sp
/
tempest
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity
Browse Source

fixed multiply-reduce operations in the presence of empty row groups

tempestpy_adaptions
dehnert 7 years ago
parent
d25cc4b05f
commit
df0b5fbfa5
7 changed files with 157 additions and 149 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Split View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 3
      src/storm-cli-utilities/model-handling.h
  2. 3
      src/storm/modelchecker/prctl/helper/SparseMdpPrctlHelper.cpp
  3. 80
      src/storm/solver/GmmxxMultiplier.cpp
  4. 10
      src/storm/solver/IterativeMinMaxLinearEquationSolver.cpp
  5. 4
      src/storm/solver/NativeLinearEquationSolver.cpp
  6. 122
      src/storm/storage/SparseMatrix.cpp
  7. 84
      src/storm/utility/vector.h

3
src/storm-cli-utilities/model-handling.h
View File

@ -644,7 +644,10 @@ namespace storm {
template <typename ValueType>
void processInputWithValueType(SymbolicInput const& input) {
auto coreSettings = storm::settings::getModule<storm::settings::modules::CoreSettings>();
auto generalSettings = storm::settings::getModule<storm::settings::modules::GeneralSettings>();
STORM_LOG_THROW(!generalSettings.isSoundSet() || coreSettings.getEngine() == storm::settings::modules::CoreSettings::Engine::Sparse, storm::exceptions::NotSupportedException, "Forcing soundness is not supported for engines other than the sparse engine.");
if (coreSettings.getDdLibraryType() == storm::dd::DdType::CUDD) {
processInputWithValueTypeAndDdlib<storm::dd::DdType::CUDD, ValueType>(input);
} else {

3
src/storm/modelchecker/prctl/helper/SparseMdpPrctlHelper.cpp
View File

@ -209,6 +209,9 @@ namespace storm {
result.schedulerHint = computeValidSchedulerHint(type, transitionMatrix, backwardTransitions, maybeStates, phiStates, targetStates);
requirements.clearValidInitialScheduler();
}
if (type == storm::solver::EquationSystemType::UntilProbabilities) {
requirements.clearGlobalUpperBound();
}
STORM_LOG_THROW(requirements.empty(), storm::exceptions::UncheckedRequirementException, "There are unchecked requirements of the solver.");
}

