//============================================================================== // // Copyright (c) 2002- // Authors: // * Dave Parker (University of Oxford, formerly University of Birmingham) // * Rashid Mehmood (University of Birmingham) // * Joachim Klein (TU Dresden) // //------------------------------------------------------------------------------ // // This file is part of PRISM. // // PRISM is free software; you can redistribute it and/or modify // it under the terms of the GNU General Public License as published by // the Free Software Foundation; either version 2 of the License, or // (at your option) any later version. // // PRISM is distributed in the hope that it will be useful, // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU General Public License for more details. // // You should have received a copy of the GNU General Public License // along with PRISM; if not, write to the Free Software Foundation, // Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA // //============================================================================== // includes #include "PrismHybrid.h" #include #include #include #include #include #include #include "sparse.h" #include "hybrid.h" #include "PrismHybridGlob.h" #include "jnipointer.h" #include "prism.h" #include "Measures.h" #include "ExportIterations.h" #include "IntervalIteration.h" #include #include // local prototypes static void sor_rec(HDDNode *hdd, int level, int row_offset, int col_offset, int r, int c, bool transpose); static void sor_rm(RMSparseMatrix *rmsm, int row_offset, int col_offset, int r, int c, bool is_diag); static void sor_cmsr(CMSRSparseMatrix *cmsrsm, int row_offset, int col_offset, int r, int c, bool is_diag); // globals (used by local functions) static HDDNode *zero; static int num_levels; static bool compact_d, compact_sm; static double *sm_dist; static int sm_dist_shift; static int sm_dist_mask; static double *diags_vec = NULL; static DistVector *diags_dist = NULL; static double *soln = NULL, *soln2 = NULL; static double omega; static bool forwards; static IntervalIteration* _helper = NULL; static bool from_below; //------------------------------------------------------------------------------ // solve the linear equation system Ax=b with Gauss-Seidel/SOR, interval variant JNIEXPORT jlong __jlongpointer JNICALL Java_hybrid_PrismHybrid_PH_1SORInterval ( JNIEnv *env, jclass cls, jlong __jlongpointer _odd, // odd jlong __jlongpointer rv, // row vars jint num_rvars, jlong __jlongpointer cv, // col vars jint num_cvars, jlong __jlongpointer _a, // matrix A jlong __jlongpointer _b, // vector b (if null, assume all zero) jlong __jlongpointer _lower, // lower bound values jlong __jlongpointer _upper, // upper bound values jboolean transpose, // transpose A? (i.e. solve xA=b not Ax=b?) jboolean row_sums, // use row sums for diags instead? (strictly speaking: negative sum of non-diagonal row elements) jdouble om, // omega (over-relaxation parameter) jboolean fwds, // forwards or backwards? jint flags ) { // cast function parameters ODDNode *odd = jlong_to_ODDNode(_odd); // odd DdNode **rvars = jlong_to_DdNode_array(rv); // row vars DdNode **cvars = jlong_to_DdNode_array(cv); // col vars DdNode *a = jlong_to_DdNode(_a); // matrix A DdNode *b = jlong_to_DdNode(_b); // vector b DdNode *lower = jlong_to_DdNode(_lower); // lower bound values DdNode *upper = jlong_to_DdNode(_upper); // upper bound values omega = om; forwards = fwds; // mtbdds DdNode *reach = NULL, *diags = NULL, *id = NULL; // model stats int n; // flags bool compact_b, l_b_max; // matrix mtbdd HDDMatrix *hddm = NULL; HDDNode *hdd = NULL; // vectors double *b_vec = NULL; DistVector *b_dist = NULL; double *soln_below = NULL, *soln_above = NULL; // timing stuff long start1, start2, start3, stop; double time_taken, time_for_setup, time_for_iters; // misc int i, j, fb, l, h, i2, h2, iters; double kb, kbt; bool done, diag_done; // measure for convergence termination check MeasureSupNormInterval measure(term_crit == TERM_CRIT_RELATIVE); if (omega <= 0.0 || omega > 1.0) { PH_SetErrorMessage("Interval iteration requires 0 < omega <= 1.0, have omega = %g", omega); return ptr_to_jlong(NULL); } IntervalIteration helper(flags); _helper = &helper; // store globally for recursion // exception handling around whole function try { // start clocks start1 = start2 = util_cpu_time(); // get number of states n = odd->eoff + odd->toff; // get reachable states reach = odd->dd; // make local copy of a Cudd_Ref(a); // remove and keep diagonal entries of matrix A id = DD_Identity(ddman, rvars, cvars, num_rvars); Cudd_Ref(reach); id = DD_And(ddman, id, reach); Cudd_Ref(id); Cudd_Ref(a); diags = DD_Apply(ddman, APPLY_TIMES, id, a); Cudd_Ref(id); a = DD_ITE(ddman, id, DD_Constant(ddman, 0), a); // build hdd for matrix PH_PrintToMainLog(env, "\nBuilding hybrid MTBDD matrix... "); hddm = build_hdd_matrix(a, rvars, cvars, num_rvars, odd, true, transpose); hdd = hddm->top; zero = hddm->zero; num_levels = hddm->num_levels; kb = hddm->mem_nodes; kbt = kb; PH_PrintToMainLog(env, "[levels=%d, nodes=%d] ", hddm->num_levels, hddm->num_nodes); PH_PrintMemoryToMainLog(env, "[", kb, "]\n"); // split hdd matrix into blocks // nb: in terms of memory, this gets precedence over sparse matrices PH_PrintToMainLog(env, "Splitting into blocks... "); split_hdd_matrix(hddm, compact, false, transpose); compact_b = hddm->compact_b; rearrange_hdd_blocks(hddm, false); kb = hddm->mem_b; kbt += kb; PH_PrintToMainLog(env, "[levels=%d, n=%d, nnz=%d%s] ", hddm->l_b, hddm->blocks->n, hddm->blocks->nnz, compact_b?", compact":""); PH_PrintMemoryToMainLog(env, "[", kb, "]\n"); // add sparse matrices PH_PrintToMainLog(env, "Adding explicit sparse matrices... "); add_sparse_matrices(hddm, compact, true, transpose); compact_sm = hddm->compact_sm; if (compact_sm) { sm_dist = hddm->dist; sm_dist_shift = hddm->dist_shift; sm_dist_mask = hddm->dist_mask; } l_b_max = (hddm->l_b == hddm->num_levels); kb = hddm->mem_sm; kbt += kb; PH_PrintToMainLog(env, "[levels=%d, num=%d%s] ", hddm->l_sm, hddm->num_sm, compact_sm?", compact":""); PH_PrintMemoryToMainLog(env, "[", kb, "]\n"); // get vector of diags, either by extracting from mtbdd or // by doing (negative, non-diagonal) row sums of original A matrix (and then setting to 1 if sum is 0) PH_PrintToMainLog(env, "Creating vector for diagonals... "); if (!row_sums) { diags = DD_MaxAbstract(ddman, diags, cvars, num_cvars); diags_vec = mtbdd_to_double_vector(ddman, diags, rvars, num_rvars, odd); } else { diags_vec = hdd_negative_row_sums(hddm, n, transpose); } // if any of the diagonals are zero, set them to one - avoids division by zero errors later // strictly speaking, such matrices shouldn't work for this iterative method // but they do occur, e.g. for steady-state computation of a bscc, this fixes it for (i = 0; i < n; i++) diags_vec[i] = (diags_vec[i] == 0) ? 