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changes to tracking values in mult-and-reduce functions of matrix

main
dehnert 8 years ago
parent
3952b47d1b
commit
0725b5e590
2 changed files with 84 additions and 38 deletions
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  1. 2
      src/storm/solver/Multiplier.h
  2. 120
      src/storm/storage/SparseMatrix.cpp

2
src/storm/solver/Multiplier.h
View File

@ -144,8 +144,6 @@ namespace storm {
~MultiplierFactory() = default; ~MultiplierFactory() = default;
std::unique_ptr<Multiplier<ValueType>> create(Environment const& env, storm::storage::SparseMatrix<ValueType> const& matrix); std::unique_ptr<Multiplier<ValueType>> create(Environment const& env, storm::storage::SparseMatrix<ValueType> const& matrix);
}; };
} }

120
src/storm/storage/SparseMatrix.cpp
View File

@ -1501,7 +1501,7 @@ namespace storm {
multiplyWithVectorParallel(vector, tmpVector); multiplyWithVectorParallel(vector, tmpVector);
result = std::move(tmpVector); result = std::move(tmpVector);
} else { } else {
tbb::parallel_for(tbb::blocked_range<index_type>(0, result.size(), 10), TbbMultAddFunctor<ValueType>(columnsAndValues, rowIndications, vector, result, summand));
tbb::parallel_for(tbb::blocked_range<index_type>(0, result.size(), 100), TbbMultAddFunctor<ValueType>(columnsAndValues, rowIndications, vector, result, summand));
} }
} }
#endif #endif
@ -1586,6 +1586,7 @@ namespace storm {
template<typename ValueType> template<typename ValueType>
void SparseMatrix<ValueType>::multiplyAndReduceForward(OptimizationDirection const& dir, std::vector<uint64_t> const& rowGroupIndices, std::vector<ValueType> const& vector, std::vector<ValueType> const* summand, std::vector<ValueType>& result, std::vector<uint_fast64_t>* choices) const { void SparseMatrix<ValueType>::multiplyAndReduceForward(OptimizationDirection const& dir, std::vector<uint64_t> const& rowGroupIndices, std::vector<ValueType> const& vector, std::vector<ValueType> const* summand, std::vector<ValueType>& result, std::vector<uint_fast64_t>* choices) const {
bool min = dir == OptimizationDirection::Minimize;
auto elementIt = this->begin(); auto elementIt = this->begin();
auto rowGroupIt = rowGroupIndices.begin(); auto rowGroupIt = rowGroupIndices.begin();
auto rowIt = rowIndications.begin(); auto rowIt = rowIndications.begin();
@ -1597,13 +1598,15 @@ namespace storm {
if (choices) { if (choices) {
choiceIt = choices->begin(); choiceIt = choices->begin();
} }
// Variables for correctly tracking choices (only update if new choice is strictly better).
ValueType oldSelectedChoiceValue;
uint64_t selectedChoice;
uint64_t currentRow = 0;
for (auto resultIt = result.begin(), resultIte = result.end(); resultIt != resultIte; ++resultIt, ++choiceIt, ++rowGroupIt) { for (auto resultIt = result.begin(), resultIte = result.end(); resultIt != resultIte; ++resultIt, ++choiceIt, ++rowGroupIt) {
ValueType currentValue = storm::utility::zero<ValueType>(); ValueType currentValue = storm::utility::zero<ValueType>();
if (choices) {
*choiceIt = 0;
}
// Only multiply and reduce if there is at least one row in the group. // Only multiply and reduce if there is at least one row in the group.
if (*rowGroupIt < *(rowGroupIt + 1)) { if (*rowGroupIt < *(rowGroupIt + 1)) {
if (summand) { if (summand) {
@ -1615,30 +1618,43 @@ namespace storm {
currentValue += elementIt->getValue() * vector[elementIt->getColumn()]; currentValue += elementIt->getValue() * vector[elementIt->getColumn()];
} }
if (choices) {
selectedChoice = 0;
if (*choiceIt == 0) {
oldSelectedChoiceValue = currentValue;
}
}
++rowIt; ++rowIt;
++currentRow;
for (; static_cast<uint_fast64_t>(std::distance(rowIndications.begin(), rowIt)) < *(rowGroupIt + 1); ++rowIt) {
for (; currentRow < *(rowGroupIt + 1); ++rowIt, ++currentRow) {
