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//==============================================================================
//
// Copyright (c) 2002-
// Authors:
// * Dave Parker <david.parker@comlab.ox.ac.uk> (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 <cmath>
#include <util.h>
#include <cudd.h>
#include <dd.h>
#include <odd.h>
#include <dv.h>
#include <prism.h>
#include "sparse.h"
#include "PrismSparseGlob.h"
#include "jnipointer.h"
#include "Measures.h"
#include <new>
//------------------------------------------------------------------------------
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);
}
//------------------------------------------------------------------------------