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//==============================================================================
//
// Copyright (c) 2002-
// Authors:
// * Dave Parker <david.parker@comlab.ox.ac.uk> (University of Oxford, formerly University of Birmingham)
// * Joachim Klein <klein@tcs.inf.tu-dresden.de> (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 <cmath>
#include <util.h>
#include <cudd.h>
#include <dd.h>
#include <odd.h>
#include <dv.h>
#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 <memory>
#include <new>
// local prototypes
static void power_rec(HDDNode *hdd, int level, int row_offset, int col_offset, bool transpose);
static void power_rm(RMSparseMatrix *rmsm, int row_offset, int col_offset);
static void power_cmsr(CMSRSparseMatrix *cmsrsm, int row_offset, int col_offset);
// globals (used by local functions)
static HDDNode *zero;
static int num_levels;
static bool compact_sm;
static double *sm_dist;
static int sm_dist_shift;
static int sm_dist_mask;
static double *soln = NULL, *soln2 = NULL;
//------------------------------------------------------------------------------
// solve the linear equation system Ax=x with the Power method, interval variant
// in addition, solutions may be provided for additional states in the vector b
// these states are assumed not to have non-zero rows in the matrix A
JNIEXPORT jlong __jlongpointer JNICALL Java_hybrid_PrismHybrid_PH_1PowerInterval
(
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=x not Ax=x?)
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
// model stats
int n;
// flags
bool compact_b;
// matrix mtbdd
HDDMatrix *hddm = NULL;
HDDNode *hdd = NULL;
// vectors
double *b_vec = NULL, *tmpsoln = NULL;
double *soln_below = NULL, *soln_below2 = NULL, *soln_above = NULL, *soln_above2 = NULL;
DistVector *b_dist = NULL;
// timing stuff
long start1, start2, start3, stop;
double time_taken, time_for_setup, time_for_iters;
// misc
int i, iters;
double kb, kbt;
bool done;
// measure for convergence termination check
MeasureSupNormInterval measure(term_crit == TERM_CRIT_RELATIVE);
IntervalIteration helper(flags);
// exception handling around whole function
try {
// start clocks
start1 = start2 = util_cpu_time();
// get number of states
n = odd->eoff + odd->toff;
// make local copy of a
Cudd_Ref(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");
// add sparse matrices
PH_PrintToMainLog(env, "Adding explicit sparse matrices... ");
add_sparse_matrices(hddm, compact, false, 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;
}
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");
// 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);
soln_below2 = new double[n];
soln_above2 = new double[n];
kb = n*8.0/1024.0;
kbt += 4*kb;
PH_PrintMemoryToMainLog(env, "[4 x ", kb, "]\n");
// print total memory usage
PH_PrintMemoryToMainLog(env, "TOTAL: [", kbt, "]\n");
std::unique_ptr<ExportIterations> iterationExport;
if (PH_GetFlagExportIterations()) {
iterationExport.reset(new ExportIterations("PH_Power_Interval"));
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++;
// matrix multiply
// initialise vector (below & above)
if (b == NULL) {
for (i = 0; i < n; i++) { soln_below2[i] = soln_above2[i] = 0.0; }
} else if (!compact_b) {
for (i = 0; i < n; i++) { soln_below2[i] = soln_above2[i] = b_vec[i]; }
} else {
for (i = 0; i < n; i++) { soln_below2[i] = soln_above2[i] = b_dist->dist[b_dist->ptrs[i]]; }
}
// set global solution vector to below
soln = soln_below;
soln2 = soln_below2;
// do matrix vector multiply bit (below)
power_rec(hdd, 0, 0, 0, transpose);
if (helper.flag_ensure_monotonic_from_below()) {
helper.ensureMonotonicityFromBelow(soln, soln2, n);
}
// set global solution vector to above
soln = soln_above;
soln2 = soln_above2;
