Undef. +| +| Post-conditions: +| * the propagation queue is empty, even if there was a conflict. +|________________________________________________________________________________________________@*/ +CRef Solver::propagate() +{ + CRef confl = CRef_Undef; + int num_props = 0; + watches.cleanAll(); + watchesBin.cleanAll(); + while (qhead < trail.size()){ + Lit p = trail[qhead++]; // 'p' is enqueued fact to propagate. + vec<Watcher>& ws = watches[p]; + Watcher *i, *j, *end; + num_props++; + + // First, Propagate binary clauses + vec<Watcher>& wbin = watchesBin[p]; + for(int k = 0;k<wbin.size();k++) { + Lit imp = wbin[k].blocker; + if(value(imp) == l_False) { + return wbin[k].cref; + } + if(value(imp) == l_Undef) { + uncheckedEnqueue(imp,wbin[k].cref); + } + } + + for (i = j = (Watcher*)ws, end = i + ws.size(); i != end;){ + // Try to avoid inspecting the clause: + Lit blocker = i->blocker; + if (value(blocker) == l_True){ + *j++ = *i++; continue; } + + // Make sure the false literal is data[1]: + CRef cr = i->cref; + Clause& c = ca[cr]; + Lit false_lit = ~p; + if (c[0] == false_lit) + c[0] = c[1], c[1] = false_lit; + assert(c[1] == false_lit); + i++; + + // If 0th watch is true, then clause is already satisfied. + Lit first = c[0]; + Watcher w = Watcher(cr, first); + if (first != blocker && value(first) == l_True){ + *j++ = w; continue; } + + // Look for new watch: + if(incremental) { // ----------------- INCREMENTAL MODE + int choosenPos = -1; + for (int k = 2; k < c.size(); k++) { + + if (value(c[k]) != l_False){ + if(decisionLevel()>assumptions.size()) { + choosenPos = k; + break; + } else { + choosenPos = k; + + if(value(c[k])==l_True || !isSelector(var(c[k]))) { + break; + } + } + + } + } + if(choosenPos!=-1) { + c[1] = c[choosenPos]; c[choosenPos] = false_lit; + watches[~c[1]].push(w); + goto NextClause; } + } else { // ----------------- DEFAULT MODE (NOT INCREMENTAL) + for (int k = 2; k < c.size(); k++) { + + if (value(c[k]) != l_False){ + c[1] = c[k]; c[k] = false_lit; + watches[~c[1]].push(w); + goto NextClause; } + } + } + + // Did not find watch -- clause is unit under assignment: + *j++ = w; + if (value(first) == l_False){ + confl = cr; + qhead = trail.size(); + // Copy the remaining watches: + while (i < end) + *j++ = *i++; + }else { + uncheckedEnqueue(first, cr); + + + } + NextClause:; + } + ws.shrink(i - j); + } + propagations += num_props; + simpDB_props -= num_props; + + return confl; +} + + +/*_________________________________________________________________________________________________ +| +| reduceDB : () -> [void] +| +| Description: +| Remove half of the learnt clauses, minus the clauses locked by the current assignment. Locked +| clauses are clauses that are reason to some assignment. Binary clauses are never removed. +|________________________________________________________________________________________________@*/ +struct reduceDB_lt { + ClauseAllocator& ca; + reduceDB_lt(ClauseAllocator& ca_) : ca(ca_) {} + bool operator () (CRef x, CRef y) { + + // Main criteria... Like in MiniSat we keep all binary clauses + if(ca[x].size()> 2 && ca[y].size()==2) return 1; + + if(ca[y].size()> 2 && ca[x].size()==2) return 0; + if(ca[x].size()==2 && ca[y].size()==2) return 0; + + // Second one based on literal block distance + if(ca[x].lbd()> ca[y].lbd()) return 1; + if(ca[x].lbd()< ca[y].lbd()) return 