80
src/storm/solver/GmmxxMultiplier.cpp
View File

@ -81,35 +81,39 @@ namespace storm {
uint64_t choice;
for (auto row_group_it = rowGroupIndices.end() - 2, row_group_ite = rowGroupIndices.begin() - 1; row_group_it != row_group_ite; --row_group_it, --choice_it, --target_it) {
T currentValue = b ? *add_it : storm::utility::zero<T>();
currentValue += vect_sp(gmm::linalg_traits<MatrixType>::row(itr), x);
--add_it;
if (choices) {
choice = *(row_group_it + 1) - 1 - *row_group_it;
*choice_it = choice;
}
--itr;
if (b) {
--add_it;
}
for (uint64_t row = *row_group_it + 1, rowEnd = *(row_group_it + 1); row < rowEnd; ++row, --itr) {
T newValue = b ? *add_it : storm::utility::zero<T>();
newValue += vect_sp(gmm::linalg_traits<MatrixType>::row(itr), x);
// Only multiply and reduce if the row group is not empty.
if (*row_group_it != *(row_group_it + 1)) {
currentValue += vect_sp(gmm::linalg_traits<MatrixType>::row(itr), x);
if (choices) {
--choice;
choice = *(row_group_it + 1) - 1 - *row_group_it;
*choice_it = choice;
}
if ((dir == OptimizationDirection::Minimize && newValue < currentValue) || (dir == OptimizationDirection::Maximize && newValue > currentValue)) {
currentValue = newValue;
--itr;
for (uint64_t row = *row_group_it + 1, rowEnd = *(row_group_it + 1); row < rowEnd; ++row, --itr) {
T newValue = b ? *add_it : storm::utility::zero<T>();
newValue += vect_sp(gmm::linalg_traits<MatrixType>::row(itr), x);
if (choices) {
*choice_it = choice;
--choice;
}
if ((dir == OptimizationDirection::Minimize && newValue < currentValue) || (dir == OptimizationDirection::Maximize && newValue > currentValue)) {
currentValue = newValue;
if (choices) {
*choice_it = choice;
}
}
if (b) {
--add_it;
}
}
if (b) {
--add_it;
}
} else if (choices) {
*choice_it = 0;
}
// Write back final value.
@ -161,28 +165,28 @@ namespace storm {
auto resultIt = result.begin() + range.begin();
for (; groupIt != groupIte; ++groupIt, ++resultIt, ++choiceIt) {
T currentValue = vect_sp(gmm::linalg_traits<gmm::csr_matrix<T>>::row(itr), x, typename gmm::linalg_traits<gmm::csr_matrix<T>>::storage_type(), typename gmm::linalg_traits<std::vector<T>>::storage_type());
if (b) {
currentValue += *bIt;
++bIt;
}
T currentValue = b ? *bIt : storm::utility::zero<T>();
++bIt;
if (choices) {
*choiceIt = 0;
}
++itr;
for (auto itre = mat_row_const_begin(matrix) + *(groupIt + 1); itr != itre; ++itr) {
T newValue = vect_sp(gmm::linalg_traits<gmm::csr_matrix<T>>::row(itr), x, typename gmm::linalg_traits<gmm::csr_matrix<T>>::storage_type(), typename gmm::linalg_traits<std::vector<T>>::storage_type());
if (b) {
newValue += *bIt;
++bIt;
}
// Only multiply and reduce if the row group is not empty.
if (*groupIt != *(groupIt + 1)) {
++itr;
if ((dir == OptimizationDirection::Minimize && newValue < currentValue) || (dir == OptimizationDirection::Maximize && newValue > currentValue)) {
currentValue = newValue;
if (choices) {
*choiceIt = std::distance(mat_row_const_begin(matrix), itr) - *groupIt;
for (auto itre = mat_row_const_begin(matrix) + *(groupIt + 1); itr != itre; ++itr) {
T newValue = vect_sp(gmm::linalg_traits<gmm::csr_matrix<T>>::row(itr), x, typename gmm::linalg_traits<gmm::csr_matrix<T>>::storage_type(), typename gmm::linalg_traits<std::vector<T>>::storage_type());
if (b) {
newValue += *bIt;
++bIt;
}
if ((dir == OptimizationDirection::Minimize && newValue < currentValue) || (dir == OptimizationDirection::Maximize && newValue > currentValue)) {
currentValue = newValue;
if (choices) {
*choiceIt = std::distance(mat_row_const_begin(matrix), itr) - *groupIt;
}
}
}
}

10
src/storm/solver/IterativeMinMaxLinearEquationSolver.cpp
View File

@ -253,7 +253,9 @@ namespace storm {
// If we will use sound value iteration, we require no ECs and an upper bound.
if (this->getSettings().getSolutionMethod() == IterativeMinMaxLinearEquationSolverSettings<ValueType>::SolutionMethod::ValueIteration && this->getSettings().getForceSoundness()) {
requirements.requireNoEndComponents();
if (!direction || direction.get() == OptimizationDirection::Maximize) {
requirements.requireNoEndComponents();
}
requirements.requireGlobalUpperBound();
}
@ -375,6 +377,7 @@ namespace storm {
}
if (this->hasInitialScheduler()) {
STORM_LOG_TRACE("Solving initial scheduler hint.");
// Resolve the nondeterminism according to the initial scheduler.
bool convertToEquationSystem = this->linearEquationSolverFactory->getEquationProblemFormat() == LinearEquationSolverProblemFormat::EquationSystem;
storm::storage::SparseMatrix<ValueType> submatrix = this->A->selectRowsFromRowGroups(this->getInitialScheduler(), convertToEquationSystem);
@ -398,6 +401,11 @@ namespace storm {
// Allow aliased multiplications.
bool useGaussSeidelMultiplication = this->linEqSolverA->supportsGaussSeidelMultiplication() && settings.getValueIterationMultiplicationStyle() == storm::solver::MultiplicationStyle::GaussSeidel;
// Initialize upper bound vector.
for (auto& e : *this->auxiliaryRowGroupVector) {
e = this->getUpperBound();
}
std::vector<ValueType>* lowerX = &x;
std::vector<ValueType>* upperX = this->auxiliaryRowGroupVector.get();
std::vector<ValueType>* tmp;