ValueType newValue = summand ? *summandIt : storm::utility::zero<ValueType>(); ValueType newValue = summand ? *summandIt : storm::utility::zero<ValueType>();
for (auto elementIte = this->begin() + *(rowIt + 1); elementIt != elementIte; ++elementIt) { for (auto elementIte = this->begin() + *(rowIt + 1); elementIt != elementIte; ++elementIt) {
newValue += elementIt->getValue() * vector[elementIt->getColumn()]; newValue += elementIt->getValue() * vector[elementIt->getColumn()];
} }
if ((dir == OptimizationDirection::Minimize && newValue < currentValue) || (dir == OptimizationDirection::Maximize && newValue > currentValue)) {
if (choices && currentRow == *choiceIt + *rowGroupIt) {
oldSelectedChoiceValue = newValue;
}
if (min ? newValue < currentValue : newValue > currentValue) {
currentValue = newValue; currentValue = newValue;
if (choices) { if (choices) {
*choiceIt = std::distance(rowIndications.begin(), rowIt) - *rowGroupIt;
selectedChoice = currentRow - *rowGroupIt;
} }
} }
if (summand) { if (summand) {
++summandIt; ++summandIt;
} }
} }
} else if (choices) {
*choiceIt = 0;
// Finally write value to target vector.
*resultIt = currentValue;
if (choices && (min ? currentValue < oldSelectedChoiceValue : currentValue > oldSelectedChoiceValue)) {
*choiceIt = selectedChoice;
}
} }
// Finally write value to target vector.
*resultIt = currentValue;
} }
} }
@ -1651,6 +1667,7 @@ namespace storm {
template<typename ValueType> template<typename ValueType>
void SparseMatrix<ValueType>::multiplyAndReduceBackward(OptimizationDirection const& dir, std::vector<uint64_t> const& rowGroupIndices, std::vector<ValueType> const& vector, std::vector<ValueType> const* summand, std::vector<ValueType>& result, std::vector<uint_fast64_t>* choices) const { void SparseMatrix<ValueType>::multiplyAndReduceBackward(OptimizationDirection const& dir, std::vector<uint64_t> const& rowGroupIndices, std::vector<ValueType> const& vector, std::vector<ValueType> const* summand, std::vector<ValueType>& result, std::vector<uint_fast64_t>* choices) const {
bool min = dir == OptimizationDirection::Minimize;
auto elementIt = this->end() - 1; auto elementIt = this->end() - 1;
auto rowGroupIt = rowGroupIndices.end() - 2; auto rowGroupIt = rowGroupIndices.end() - 2;
auto rowIt = rowIndications.end() - 2; auto rowIt = rowIndications.end() - 2;
@ -1662,13 +1679,15 @@ namespace storm {
if (choices) { if (choices) {
choiceIt = choices->end() - 1; choiceIt = choices->end() - 1;
} }
// Variables for correctly tracking choices (only update if new choice is strictly better).
ValueType oldSelectedChoiceValue;
uint64_t selectedChoice;
uint64_t currentRow = this->getRowCount() - 1;
for (auto resultIt = result.end() - 1, resultIte = result.begin() - 1; resultIt != resultIte; --resultIt, --choiceIt, --rowGroupIt) { for (auto resultIt = result.end() - 1, resultIte = result.begin() - 1; resultIt != resultIte; --resultIt, --choiceIt, --rowGroupIt) {
if (choices) {
*choiceIt = 0;
}
ValueType currentValue = storm::utility::zero<ValueType>(); ValueType currentValue = storm::utility::zero<ValueType>();
// Only multiply and reduce if there is at least one row in the group. // Only multiply and reduce if there is at least one row in the group.
if (*rowGroupIt < *(rowGroupIt + 1)) { if (*rowGroupIt < *(rowGroupIt + 1)) {
if (summand) { if (summand) {
@ -1680,27 +1699,38 @@ namespace storm {
currentValue += elementIt->getValue() * vector[elementIt->getColumn()]; currentValue += elementIt->getValue() * vector[elementIt->getColumn()];
} }
if (choices) { if (choices) {
*choiceIt = std::distance(rowIndications.begin(), rowIt) - *rowGroupIt;
selectedChoice = currentRow - *rowGroupIt;
if (*choiceIt == selectedChoice) {
oldSelectedChoiceValue = currentValue;
}
} }
--rowIt; --rowIt;
--currentRow;
for (uint64_t i = *rowGroupIt + 1, end = *(rowGroupIt + 1); i < end; --rowIt, ++i, --summandIt) {