0; + + // Finally we can use old activity or size, we choose the last one + return ca[x].activity() < ca[y].activity(); + //return x->size() < y->size(); + //return ca[x].size() > 2 && (ca[y].size() == 2 || ca[x].activity() < ca[y].activity()); } + } +}; + +void Solver::reduceDB() +{ + int i, j; + nbReduceDB++; + sort(learnts, reduceDB_lt(ca)); + + // We have a lot of "good" clauses, it is difficult to compare them. Keep more ! + if(ca[learnts[learnts.size() / RATIOREMOVECLAUSES]].lbd()<=3) nbclausesbeforereduce +=specialIncReduceDB; + // Useless :-) + if(ca[learnts.last()].lbd()<=5) nbclausesbeforereduce +=specialIncReduceDB; + + // Don't delete binary or locked clauses. From the rest, delete clauses from the first half + // Keep clauses which seem to be usefull (their lbd was reduce during this sequence) + + int limit = learnts.size() / 2; + for (i = j = 0; i < learnts.size(); i++){ + Clause& c = ca[learnts[i]]; + if (c.lbd()>2 && c.size() > 2 && c.canBeDel() && !locked(c) && (i < limit)) { + removeClause(learnts[i]); + nbRemovedClauses++; + } + else { + if(!c.canBeDel()) limit++; //we keep c, so we can delete an other clause + c.setCanBeDel(true); // At the next step, c can be delete + learnts[j++] = learnts[i]; + } + } + learnts.shrink(i - j); + checkGarbage(); +} + + +void Solver::removeSatisfied(vec<CRef>& cs) +{ + int i, j; + for (i = j = 0; i < cs.size(); i++){ + Clause& c = ca[cs[i]]; + if (satisfied(c)) + removeClause(cs[i]); + else + cs[j++] = cs[i]; + } + cs.shrink(i - j); +} + + +void Solver::rebuildOrderHeap() +{ + vec<Var> vs; + for (Var v = 0; v < nVars(); v++) + if (decision[v] && value(v) == l_Undef) + vs.push(v); + order_heap.build(vs); +} + + +/*_________________________________________________________________________________________________ +| +| simplify : [void] -> [bool] +| +| Description: +| Simplify the clause database according to the current top-level assigment. Currently, the only +| thing done here is the removal of satisfied clauses, but more things can be put here. +|________________________________________________________________________________________________@*/ +bool Solver::simplify() +{ + assert(decisionLevel() == 0); + + if (!ok || propagate() != CRef_Undef) + return ok = false; + + if (nAssigns() == simpDB_assigns || (simpDB_props > 0)) + return true; + + // Remove satisfied clauses: + removeSatisfied(learnts); + if (remove_satisfied) // Can be turned off. + removeSatisfied(clauses); + + checkGarbage(); + + rebuildOrderHeap(); + + simpDB_assigns = nAssigns(); + simpDB_props = clauses_literals + learnts_literals; // (shouldn't depend on stats really, but it will do for now) + + return true; +} + + +/*_________________________________________________________________________________________________ +| +| search : (nof_conflicts : int) (params : const SearchParams&) -> [lbool] +| +| Description: +| Search for a model the specified number of conflicts. +| NOTE! Use negative value for 'nof_conflicts' indicate infinity. +| +| Output: +| 'l_True' if a partial assigment that is consistent with respect to the clauseset is found. If +| all variables are decision variables, this means that the clause set is satisfiable. 'l_False' +| if the clause set is unsatisfiable. 