4
src/storm/solver/NativeLinearEquationSolver.cpp
View File

@ -436,6 +436,10 @@ namespace storm {
std::vector<ValueType>* lowerX = &x;
if (!this->cachedRowVector) {
this->cachedRowVector = std::make_unique<std::vector<ValueType>>(getMatrixRowCount(), this->getUpperBound());
} else {
for (auto& e : *this->cachedRowVector) {
e = this->getUpperBound();
}
}
std::vector<ValueType>* upperX = this->cachedRowVector.get();

122
src/storm/storage/SparseMatrix.cpp
View File

@ -1523,33 +1523,37 @@ namespace storm {
for (auto resultIt = result.begin(), resultIte = result.end(); resultIt != resultIte; ++resultIt, ++choiceIt, ++rowGroupIt) {
ValueType currentValue = summand ? *summandIt : storm::utility::zero<ValueType>();
for (auto elementIte = this->begin() + *(rowIt + 1); elementIt != elementIte; ++elementIt) {
currentValue += elementIt->getValue() * vector[elementIt->getColumn()];
}
++summandIt;
if (choices) {
*choiceIt = 0;
}
++rowIt;
if (summand) {
++summandIt;
}
for (; static_cast<uint_fast64_t>(std::distance(rowIndications.begin(), rowIt)) < *(rowGroupIt + 1); ++rowIt) {
ValueType newValue = summand ? *summandIt : storm::utility::zero<ValueType>();
// Only multiply and reduce if there is at least one row in the group.
if (*rowGroupIt < *(rowGroupIt + 1)) {
for (auto elementIte = this->begin() + *(rowIt + 1); elementIt != elementIte; ++elementIt) {
newValue += elementIt->getValue() * vector[elementIt->getColumn()];
currentValue += elementIt->getValue() * vector[elementIt->getColumn()];
}
if (choices) {
*choiceIt = 0;
}
if ((dir == OptimizationDirection::Minimize && newValue < currentValue) || (dir == OptimizationDirection::Maximize && newValue > currentValue)) {
currentValue = newValue;
if (choices) {
*choiceIt = std::distance(rowIndications.begin(), rowIt) - *rowGroupIt;
++rowIt;
for (; static_cast<uint_fast64_t>(std::distance(rowIndications.begin(), rowIt)) < *(rowGroupIt + 1); ++rowIt) {
ValueType newValue = summand ? *summandIt : storm::utility::zero<ValueType>();
for (auto elementIte = this->begin() + *(rowIt + 1); elementIt != elementIte; ++elementIt) {
newValue += elementIt->getValue() * vector[elementIt->getColumn()];
}
if ((dir == OptimizationDirection::Minimize && newValue < currentValue) || (dir == OptimizationDirection::Maximize && newValue > currentValue)) {
currentValue = newValue;
if (choices) {
*choiceIt = std::distance(rowIndications.begin(), rowIt) - *rowGroupIt;
}
}
if (summand) {
++summandIt;
}
}
if (summand) {
++summandIt;
}
}
@ -1581,34 +1585,37 @@ namespace storm {
for (auto resultIt = result.end() - 1, resultIte = result.begin() - 1; resultIt != resultIte; --resultIt, --choiceIt, --rowGroupIt) {
ValueType currentValue = summand ? *summandIt : storm::utility::zero<ValueType>();
--summandIt;
for (auto elementIte = this->begin() + *rowIt - 1; elementIt != elementIte; --elementIt) {
currentValue += elementIt->getValue() * vector[elementIt->getColumn()];
}
if (choices) {
*choiceIt = std::distance(rowIndications.begin(), rowIt) - *rowGroupIt;
}
--rowIt;
if (summand) {
--summandIt;
}
for (uint64_t i = *rowGroupIt + 1, end = *(rowGroupIt + 1); i < end; --rowIt, ++i) {
ValueType newValue = summand ? *summandIt : storm::utility::zero<ValueType>();
// Only multiply and reduce if there is at least one row in the group.