1.0 : diags_vec[i]; // try and convert to compact form if required compact_d = false; if (compact) { if ((diags_dist = double_vector_to_dist(diags_vec, n))) { compact_d = true; delete[] diags_vec; diags_vec = NULL; } } kb = (!compact_d) ? n*8.0/1024.0 : (diags_dist->num_dist*8.0+n*2.0)/1024.0; kbt += kb; if (compact_d) PH_PrintToMainLog(env, "[dist=%d, compact] ", diags_dist->num_dist); PH_PrintMemoryToMainLog(env, "[", kb, "]\n"); // invert diagonal if (!compact_d) { for (i = 0; i < n; i++) diags_vec[i] = 1.0 / diags_vec[i]; } else { for (i = 0; i < diags_dist->num_dist; i++) diags_dist->dist[i] = 1.0 / diags_dist->dist[i]; } // build b vector (if present) if (b != NULL) { PH_PrintToMainLog(env, "Creating vector for RHS... "); b_vec = mtbdd_to_double_vector(ddman, b, rvars, num_rvars, odd); // try and convert to compact form if required compact_b = false; if (compact) { if ((b_dist = double_vector_to_dist(b_vec, n))) { compact_b = true; delete[] b_vec; b_vec = NULL; } } kb = (!compact_b) ? n*8.0/1024.0 : (b_dist->num_dist*8.0+n*2.0)/1024.0; kbt += kb; if (compact_b) PH_PrintToMainLog(env, "[dist=%d, compact] ", b_dist->num_dist); PH_PrintMemoryToMainLog(env, "[", kb, "]\n"); } // create solution/iteration vectors PH_PrintToMainLog(env, "Allocating iteration vectors... "); soln_below = mtbdd_to_double_vector(ddman, lower, rvars, num_rvars, odd); soln_above = mtbdd_to_double_vector(ddman, upper, rvars, num_rvars, odd); soln2 = new double[hddm->blocks->max]; for (i = 0; i < hddm->blocks->max; i++) soln2[i] = 0; kb = 2*(n*8.0/1024.0)+(hddm->blocks->max*8.0/1024.0); kbt += kb; PH_PrintMemoryToMainLog(env, "[2 x ", (n*8.0/1024.0), ""); PH_PrintMemoryToMainLog(env, " + ", (hddm->blocks->max*8.0/1024.0), ""); PH_PrintMemoryToMainLog(env, " = ", kb, "]\n"); // print total memory usage PH_PrintMemoryToMainLog(env, "TOTAL: [", kbt, "]\n"); std::unique_ptr iterationExport; if (PH_GetFlagExportIterations()) { std::string title("PH_SORInterval ("); title += (omega == 1.0)?"Gauss-Seidel": ("SOR omega=" + std::to_string(omega)); title += ")"; iterationExport.reset(new ExportIterations(title.c_str())); PH_PrintToMainLog(env, "Exporting iterations to %s\n", iterationExport->getFileName().c_str()); iterationExport->exportVector(soln_below, n, 0); iterationExport->exportVector(soln_above, n, 1); } // get setup time stop = util_cpu_time(); time_for_setup = (double)(stop - start2)/1000; start2 = stop; start3 = stop; // start iterations iters = 0; done = false; PH_PrintToMainLog(env, "\nStarting iterations...\n"); while (!done && iters < max_iters) { iters++; // stuff for block storage int b_n = hddm->blocks->n; int b_nnz = hddm->blocks->nnz; HDDNode **b_blocks = hddm->blocks->blocks; unsigned int *b_rowscols = hddm->blocks->rowscols; unsigned char *b_counts = hddm->blocks->counts; int *b_starts = (int *)hddm->blocks->counts; bool b_use_counts = hddm->blocks->use_counts; int *b_offsets = hddm->blocks->offsets; HDDNode **b_nodes = hddm->row_tables[hddm->l_b]; int b_dist_shift = hddm->blocks->dist_shift; int b_dist_mask = hddm->blocks->dist_mask; int row_offset, col_offset; HDDNode *node; int it; for (it = 0; it <= 1; it++) { if (it == 0) { // from below from_below = true; soln = soln_below; } else { // from above from_below = false; soln = soln_above; } // loop through rows of blocks l = b_nnz; h = 0; for(fb = 0; fb < b_n; fb++) { // loop actually over i (can do forwards or backwards sor/gs) i = (forwards) ? fb : b_n-1-fb; // store block row offset row_offset = b_offsets[i]; // initialise (partial) solution vector h2 = b_offsets[i+1] - b_offsets[i]; // initialise vector if (b == NULL) { for (i2 = 0; i2 < h2; i2++) { soln2[i2] = 0.0; } } else if (!compact_b) { for (i2 = 0; i2 < h2; i2++) { soln2[i2] = b_vec[row_offset + i2]; } } else { for (i2 = 0; i2 < h2; i2++) { soln2[i2] = b_dist->dist[b_dist->ptrs[row_offset + i2]]; } } // loop through blocks in this row of blocks if (!b_use_counts) { l = b_starts[i]; h = b_starts[i+1]; } else if (forwards) { l = h; h += b_counts[i]; } else { h = l; l -= b_counts[i]; } diag_done = false; for(j = l; j < h; j++) { // get node for block and its col offset if (!compact_b) { node = b_blocks[j]; col_offset = b_offsets[b_rowscols[j]]; } else { node = b_nodes[(int)(b_rowscols[j] & b_dist_mask)]; col_offset = b_offsets[(int)(b_rowscols[j] >> b_dist_shift)]; } // trivial case where we are the bottom of the mtbdd already if (l_b_max) { soln2[0] -= soln[col_offset] * node->type.val; //printf("(%d,%d)=%f\n", row_offset, col_offset, node->type.val); continue; } // non-diagonal blocks treated normally // (diagonal should be the last block, unless it is absent because empty) if ((j != h-1) || (j == h-1 && row_offset !=col_offset)) { sor_rec(node, hddm->l_b, row_offset, col_offset, 0, 0, transpose); } // diagonal blocks (last blocks in row/col) are different // call sparse matrix traversal directly with "is_diag" flag = true else { diag_done = true; if (!compact_sm) { sor_rm((RMSparseMatrix *)node->sm.ptr, row_offset, col_offset, 0, 0, true); } else { sor_cmsr((CMSRSparseMatrix *)node->sm.ptr, row_offset, col_offset, 0, 0, true); } } } // if we never found a diagonal block (because it is empty and so not there), // then we do the stuff that should have been done after the processing of the diagonal block if (!l_b_max && !diag_done) for (i2 = 0; i2 < h2; i2++) { // divide by diagonal if (!compact_d) { soln2[i2] *= diags_vec[row_offset + i2]; } else { soln2[i2] *= (diags_dist->dist[(int)diags_dist->ptrs[row_offset + i2]]); } // do over-relaxation if necessary if (omega != 1) { soln2[i2] = ((1-omega) * soln[row_offset + i2]) + (omega * soln2[i2]); } // set vector element helper.updateValue(soln[row_offset + i2], soln[row_offset + i2], soln2[i2], from_below); } // trivial case where we are the bottom of the mtbdd already if (l_b_max) { soln2[0] *= ((!compact_d)?(diags_vec[row_offset]):(diags_dist->dist[(int)diags_dist->ptrs[row_offset]])); if (omega != 1) soln2[0] = ((1-omega) * soln[row_offset]) + (omega * soln2[0]); // set vector element helper.updateValue(soln[row_offset], soln[row_offset], soln2[0], from_below); } } } if (iterationExport) { iterationExport->exportVector(soln_below, n, 0); iterationExport->exportVector(soln_above, n, 1); } // check convergence measure.reset(); measure.measure(soln_below, soln_above, n); if (measure.value() < term_crit_param) { PH_PrintToMainLog(env, "Max %sdiff between upper and lower bound on convergence: %G", measure.isRelative()?"relative ":"", measure.value()); done = true; } // print occasional status update if ((util_cpu_time() - start3) > UPDATE_DELAY) { PH_PrintToMainLog(env, "Iteration %d: max %sdiff=%f", iters, measure.isRelative()?"relative ":"", measure.value()); PH_PrintToMainLog(env, ", %.2f sec so far\n", ((double)(util_cpu_time() - start2)/1000)); start3 = util_cpu_time(); } } // stop clocks stop = util_cpu_time(); time_for_iters = (double)(stop - start2)/1000; time_taken = (double)(stop - start1)/1000; // print iters/timing info PH_PrintToMainLog(env, "\n%s%s (interval iteration): %d iterations in %.2f seconds (average %.6f, setup %.2f)\n", forwards?"":"Backwards ", (omega == 1.0)?"Gauss-Seidel":"SOR", iters, time_taken, time_for_iters/iters, time_for_setup); // if the iterative method didn't terminate, this is an error if (!done) { delete[] soln_below; soln_below = NULL; PH_SetErrorMessage("Iterative method (interval iteration) did not converge within %d iterations.\nConsider using a different numerical method or increasing the maximum number of iterations", iters); PH_PrintToMainLog(env, "Max remaining %sdiff between upper and lower bound on convergence: %G", measure.isRelative()?"relative ":"", measure.value()); } if (helper.flag_select_midpoint() && soln_below) { // we did converge, select midpoint helper.selectMidpoint(soln_below, soln_above, n); if (iterationExport) { // export result vector as below and above iterationExport->exportVector(soln_below, n, 0); iterationExport->exportVector(soln_below, n, 1); } } // catch exceptions: register error, free memory } catch (std::bad_alloc e) { PH_SetErrorMessage("Out of memory"); if (soln_below) delete[] soln_below; soln_below = 0; } // free memory if (a) Cudd_RecursiveDeref(ddman, a); if (id) Cudd_RecursiveDeref(ddman, id); if (diags) Cudd_RecursiveDeref(ddman, diags); if (hddm) delete hddm; if (diags_vec) delete[] diags_vec; if (diags_dist) delete diags_dist; if (b_vec) delete[] b_vec; if (b_dist) delete b_dist; if (soln2) delete[] soln2; if (soln_above) delete[] soln_above; return ptr_to_jlong(soln_below); } //------------------------------------------------------------------------------ static void sor_rec(HDDNode *hdd, int level, int row_offset, int col_offset, int r, int c, bool transpose) { HDDNode *e, *t; // if it's the zero node if (hdd == zero) { return; } // or if we've reached a submatrix // (check for non-null ptr but, equivalently, we could just check if level==l_sm) else if (hdd->sm.ptr) { if (!compact_sm) { sor_rm((RMSparseMatrix *)hdd->sm.ptr, row_offset, col_offset, r, c, false); } else { sor_cmsr((CMSRSparseMatrix *)hdd->sm.ptr, row_offset, col_offset, r, c, false); } return; } // or if we've reached the bottom else if (level == num_levels) { //printf("(%d,%d)=%f\n", row_offset, col_offset, hdd->type.val); soln2[r] -= soln[col_offset+c] * hdd->type.val; return; } // otherwise recurse e = hdd->type.kids.e; if (e != zero) { if (!transpose) { sor_rec(e->type.kids.e, level+1, row_offset, col_offset, r, c, transpose); sor_rec(e->type.kids.t, level+1, row_offset, col_offset, r, c+e->off.val, transpose); } else { sor_rec(e->type.kids.e, level+1, row_offset, col_offset, r, c, transpose); sor_rec(e->type.kids.t, level+1, row_offset, col_offset, r+e->off.val, c, transpose); } } t = hdd->type.kids.t; if (t != zero) { if (!transpose) { sor_rec(t->type.kids.e, level+1, row_offset, col_offset, r+hdd->off.val, c, transpose); sor_rec(t->type.kids.t, level+1, row_offset, col_offset, r+hdd->off.val, c+t->off.val, transpose); } else { sor_rec(t->type.kids.e, level+1, row_offset, col_offset, r, c+hdd->off.val, transpose); sor_rec(t->type.kids.t, level+1, row_offset, col_offset, r+t->off.val, c+hdd->off.val, transpose); } } } //----------------------------------------------------------------------------------- static void sor_rm(RMSparseMatrix *rmsm, int row_offset, int col_offset, int r, int c, bool is_diag) { int fb2, i2, j2, l2, h2; int sm_n = rmsm->n; int sm_nnz = rmsm->nnz; double *sm_non_zeros = rmsm->non_zeros; unsigned char *sm_row_counts = rmsm->row_counts; int *sm_row_starts = (int *)rmsm->row_counts; bool sm_use_counts = rmsm->use_counts; unsigned int *sm_cols = rmsm->cols; // loop through rows of submatrix l2 = sm_nnz; h2 = 0; for (fb2 = 0; fb2 < sm_n; fb2++) { // loop actually over i2 (can do forwards or backwards sor/gs) i2 = (forwards) ? fb2 : sm_n-1-fb2; // loop through entries in this row if (!sm_use_counts) { l2 = sm_row_starts[i2]; h2 = sm_row_starts[i2+1]; } else if (forwards) { l2 = h2; h2 += sm_row_counts[i2]; } else { h2 = l2; l2 -= sm_row_counts[i2]; } for (j2 = l2; j2 < h2; j2++) { soln2[r + i2] -= soln[col_offset + c + sm_cols[j2]] * sm_non_zeros[j2]; //printf("(%d,%d)=%f\n", r + i2, col_offset + c + sm_cols[j2], sm_non_zeros[j2]); } if (is_diag) { // divide by diagonal if (!compact_d) { soln2[r + i2] *= diags_vec[row_offset + r + i2]; } else { soln2[r + i2] *= (diags_dist->dist[(int)diags_dist->ptrs[row_offset + r + i2]]); } // do over-relaxation if necessary if (omega != 1) { soln2[r + i2] = ((1-omega) * soln[row_offset + r + i2]) + (omega * soln2[r + i2]); } // set vector element _helper->updateValue(soln[row_offset + r + i2], soln[row_offset + r + i2], soln2[r + i2], from_below); } } } //----------------------------------------------------------------------------------- static void sor_cmsr(CMSRSparseMatrix *cmsrsm, int row_offset, int col_offset, int r, int c, bool is_diag) { int fb2, i2, j2, l2, h2; int sm_n = cmsrsm->n; int sm_nnz = cmsrsm->nnz; unsigned char *sm_row_counts = cmsrsm->row_counts; int *sm_row_starts = (int *)cmsrsm->row_counts; bool sm_use_counts = cmsrsm->use_counts; unsigned int *sm_cols = cmsrsm->cols; // loop through rows of submatrix l2 = sm_nnz; h2 = 0; for (fb2 = 0; fb2 < sm_n; fb2++) { // loop actually over i2 (can do forwards or backwards sor/gs) i2 = (forwards) ? fb2 : sm_n-1-fb2; // loop through entries in this row if (!sm_use_counts) { l2 = sm_row_starts[i2]; h2 = sm_row_starts[i2+1]; } else if (forwards) { l2 = h2; h2 += sm_row_counts[i2]; } else { h2 = l2; l2 -= sm_row_counts[i2]; } for (j2 = l2; j2 < h2; j2++) { soln2[r + i2] -= soln[col_offset + c + (int)(sm_cols[j2] >> sm_dist_shift)] * sm_dist[(int)(sm_cols[j2] & sm_dist_mask)]; //printf("(%d,%d)=%f\n", row_offset + r + i2, col_offset + c + (int)(sm_cols[j2] >> sm_dist_shift), sm_dist[(int)(sm_cols[j2] & sm_dist_mask)]); } if (is_diag) { // divide by diagonal if (!compact_d) { soln2[r + i2] *= diags_vec[row_offset + r + i2]; } else { soln2[r + i2] *= (diags_dist->dist[(int)diags_dist->ptrs[row_offset + r + i2]]); } // do over-relaxation if necessary if (omega != 1) { soln2[r + i2] = ((1-omega) * soln[row_offset + r + i2]) + (omega * soln2[r + i2]); } // set vector element _helper->updateValue(soln[row_offset + r + i2], soln[row_offset + r + i2], soln2[r + i2], from_below); } } } //------------------------------------------------------------------------------