'l_Undef' if the bound on number of conflicts is reached. +|________________________________________________________________________________________________@*/ +lbool Solver::search(int nof_conflicts) +{ + assert(ok); + int backtrack_level; + int conflictC = 0; + vec<Lit> learnt_clause,selectors; + unsigned int nblevels,szWoutSelectors; + bool blocked=false; + starts++; + for (;;){ + CRef confl = propagate(); + if (confl != CRef_Undef){ + // CONFLICT + conflicts++; conflictC++;conflictsRestarts++; + if(conflicts%5000==0 && var_decay<0.95) + var_decay += 0.01; + + if (verbosity >= 1 && conflicts%verbEveryConflicts==0){ + printf("c | %8d %7d %5d | %7d %8d %8d | %5d %8d %6d %8d | %6.3f %% |\n", + (int)starts,(int)nbstopsrestarts, (int)(conflicts/starts), + (int)dec_vars - (trail_lim.size() == 0 ? trail.size() : trail_lim[0]), nClauses(), (int)clauses_literals, + (int)nbReduceDB, nLearnts(), (int)nbDL2,(int)nbRemovedClauses, progressEstimate()*100); + } + if (decisionLevel() == 0) { + return l_False; + + } + + trailQueue.push(trail.size()); + // BLOCK RESTART (CP 2012 paper) + if( conflictsRestarts>LOWER_BOUND_FOR_BLOCKING_RESTART && lbdQueue.isvalid() && trail.size()>R*trailQueue.getavg()) { + lbdQueue.fastclear(); + nbstopsrestarts++; + if(!blocked) {lastblockatrestart=starts;nbstopsrestartssame++;blocked=true;} + } + + learnt_clause.clear(); + selectors.clear(); + analyze(confl, learnt_clause, selectors,backtrack_level,nblevels,szWoutSelectors); + + lbdQueue.push(nblevels); + sumLBD += nblevels; + + cancelUntil(backtrack_level); + + if (certifiedUNSAT) { + for (int i = 0; i < learnt_clause.size(); i++) + fprintf(certifiedOutput, "%i " , (var(learnt_clause[i]) + 1) * + (-2 * sign(learnt_clause[i]) + 1) ); + fprintf(certifiedOutput, "0\n"); + } + + if (learnt_clause.size() == 1){ + uncheckedEnqueue(learnt_clause[0]);nbUn++; + }else{ + CRef cr = ca.alloc(learnt_clause, true); + ca[cr].setLBD(nblevels); + ca[cr].setSizeWithoutSelectors(szWoutSelectors); + if(nblevels<=2) nbDL2++; // stats + if(ca[cr].size()==2) nbBin++; // stats + learnts.push(cr); + attachClause(cr); + + claBumpActivity(ca[cr]); + uncheckedEnqueue(learnt_clause[0], cr); + } + varDecayActivity(); + claDecayActivity(); + + + }else{ + + // Our dynamic restart, see the SAT09 competition compagnion paper + if ( (conflictsRestarts && lbdQueue.isvalid() && lbdQueue.getavg()*K > sumLBD/conflictsRestarts) || (pstop && *pstop) ) { + lbdQueue.fastclear(); + progress_estimate = progressEstimate(); + int bt = 0; + if(incremental) { // DO NOT BACKTRACK UNTIL 0.. USELESS + bt = (decisionLevel()<assumptions.size()) ? decisionLevel() : assumptions.size(); + } + cancelUntil(bt); + return l_Undef; + } + + // Simplify the set of problem clauses: + if (decisionLevel() == 0 && !simplify()) { + return l_False; + } + // Perform clause database reduction ! + if(conflicts>=curRestart* nbclausesbeforereduce) + { + + assert(learnts.size()>0); + curRestart = (conflicts/ nbclausesbeforereduce)+1; + reduceDB(); + nbclausesbeforereduce += incReduceDB; + } + + Lit next = lit_Undef; + while (decisionLevel() < assumptions.size()){ + // Perform user provided assumption: + Lit p = assumptions[decisionLevel()]; + if (value(p) == l_True){ + // Dummy decision level: + newDecisionLevel(); + }else if (value(p) == l_False){ + analyzeFinal(~p, conflict); + return l_False; + }else{ + next = p; + break; + } + } + + if (next == lit_Undef){ + // New variable decision: + decisions++; + next = pickBranchLit(); + + if (next == lit_Undef){ + //printf("c last restart ## conflicts : %d %d \n",conflictC,decisionLevel()); + // Model found: + return l_True; + } + } + + // Increase decision level and enqueue 'next' + newDecisionLevel(); + uncheckedEnqueue(next); + } + } +} + + +double Solver::progressEstimate() const +{ + double progress = 0; + double F = 1.0 / nVars(); + + for (int i = 0; i <= decisionLevel(); i++){ + int beg = i == 0 ? 