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implemented gauss-seidl multiplications and relative termination for quick power iteration

tempestpy_adaptions
TimQu 7 years ago
parent
b55e92bef7
commit
bb0c0bbeb6
1 changed files with 68 additions and 40 deletions
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  1. 108
      src/storm/solver/NativeLinearEquationSolver.cpp

108
src/storm/solver/NativeLinearEquationSolver.cpp
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@ -558,23 +558,37 @@ namespace storm {
template<typename ValueType>
bool NativeLinearEquationSolver<ValueType>::solveEquationsQuickSoundPower(Environment const& env, std::vector<ValueType>& x, std::vector<ValueType> const& b) const {
STORM_LOG_INFO("Solving linear equation system (" << x.size() << " rows) with NativeLinearEquationSolver (QuickPower)");
bool useGaussSeidelMultiplication = env.solver().native().getPowerMethodMultiplicationStyle() == storm::solver::MultiplicationStyle::GaussSeidel;
// Prepare the solution vectors.
if (!this->cachedRowVector) {
this->cachedRowVector = std::make_unique<std::vector<ValueType>>(getMatrixRowCount(), storm::utility::zero<ValueType>());
} else {
this->cachedRowVector->assign(getMatrixRowCount(), storm::utility::zero<ValueType>());
}
if (!this->cachedRowVector2) {
this->cachedRowVector2 = std::make_unique<std::vector<ValueType>>(getMatrixRowCount(), storm::utility::one<ValueType>());
assert(x.size() == getMatrixRowCount());
std::vector<ValueType> *stepBoundedX, *stepBoundedStayProbs, *tmp;
if (useGaussSeidelMultiplication) {
stepBoundedX = &x;
stepBoundedX->assign(getMatrixRowCount(), storm::utility::zero<ValueType>());
if (!this->cachedRowVector) {
this->cachedRowVector = std::make_unique<std::vector<ValueType>>(getMatrixRowCount(), storm::utility::one<ValueType>());
} else {
this->cachedRowVector->assign(getMatrixRowCount(), storm::utility::one<ValueType>());
}
stepBoundedStayProbs = this->cachedRowVector.get();
tmp = nullptr;
} else {
this->cachedRowVector2->assign(getMatrixRowCount(), storm::utility::one<ValueType>());
if (!this->cachedRowVector) {
this->cachedRowVector = std::make_unique<std::vector<ValueType>>(getMatrixRowCount(), storm::utility::zero<ValueType>());
} else {
this->cachedRowVector->assign(getMatrixRowCount(), storm::utility::zero<ValueType>());
}
stepBoundedX = this->cachedRowVector.get();
if (!this->cachedRowVector2) {
this->cachedRowVector2 = std::make_unique<std::vector<ValueType>>(getMatrixRowCount(), storm::utility::one<ValueType>());
} else {
this->cachedRowVector2->assign(getMatrixRowCount(), storm::utility::one<ValueType>());
}
stepBoundedStayProbs = this->cachedRowVector2.get();
tmp = &x;
}
std::vector<ValueType>* stepBoundedValues = this->cachedRowVector.get();
std::vector<ValueType>* stepBoundedStayProbabilities = this->cachedRowVector2.get();
std::vector<ValueType>* tmp = &x;
ValueType precision = storm::utility::convertNumber<ValueType>(env.solver().native().getPrecision());
bool relative = env.solver().native().getRelativeTerminationCriterion();
if (!relative) {
@ -598,43 +612,53 @@ namespace storm {
while (!converged && !terminate && iterations < maxIter) {
// Apply step
this->multiplier.multAdd(*this->A, *stepBoundedValues, &b, *tmp);
std::swap(tmp, stepBoundedValues);
this->multiplier.multAdd(*this->A, *stepBoundedStayProbabilities, nullptr, *tmp);
std::swap(tmp, stepBoundedStayProbabilities);
if (useGaussSeidelMultiplication) {
this->multiplier.multAddGaussSeidelBackward(*this->A, *stepBoundedX, &b);
this->multiplier.multAddGaussSeidelBackward(*this->A, *stepBoundedStayProbs, nullptr);
} else {
this->multiplier.multAdd(*this->A, *stepBoundedX, &b, *tmp);
std::swap(tmp, stepBoundedX);
this->multiplier.multAdd(*this->A, *stepBoundedStayProbs, nullptr, *tmp);
std::swap(tmp, stepBoundedStayProbs);
}
//std::cout << "Iteration " << iterations << std::endl;
//std::cout << "x: " << storm::utility::vector::toString(*stepBoundedValues) << std::endl;
//std::cout << "y: " << storm::utility::vector::toString(*stepBoundedStayProbabilities) << std::endl;
//std::cout << "x: " << storm::utility::vector::toString(*stepBoundedX) << std::endl;
//std::cout << "y: " << storm::utility::vector::toString(*stepBoundedStayProbs) << std::endl;
// Check for convergence
// Phase 1: the probability to 'stay within the matrix' has to be < 1 at every state
for (; firstStayProb1Index != stepBoundedStayProbabilities->size(); ++firstStayProb1Index) {
for (; firstStayProb1Index != stepBoundedStayProbs->size(); ++firstStayProb1Index) {
static_assert(NumberTraits<ValueType>::IsExact || std::is_same<ValueType, double>::value, "Considered ValueType not handled.");
if (NumberTraits<ValueType>::IsExact) {
if (storm::utility::isOne(stepBoundedStayProbabilities->at(firstStayProb1Index))) {