// do matrix vector multiply bit (above)
power_rec(hdd, 0, 0, 0, transpose);
if (helper.flag_ensure_monotonic_from_above()) {
helper.ensureMonotonicityFromAbove(soln, soln2, n);
}
if (iterationExport) {
iterationExport->exportVector(soln_below, n, 0);
iterationExport->exportVector(soln_above, n, 1);
}
// check convergence
measure.reset();
measure.measure(soln_below2, soln_above2, 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();
}
// prepare for next iteration
tmpsoln = soln_below;
soln_below = soln_below2;
soln_below2 = tmpsoln;
tmpsoln = soln_above;
soln_above = soln_above2;
soln_above2 = tmpsoln;
}
// 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, "\nPower method (interval iteration): %d iterations in %.2f seconds (average %.6f, setup %.2f)\n", 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 = 0;
}
// free memory
if (a) Cudd_RecursiveDeref(ddman, a);
if (hddm) delete hddm;
if (b_vec) delete[] b_vec;
if (b_dist) delete b_dist;
if (soln2) delete soln_below2;
if (soln_above) delete soln_above;
if (soln_above2) delete soln_above2;
return ptr_to_jlong(soln_below);
}
//------------------------------------------------------------------------------
static void power_rec(HDDNode *hdd, int level, int row_offset, int col_offset, 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) {
power_rm((RMSparseMatrix *)hdd->sm.ptr, row_offset, col_offset);
} else {
power_cmsr((CMSRSparseMatrix *)hdd->sm.ptr, row_offset, col_offset);
}
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[row_offset] += soln[col_offset] * hdd->type.val;
return;
}
// otherwise recurse
e = hdd->type.kids.e;
if (e != zero) {
if (!transpose) {
power_rec(e->type.kids.e, level+1, row_offset, col_offset, transpose);
power_rec(e->type.kids.t, level+1, row_offset, col_offset+e->off.val, transpose);
} else {
power_rec(e->type.kids.e, level+1, row_offset, col_offset, transpose);
power_rec(e->type.kids.t, level+1, row_offset+e->off.val, col_offset, transpose);
}
}
t = hdd->type.kids.t;
if (t != zero) {
if (!transpose) {
power_rec(t->type.kids.e, level+1, row_offset+hdd->off.val, col_offset, transpose);
power_rec(t->type.kids.t, level+1, row_offset+hdd->off.val, col_offset+t->off.val, transpose);
} else {
power_rec(t->type.kids.e, level+1, row_offset, col_offset+hdd->off.val, transpose);
power_rec(t->type.kids.t, level+1, row_offset+t->off.val, col_offset+hdd->off.val, transpose);
}
}
}
//-----------------------------------------------------------------------------------
static void power_rm(RMSparseMatrix *rmsm, int row_offset, int col_offset)
{
int 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 (i2 = 0; i2 < sm_n; i2++) {
// loop through entries in this row
if (!sm_use_counts) { l2 = sm_row_starts[i2]; h2 = sm_row_starts[i2+1]; }
else { l2 = h2; h2 += sm_row_counts[i2]; }
for (j2 = l2; j2 < h2; j2++) {
soln2[row_offset + i2] += soln[col_offset + sm_cols[j2]] * sm_non_zeros[j2];
//printf("(%d,%d)=%f\n", row_offset + i2, col_offset + sm_cols[j2], sm_non_zeros[j2]);
}
}
}
//-----------------------------------------------------------------------------------
static void power_cmsr(CMSRSparseMatrix *cmsrsm, int row_offset, int col_offset)
{
int 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 (i2 = 0; i2 < sm_n; i2++) {
// loop through entries in this row
if (!sm_use_counts) { l2 = sm_row_starts[i2]; h2 = sm_row_starts[i2+1]; }
else { l2 = h2; h2 += sm_row_counts[i2]; }
for (j2 = l2; j2 < h2; j2++) {
soln2[row_offset + i2] += soln[col_offset + (int)(sm_cols[j2] >> sm_dist_shift)] * sm_dist[(int)(sm_cols[j2] & sm_dist_mask)];
//printf("(%d,%d)=%f\n", row_offset + i2, col_offset + (int)(sm_cols[j2] >> sm_dist_shift), sm_dist[(int)(sm_cols[j2] & sm_dist_mask)]);
}
}
}
//------------------------------------------------------------------------------