0 : trail_lim[i - 1]; + int end = i == decisionLevel() ? trail.size() : trail_lim[i]; + progress += pow(F, i) * (end - beg); + } + + return progress / nVars(); +} + +void Solver::printIncrementalStats() { + + printf("c---------- Glucose Stats -------------------------\n"); + printf("c restarts : %ld\n", starts); + printf("c nb ReduceDB : %ld\n", nbReduceDB); + printf("c nb removed Clauses : %ld\n", nbRemovedClauses); + printf("c nb learnts DL2 : %ld\n", nbDL2); + printf("c nb learnts size 2 : %ld\n", nbBin); + printf("c nb learnts size 1 : %ld\n", nbUn); + + printf("c conflicts : %ld\n", conflicts); + printf("c decisions : %ld\n", decisions); + printf("c propagations : %ld\n", propagations); + + printf("c SAT Calls : %d in %g seconds\n", nbSatCalls, totalTime4Sat); + printf("c UNSAT Calls : %d in %g seconds\n", nbUnsatCalls, totalTime4Unsat); + printf("c--------------------------------------------------\n"); + + +} + + +// NOTE: assumptions passed in member-variable 'assumptions'. +lbool Solver::solve_() +{ + + if(incremental && certifiedUNSAT) { + printf("Can not use incremental and certified unsat in the same time\n"); + exit(-1); + } + model.clear(); + conflict.clear(); + if (!ok) return l_False; + double curTime = cpuTime(); + + + solves++; + + + + lbool status = l_Undef; + if(!incremental && verbosity>=1) { + printf("c ========================================[ MAGIC CONSTANTS ]==============================================\n"); + printf("c | Constants are supposed to work well together :-) |\n"); + printf("c | however, if you find better choices, please let us known... |\n"); + printf("c |-------------------------------------------------------------------------------------------------------|\n"); + printf("c | | | |\n"); + printf("c | - Restarts: | - Reduce Clause DB: | - Minimize Asserting: |\n"); + printf("c | * LBD Queue : %6d | * First : %6d | * size < %3d |\n",lbdQueue.maxSize(),nbclausesbeforereduce,lbSizeMinimizingClause); + printf("c | * Trail Queue : %6d | * Inc : %6d | * lbd < %3d |\n",trailQueue.maxSize(),incReduceDB,lbLBDMinimizingClause); + printf("c | * K : %6.2f | * Special : %6d | |\n",K,specialIncReduceDB); + printf("c | * R : %6.2f | * Protected : (lbd)< %2d | |\n",R,lbLBDFrozenClause); + printf("c | | | |\n"); +printf("c ==================================[ Search Statistics (every %6d conflicts) ]=========================\n",verbEveryConflicts); + printf("c | |\n"); + + printf("c | RESTARTS | ORIGINAL | LEARNT | Progress |\n"); + printf("c | NB Blocked Avg Cfc | Vars Clauses Literals | Red Learnts LBD2 Removed | |\n"); + printf("c =========================================================================================================\n"); + } + + // Search: + int curr_restarts = 0; + while (status == l_Undef){ + status = search(0); // the parameter is useless in glucose, kept to allow modifications + if (!withinBudget() || terminate_search_early || (pstop && *pstop)) break; + if (nRuntimeLimit && Abc_Clock() > nRuntimeLimit) break; + curr_restarts++; + } + + if (!incremental && verbosity >= 1) + printf("c =========================================================================================================\n"); + + + if (certifiedUNSAT){ // Want certified output + if (status == l_False) + fprintf(certifiedOutput, "0\n"); + fclose(certifiedOutput); + } + + + if (status == l_True){ + // Extend & copy model: + model.growTo(nVars()); + for (int i = 0; i < nVars(); i++) model[i] = value(i); + }else if (status == l_False && conflict.size() == 0) + ok = false; + + cancelUntil(0); + + double finalTime = cpuTime(); + if(status==l_True) { + nbSatCalls++; + totalTime4Sat +=(finalTime-curTime); + } + if(status==l_False) { + nbUnsatCalls++; + totalTime4Unsat +=(finalTime-curTime); + } + + // ABC callback + if (pCnfFunc && !terminate_search_early) {// hack to avoid calling callback twise if the solver was terminated early + int * pCex = NULL; + int message = (status == l_True ? 1 : status == l_False ? 0 : -1); + if (status == l_True) { + pCex = new int[nVars()]; + for (int i = 0; i < nVars(); i++) + pCex[i] = (model[i] == l_True); + } + + int callback_result = pCnfFunc(pCnfMan, message, pCex); + assert(callback_result == 0); + } + else if (pCnfFunc) + terminate_search_early = false; // for next run + + return status; +} + +//================================================================================================= +// Writing CNF to DIMACS: +// +// FIXME: this needs to be rewritten completely. + +static Var mapVar(Var x, vec<Var>& map, Var& max) +{ + if (map.size() <= x || map[x] == -1){ + map.growTo(x+1, -1); + map[x] = max++; + } + return map[x]; +} + + +void Solver::toDimacs(FILE* f, Clause& c, vec<Var>& map, Var& max) +{ + if (satisfied(c)) return; + + for (int i = 0; i < c.size(); i++) + if (value(c[i]) != l_False) + fprintf(f, "%s%d ", sign(c[i]) ? "-" : "", mapVar(var(c[i]), map, max)+1); + fprintf(f, "0\n"); +} + + +void Solver::toDimacs(const char *file, const vec<Lit>& assumps) +{ + FILE* f = fopen(file, "wr"); + if (f == NULL) + fprintf(stderr, "could not open file %s\n", file), exit(1); + toDimacs(f, assumps); + fclose(f); +} + + +void Solver::toDimacs(FILE* f, const vec<Lit>& assumps) +{ + // Handle case when solver is in contradictory state: + if (!ok){ + fprintf(f, "p cnf 1 2\n1 0\n-1 0\n"); + return; } + + vec<Var> map; Var max = 0; + + // Cannot use removeClauses here because it is not safe + // to deallocate them at this point. Could be improved. + int i, cnt = 0; + for (i = 0; i < clauses.size(); i++) + if (!satisfied(ca[clauses[i]])) + cnt++; + + for (i = 0; i < clauses.size(); i++) + if (!satisfied(ca[clauses[i]])){ + Clause& c = ca[clauses[i]]; + for (int j = 0; j < c.size(); j++) + if (value(c[j]) != l_False) + mapVar(var(c[j]), map, max); + } + + // Assumptions are added as unit clauses: + cnt += assumptions.size(); + + fprintf(f, "p cnf %d %d\n", max, cnt); + + for (i = 0; i < assumptions.size(); i++){ + assert(value(assumptions[i]) != l_False); + fprintf(f, "%s%d 0\n", sign(assumptions[i]) ? "-" : "", mapVar(var(assumptions[i]), map, max)+1); + } + + for (i = 0; i < clauses.size(); i++) + toDimacs(f, ca[clauses[i]], map, max); + + if (verbosity > 0) + printf("Wrote %d clauses with %d variables.