if (*rowGroupIt < *(rowGroupIt + 1)) {
for (auto elementIte = this->begin() + *rowIt - 1; elementIt != elementIte; --elementIt) {
newValue += elementIt->getValue() * vector[elementIt->getColumn()];
currentValue += elementIt->getValue() * vector[elementIt->getColumn()];
}
if ((dir == OptimizationDirection::Minimize && newValue < currentValue) || (dir == OptimizationDirection::Maximize && newValue > currentValue)) {
currentValue = newValue;
if (choices) {
*choiceIt = std::distance(rowIndications.begin(), rowIt) - *rowGroupIt;
}
if (choices) {
*choiceIt = std::distance(rowIndications.begin(), rowIt) - *rowGroupIt;
}
if (summand) {
--summandIt;
--rowIt;
for (uint64_t i = *rowGroupIt + 1, end = *(rowGroupIt + 1); i < end; --rowIt, ++i) {
ValueType newValue = summand ? *summandIt : storm::utility::zero<ValueType>();
for (auto elementIte = this->begin() + *rowIt - 1; elementIt != elementIte; --elementIt) {
newValue += elementIt->getValue() * vector[elementIt->getColumn()];
}
if ((dir == OptimizationDirection::Minimize && newValue < currentValue) || (dir == OptimizationDirection::Maximize && newValue > currentValue)) {
currentValue = newValue;
if (choices) {
*choiceIt = std::distance(rowIndications.begin(), rowIt) - *rowGroupIt;
}
}
if (summand) {
--summandIt;
}
}
} else if (choices) {
*choiceIt = 0;
}
// Finally write value to target vector.
@ -1654,27 +1661,30 @@ namespace storm {
for (; groupIt != groupIte; ++groupIt, ++resultIt, ++choiceIt) {
ValueType currentValue = summand ? *summandIt : storm::utility::zero<ValueType>();
for (auto elementIte = columnsAndEntries.begin() + *(rowIt + 1); elementIt != elementIte; ++elementIt) {
currentValue += elementIt->getValue() * x[elementIt->getColumn()];
}
++summandIt;
if (choices) {
*choiceIt = 0;
}
++rowIt;
++summandIt;
for (; static_cast<uint_fast64_t>(std::distance(rowIndications.begin(), rowIt)) < *(groupIt + 1); ++rowIt, ++summandIt) {
ValueType newValue = summand ? *summandIt : storm::utility::zero<ValueType>();
// Only multiply and reduce if there is at least one row in the group.
if (*groupIt < *(groupIt + 1)) {
for (auto elementIte = columnsAndEntries.begin() + *(rowIt + 1); elementIt != elementIte; ++elementIt) {
newValue += elementIt->getValue() * x[elementIt->getColumn()];
currentValue += elementIt->getValue() * x[elementIt->getColumn()];
}
if ((dir == OptimizationDirection::Minimize && newValue < currentValue) || (dir == OptimizationDirection::Maximize && newValue > currentValue)) {
currentValue = newValue;
if (choices) {
*choiceIt = std::distance(rowIndications.begin(), rowIt) - *groupIt;
++rowIt;
for (; static_cast<uint_fast64_t>(std::distance(rowIndications.begin(), rowIt)) < *(groupIt + 1); ++rowIt, ++summandIt) {
ValueType newValue = summand ? *summandIt : storm::utility::zero<ValueType>();
for (auto elementIte = columnsAndEntries.begin() + *(rowIt + 1); elementIt != elementIte; ++elementIt) {
newValue += elementIt->getValue() * x[elementIt->getColumn()];
}
if ((dir == OptimizationDirection::Minimize && newValue < currentValue) || (dir == OptimizationDirection::Maximize && newValue > currentValue)) {
currentValue = newValue;
if (choices) {
*choiceIt = std::distance(rowIndications.begin(), rowIt) - *groupIt;
}
}
}
}