if (storm::utility::isOne(stepBoundedStayProbs->at(firstStayProb1Index))) {
break;
}
} else {
if (storm::utility::isAlmostOne(storm::utility::convertNumber<double>(stepBoundedStayProbabilities->at(firstStayProb1Index)))) {
if (storm::utility::isAlmostOne(storm::utility::convertNumber<double>(stepBoundedStayProbs->at(firstStayProb1Index)))) {
break;
// std::cout << "In Phase 1" << std::endl;
}
}
}
if (firstStayProb1Index == stepBoundedStayProbabilities->size()) {
STORM_LOG_ASSERT(!std::any_of(stepBoundedStayProbabilities->begin(), stepBoundedStayProbabilities->end(), [](ValueType value){return storm::utility::isOne(value);}), "Did not expect staying-probability 1 at this point.");
if (firstStayProb1Index == stepBoundedStayProbs->size()) {
STORM_LOG_ASSERT(!std::any_of(stepBoundedStayProbs->begin(), stepBoundedStayProbs->end(), [](ValueType value){return storm::utility::isOne(value);}), "Did not expect staying-probability 1 at this point.");
// Phase 2: the difference between lower and upper bound has to be < precision at every (relevant) value
// std::cout << "In Phase 2" << std::endl;
// First check with (possibly too tight) bounds from a previous iteration. Only compute the actual bounds if this first check passes.
minValueBound = stepBoundedValues->at(minIndex) / (storm::utility::one<ValueType>() - stepBoundedStayProbabilities->at(minIndex));
maxValueBound = stepBoundedValues->at(maxIndex) / (storm::utility::one<ValueType>() - stepBoundedStayProbabilities->at(maxIndex));
ValueType const& stayProb = stepBoundedStayProbabilities->at(firstIndexViolatingConvergence);
if (stayProb * (maxValueBound - minValueBound) < precision) {
minValueBound = stepBoundedX->at(minIndex) / (storm::utility::one<ValueType>() - stepBoundedStayProbs->at(minIndex));
maxValueBound = stepBoundedX->at(maxIndex) / (storm::utility::one<ValueType>() - stepBoundedStayProbs->at(maxIndex));
ValueType const& stayProb = stepBoundedStayProbs->at(firstIndexViolatingConvergence);
// The error made in this iteration
ValueType absoluteError = stayProb * (maxValueBound - minValueBound);
// The maximal allowed error (possibly respecting relative precision)
// Note: We implement the relative convergence criterion in a way that avoids division by zero in the case where stepBoundedX[i] is zero.
ValueType maxAllowedError = relative ? (precision * stepBoundedX->at(firstIndexViolatingConvergence)) : precision;
if (absoluteError <= maxAllowedError) {
// Compute the actual bounds now
auto valIt = stepBoundedValues->begin();
auto valIte = stepBoundedValues->end();
auto probIt = stepBoundedStayProbabilities->begin();
auto valIt = stepBoundedX->begin();
auto valIte = stepBoundedX->end();
auto probIt = stepBoundedStayProbs->begin();
for (uint64_t index = 0; valIt != valIte; ++valIt, ++probIt, ++index) {
ValueType currentBound = *valIt / (storm::utility::one<ValueType>() - *probIt);
if (currentBound < minValueBound) {
@ -645,24 +669,28 @@ namespace storm {
maxValueBound = std::move(currentBound);
}
}
if (stayProb * (maxValueBound - minValueBound) < precision) {
absoluteError = stayProb * (maxValueBound - minValueBound);
if (absoluteError <= maxAllowedError) {
// The current index satisfies the desired bound. We now move to the next index that violates it
do {
while (true) {
++firstIndexViolatingConvergence;
if (this->hasRelevantValues()) {
firstIndexViolatingConvergence = this->getRelevantValues().getNextSetIndex(firstIndexViolatingConvergence);
}
if (firstIndexViolatingConvergence == stepBoundedStayProbabilities->size()) {
if (firstIndexViolatingConvergence == stepBoundedStayProbs->size()) {
converged = true;
break;
} else if (stepBoundedStayProbabilities->at(firstIndexViolatingConvergence) * (maxValueBound - minValueBound) >= precision) {
// not converged yet
break;
} else {
absoluteError = stepBoundedStayProbs->at(firstIndexViolatingConvergence) * (maxValueBound - minValueBound);
maxAllowedError = relative ? (precision * stepBoundedX->at(firstIndexViolatingConvergence)) : precision;
if (absoluteError > maxAllowedError) {
// not converged yet
break;
}
}
} while (true);
}
}
}
STORM_LOG_ASSERT(!relative, "Relative termination criterion not implemented currently.");
}
// Potentially show progress.
@ -675,7 +703,7 @@ namespace storm {
// Finally set up the solution vector
ValueType meanBound = (maxValueBound + minValueBound) / storm::utility::convertNumber<ValueType>(2.0);
storm::utility::vector::applyPointwise(*stepBoundedValues, *stepBoundedStayProbabilities, x, [&meanBound] (ValueType const& v, ValueType const& p) { return v + p * meanBound; });
storm::utility::vector::applyPointwise(*stepBoundedX, *stepBoundedStayProbs, x, [&meanBound] (ValueType const& v, ValueType const& p) { return v + p * meanBound; });
if (!this->isCachingEnabled()) {
clearCache();

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