\n", cnt, max); +} + + +//================================================================================================= +// Garbage Collection methods: + +void Solver::relocAll(ClauseAllocator& to) +{ + int v, s, i, j; + // All watchers: + // + // for (int i = 0; i < watches.size(); i++) + watches.cleanAll(); + watchesBin.cleanAll(); + for (v = 0; v < nVars(); v++) + for (s = 0; s < 2; s++){ + Lit p = mkLit(v, s != 0); + // printf(" >>> RELOCING: %s%d\n", sign(p)?"-":"", var(p)+1); + vec<Watcher>& ws = watches[p]; + for (j = 0; j < ws.size(); j++) + ca.reloc(ws[j].cref, to); + vec<Watcher>& ws2 = watchesBin[p]; + for (j = 0; j < ws2.size(); j++) + ca.reloc(ws2[j].cref, to); + } + + // All reasons: + // + for (i = 0; i < trail.size(); i++){ + Var v = var(trail[i]); + + if (reason(v) != CRef_Undef && (ca[reason(v)].reloced() || locked(ca[reason(v)]))) + ca.reloc(vardata[v].reason, to); + } + + // All learnt: + // + for (i = 0; i < learnts.size(); i++) + ca.reloc(learnts[i], to); + + // All original: + // + for (i = 0; i < clauses.size(); i++) + ca.reloc(clauses[i], to); +} + + +void Solver::garbageCollect() +{ + // Initialize the next region to a size corresponding to the estimated utilization degree. This + // is not precise but should avoid some unnecessary reallocations for the new region: + ClauseAllocator to(ca.size() - ca.wasted()); + + relocAll(to); + if (verbosity >= 2) + printf("| Garbage collection: %12d bytes => %12d bytes |\n", + ca.size()*ClauseAllocator::Unit_Size, to.size()*ClauseAllocator::Unit_Size); + to.moveTo(ca); +} + +void Solver::reset() +{ + // Reset everything + ok = true; + K = (double)opt_K; + R = (double)opt_R; + firstReduceDB = opt_first_reduce_db; + var_decay = (double)opt_var_decay; + //max_var_decay = opt_max_var_decay; + solves = starts = decisions = propagations = conflicts = conflictsRestarts = 0; + curRestart = 1; + cla_inc = var_inc = 1; + watches.clear(false); // We don't free the memory, new calls should be of the same size order. + watchesBin.clear(false); + //unaryWatches.clear(false); + qhead = 0; + simpDB_assigns = -1; + simpDB_props = 0; + order_heap.clear(false); + progress_estimate = 0; + //lastLearntClause = CRef_Undef; + conflict_budget = -1; + propagation_budget = -1; + nbVarsInitialFormula = INT32_MAX; + totalTime4Sat = 0.; + totalTime4Unsat = 0.; + nbSatCalls = nbUnsatCalls = 0; + MYFLAG = 0; + lbdQueue.clear(false); + lbdQueue.initSize(sizeLBDQueue); + trailQueue.clear(false); + trailQueue.initSize(sizeTrailQueue); + sumLBD = 0; + nbclausesbeforereduce = firstReduceDB; + //stats.clear(); + //stats.growTo(coreStatsSize, 0); + clauses.clear(false); + learnts.clear(false); + //permanentLearnts.clear(false); + //unaryWatchedClauses.clear(false); + model.clear(false); + conflict.clear(false); + activity.clear(false); + assigns.clear(false); + polarity.clear(false); + //forceUNSAT.clear(false); + decision.clear(false); + trail.clear(false); + nbpos.clear(false); + trail_lim.clear(false); + vardata.clear(false); + assumptions.clear(false); + permDiff.clear(false); + lastDecisionLevel.clear(false); + ca.clear(); + seen.clear(false); + analyze_stack.clear(false); + analyze_toclear.clear(false); + add_tmp.clear(false); + assumptionPositions.clear(false); + initialPositions.clear(false); +} + +ABC_NAMESPACE_IMPL_END |