//============================================================================== // // Copyright (c) 2002- // Authors: // * Dave Parker (University of Oxford, formerly University of Birmingham) // //------------------------------------------------------------------------------ // // 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 "PrismSparse.h" #include #include #include #include #include #include #include #include "sparse.h" #include "PrismSparseGlob.h" #include "jnipointer.h" #include "Measures.h" #include //------------------------------------------------------------------------------ JNIEXPORT jlong __jlongpointer JNICALL Java_sparse_PrismSparse_PS_1StochTransient ( JNIEnv *env, jclass cls, jlong __jlongpointer tr, // trans matrix jlong __jlongpointer od, // odd jlong __jlongpointer in, // initial distribution (note: this will be deleted afterwards) jlong __jlongpointer rv, // row vars jint num_rvars, jlong __jlongpointer cv, // col vars jint num_cvars, jdouble time // time bound ) { // cast function parameters DdNode *trans = jlong_to_DdNode(tr); // trans matrix ODDNode *odd = jlong_to_ODDNode(od); // odd double *init = jlong_to_double(in); // initial distribution DdNode **rvars = jlong_to_DdNode_array(rv); // row vars DdNode **cvars = jlong_to_DdNode_array(cv); // col vars // model stats int n; long nnz; // flags bool compact_tr, compact_d; // sparse matrix CMSparseMatrix *cmsm = NULL; CMSCSparseMatrix *cmscsm = NULL; // vectors double *diags = NULL, *soln = NULL, *soln2 = NULL, *tmpsoln = NULL, *sum = NULL; DistVector *diags_dist = NULL; // fox glynn stuff FoxGlynnWeights fgw; // timing stuff long start1, start2, start3, stop; double time_taken, time_for_setup, time_for_iters; // misc bool done; int j, l, h; long i, iters, num_iters; double d, max_diag, weight, kb, kbt, unif, term_crit_param_unif; // measure for convergence termination check MeasureSupNorm measure(term_crit == TERM_CRIT_RELATIVE); // exception handling around whole function try { // start clocks start1 = start2 = util_cpu_time(); // get number of states n = odd->eoff + odd->toff; // build sparse matrix PS_PrintToMainLog(env, "\nBuilding sparse matrix... "); // if requested, try and build a "compact" version compact_tr = true; cmscsm = NULL; if (compact) cmscsm = build_cmsc_sparse_matrix(ddman, trans, rvars, cvars, num_rvars, odd); if (cmscsm != NULL) { nnz = cmscsm->nnz; kb = cmscsm->mem; } // if not or if it wasn't possible, built a normal one else { compact_tr = false; cmsm = build_cm_sparse_matrix(ddman, trans, rvars, cvars, num_rvars, odd); nnz = cmsm->nnz; kb = cmsm->mem; } kbt = kb; // print some info PS_PrintToMainLog(env, "[n=%d, nnz=%ld%s] ", n, nnz, compact_tr?", compact":""); PS_PrintMemoryToMainLog(env, "[", kb, "]\n"); // get vector of diagonals PS_PrintToMainLog(env, "Creating vector for diagonals... "); diags = compact_tr ? cmsc_negative_row_sums(cmscsm) : cm_negative_row_sums(cmsm); // try and convert to compact form if required compact_d = false; if (compact) { if ((diags_dist = double_vector_to_dist(diags, n))) { compact_d = true; delete diags; diags = 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) PS_PrintToMainLog(env, "[dist=%d, compact] ", diags_dist->num_dist); PS_PrintMemoryToMainLog(env, "[", kb, "]\n"); // find max diagonal element if (!compact_d) { max_diag = diags[0]; for (i = 1; i < n; i++) if (diags[i] < max_diag) max_diag = diags[i]; } else { max_diag = diags_dist->dist[0]; for (i = 1; i < diags_dist->num_dist; i++) if (diags_dist->dist[i] < max_diag) max_diag = diags_dist->dist[i]; } max_diag = -max_diag; // constant for uniformization unif = 1.02*max_diag; // modify diagonals if (!compact_d) { for (i = 0; i < n; i++) diags[i] = diags[i] / unif + 1; } else { for (i = 0; i < diags_dist->num_dist; i++) diags_dist->dist[i] = diags_dist->dist[i] / unif + 1; } // uniformization if (!compact_tr) { for (i = 0; i < nnz; i++) cmsm->non_zeros[i] /= unif; } else { for (i = 0; i < cmscsm->dist_num; i++) cmscsm->dist[i] /= unif; } // create solution/iteration vectors PS_PrintToMainLog(env, "Allocating iteration vectors... "); // for soln, we just use init (since we are free to modify/delete this vector) // we also report the memory usage of this vector here, even though it has already been created soln = init; soln2 = new double[n]; sum = new double[n]; kb = n*8.0/1024.0; kbt += 3*kb; PS_PrintMemoryToMainLog(env, "[3 x ", kb, "]\n"); // print total memory usage PS_PrintMemoryToMainLog(env, "TOTAL: [", kbt, "]\n"); // compute new termination criterion parameter (epsilon/8) term_crit_param_unif = term_crit_param / 8.0; // compute poisson probabilities (fox/glynn) PS_PrintToMainLog(env, "\nUniformisation: q.t = %f x %f = %f\n", unif, time, unif * time); fgw = fox_glynn(unif * time, 1.0e-300, 1.0e+300, term_crit_param_unif); if (fgw.right < 0) throw "Overflow in Fox-Glynn computation (time bound too big?)"; for (i = fgw.left; i <= fgw.right; i++) { fgw.weights[i-fgw.left] /= fgw.total_weight; } PS_PrintToMainLog(env, "Fox-Glynn: left = %ld, right = %ld\n", fgw.left, fgw.right); // set up vectors for (i = 0; i < n; i++) { sum[i] = 0.0; } // get setup time stop = util_cpu_time(); time_for_setup = (double)(stop - start2)/1000; start2 = stop; start3 = stop; // start transient analysis done = false; num_iters = -1; PS_PrintToMainLog(env, "\nStarting iterations...\n"); // if necessary, do 0th element of summation (doesn't require any matrix powers) if (fgw.left == 0) for (i = 0; i < n; i++) { sum[i] += fgw.weights[0] * soln[i]; } // note that we ignore max_iters as we know how any iterations _should_ be performed for (iters = 1; (iters <= fgw.right) && !done; iters++) { // store local copies of stuff double *non_zeros; unsigned char *col_counts; int *col_starts; bool use_counts; unsigned int *rows; double *dist; int dist_shift; int dist_mask; if (!compact_tr) { non_zeros = cmsm->non_zeros; col_counts = cmsm->col_counts; col_starts = (int *)cmsm->col_counts; use_counts = cmsm->use_counts; rows = cmsm->rows; } else { col_counts = cmscsm->col_counts; col_starts = (int *)cmscsm->col_counts; use_counts = cmscsm->use_counts; rows = cmscsm->rows; dist = cmscsm->dist; dist_shift = cmscsm->dist_shift; dist_mask = cmscsm->dist_mask; } // do matrix vector multiply bit h = 0; for (i = 0; i < n; i++) { d = (!compact_d) ? (diags[i] * soln[i]) : (diags_dist->dist[diags_dist->ptrs[i]] * soln[i]); if (!use_counts) { l = col_starts[i]; h = col_starts[i+1]; } else { l = h; h += col_counts[i]; } // "column major" version if (!compact_tr) { for (j = l; j < h; j++) { d += non_zeros[j] * soln[rows[j]]; } // "compact msc" version } else { for (j = l; j < h; j++) { d += dist[(int)(rows[j] & dist_mask)] * soln[(int)(rows[j] >> dist_shift)]; } } // set vector element soln2[i] = d; } // check for steady state convergence if (do_ss_detect) { measure.reset(); measure.measure(soln, soln2, n); if (measure.value() < term_crit_param_unif) { done = true; } } // special case when finished early (steady-state detected) if (done) { // work out sum of remaining poisson probabilities if (iters <= fgw.left) { weight = 1.0; } else { weight = 0.0; for (i = iters; i <= fgw.right; i++) { weight += fgw.weights[i-fgw.left]; } } // add to sum for (i = 0; i < n; i++) sum[i] += weight * soln2[i]; PS_PrintToMainLog(env, "\nSteady state detected at iteration %ld\n", iters); num_iters = iters; break; } // print occasional status update if ((util_cpu_time() - start3) > UPDATE_DELAY) { PS_PrintToMainLog(env, "Iteration %ld (of %ld): ", iters, fgw.right); if (do_ss_detect) PS_PrintToMainLog(env, "max %sdiff=%f, ", measure.isRelative()?"relative ":"", measure.value()); PS_PrintToMainLog(env, "%.2f sec so far\n", ((double)(util_cpu_time() - start2)/1000)); start3 = util_cpu_time(); } // prepare for next iteration tmpsoln = soln; soln = soln2; soln2 = tmpsoln; // add to sum if (iters >= fgw.left) { for (i = 0; i < n; i++) sum[i] += fgw.weights[iters-fgw.left] * soln[i]; } } // stop clocks stop = util_cpu_time(); time_for_iters = (double)(stop - start2)/1000; time_taken = (double)(stop - start1)/1000; // print iters/timing info if (num_iters == -1) num_iters = fgw.right; PS_PrintToMainLog(env, "\nIterative method: %ld iterations in %.2f seconds (average %.6f, setup %.2f)\n", num_iters, time_taken, time_for_iters/num_iters, time_for_setup); // catch exceptions: register error, free memory } catch (std::bad_alloc e) { PS_SetErrorMessage("Out of memory"); if (sum) delete[] sum; sum = 0; } catch (const char *err) { PS_SetErrorMessage("%s", err); if (sum) delete[] sum; sum = 0; } // free memory if (cmscsm) delete cmscsm; if (cmsm) delete cmsm; if (diags) delete[] diags; if (diags_dist) delete diags_dist; // nb: we *do* free soln (which was originally init) if (soln) delete[] soln; if (soln2) delete[] soln2; if (fgw.weights) delete[] fgw.weights; return ptr_to_jlong(sum); } //------------------------------------------------------------------------------