84
src/storm/utility/vector.h
View File

@ -627,36 +627,24 @@ namespace storm {
}
for (; targetIt != targetIte; ++targetIt, ++rowGroupingIt) {
// Only do work if the row group is not empty.
if (*rowGroupingIt != *(rowGroupingIt + 1)) {
*targetIt = *sourceIt;
++sourceIt;
localChoice = 1;
if (choices != nullptr) {
*choiceIt = 0;
}
for (sourceIte = source.begin() + *(rowGroupingIt + 1); sourceIt != sourceIte; ++sourceIt, ++localChoice) {
if (f(*sourceIt, *targetIt)) {
*targetIt = *sourceIt;
if (choices != nullptr) {
*choiceIt = localChoice;
}
*targetIt = *sourceIt;
++sourceIt;
localChoice = 1;
if (choices != nullptr) {
*choiceIt = 0;
}
for (sourceIte = source.begin() + *(rowGroupingIt + 1); sourceIt != sourceIte; ++sourceIt, ++localChoice) {
if (f(*sourceIt, *targetIt)) {
*targetIt = *sourceIt;
if (choices != nullptr) {
*choiceIt = localChoice;
}
}
if (choices != nullptr) {
++choiceIt;
}
} else {
// Compensate for the 'wrong' move forward in the loop header.
--targetIt;
// Record dummy choice.
if (choices != nullptr) {
*choiceIt = 0;
++choiceIt;
}
}
if (choices != nullptr) {
++choiceIt;
}
}
}
@ -695,34 +683,22 @@ namespace storm {
}
for (; targetIt != targetIte; ++targetIt, ++rowGroupingIt) {
// Only do work if the row group is not empty.
if (*rowGroupingIt != *(rowGroupingIt + 1)) {
*targetIt = *sourceIt;
++sourceIt;
localChoice = 1;
if (choices != nullptr) {
*choiceIt = 0;
}
for (sourceIte = source.begin() + *(rowGroupingIt + 1); sourceIt != sourceIte; ++sourceIt, ++localChoice) {
if (f(*sourceIt, *targetIt)) {
*targetIt = *sourceIt;
if (choices != nullptr) {
*choiceIt = localChoice;
}
*targetIt = *sourceIt;
++sourceIt;
localChoice = 1;
if (choices != nullptr) {
*choiceIt = 0;
}
for (sourceIte = source.begin() + *(rowGroupingIt + 1); sourceIt != sourceIte; ++sourceIt, ++localChoice) {
if (f(*sourceIt, *targetIt)) {
*targetIt = *sourceIt;
if (choices != nullptr) {
*choiceIt = localChoice;
}
}
if (choices != nullptr) {
++choiceIt;
}
} else {
// Compensate for the 'wrong' move forward in the loop header.
--targetIt;
// Record dummy choice.
if (choices != nullptr) {
*choiceIt = 0;
++choiceIt;
}
}
if (choices != nullptr) {
++choiceIt;
}
}
}

Write Preview
Loading…
Cancel
Save