for (uint64_t i = *rowGroupIt + 1, end = *(rowGroupIt + 1); i < end; --rowIt, --currentRow, ++i, --summandIt) {
ValueType newValue = summand ? *summandIt : storm::utility::zero<ValueType>(); ValueType newValue = summand ? *summandIt : storm::utility::zero<ValueType>();
for (auto elementIte = this->begin() + *rowIt - 1; elementIt != elementIte; --elementIt) { for (auto elementIte = this->begin() + *rowIt - 1; elementIt != elementIte; --elementIt) {
newValue += elementIt->getValue() * vector[elementIt->getColumn()]; newValue += elementIt->getValue() * vector[elementIt->getColumn()];
} }
if ((dir == OptimizationDirection::Minimize && newValue < currentValue) || (dir == OptimizationDirection::Maximize && newValue > currentValue)) {
if (choices && currentRow == *choiceIt + *rowGroupIt) {
oldSelectedChoiceValue = newValue;
}
if (min ? newValue < currentValue : newValue > currentValue) {
currentValue = newValue; currentValue = newValue;
if (choices) { if (choices) {
*choiceIt = std::distance(rowIndications.begin(), rowIt) - *rowGroupIt;
selectedChoice = currentRow - *rowGroupIt;
} }
} }
} }
// Finally write value to target vector.
*resultIt = currentValue;
if (choices && (min ? currentValue < oldSelectedChoiceValue : currentValue > oldSelectedChoiceValue)) {
*choiceIt = selectedChoice;
}
} }
// Finally write value to target vector.
*resultIt = currentValue;
} }
} }
@ -1724,6 +1754,8 @@ namespace storm {
} }
void operator()(tbb::blocked_range<index_type> const& range) const { void operator()(tbb::blocked_range<index_type> const& range) const {
bool min = dir == storm::OptimizationDirection::Minimize;
auto groupIt = rowGroupIndices.begin() + range.begin(); auto groupIt = rowGroupIndices.begin() + range.begin();
auto groupIte = rowGroupIndices.begin() + range.end(); auto groupIte = rowGroupIndices.begin() + range.end();
@ -1740,11 +1772,12 @@ namespace storm {
auto resultIt = result.begin() + range.begin(); auto resultIt = result.begin() + range.begin();
// Variables for correctly tracking choices (only update if new choice is strictly better).
ValueType oldSelectedChoiceValue;
uint64_t selectedChoice;
uint64_t currentRow = *groupIt;
for (; groupIt != groupIte; ++groupIt, ++resultIt, ++choiceIt) { for (; groupIt != groupIte; ++groupIt, ++resultIt, ++choiceIt) {
if (choices) {
*choiceIt = 0;
}
ValueType currentValue = storm::utility::zero<ValueType>(); ValueType currentValue = storm::utility::zero<ValueType>();
// Only multiply and reduce if there is at least one row in the group. // Only multiply and reduce if there is at least one row in the group.
@ -1758,25 +1791,40 @@ namespace storm {
currentValue += elementIt->getValue() * x[elementIt->getColumn()]; currentValue += elementIt->getValue() * x[elementIt->getColumn()];
} }
if (choices) {
selectedChoice = 0;
if (*choiceIt == 0) {
oldSelectedChoiceValue = currentValue;
}
}
++rowIt; ++rowIt;
++currentRow;
for (; static_cast<uint_fast64_t>(std::distance(rowIndications.begin(), rowIt)) < *(groupIt + 1); ++rowIt, ++summandIt) {
for (; currentRow < *(groupIt + 1); ++rowIt, ++currentRow, ++summandIt) {
ValueType newValue = summand ? *summandIt : storm::utility::zero<ValueType>(); ValueType newValue = summand ? *summandIt : storm::utility::zero<ValueType>();
for (auto elementIte = columnsAndEntries.begin() + *(rowIt + 1); elementIt != elementIte; ++elementIt) { for (auto elementIte = columnsAndEntries.begin() + *(rowIt + 1); elementIt != elementIte; ++elementIt) {
newValue += elementIt->getValue() * x[elementIt->getColumn()]; newValue += elementIt->getValue() * x[elementIt->getColumn()];
} }
if ((dir == OptimizationDirection::Minimize && newValue < currentValue) || (dir == OptimizationDirection::Maximize && newValue > currentValue)) {
if (choices && currentRow == *choiceIt + *groupIt) {
oldSelectedChoiceValue = newValue;
}
if (min ? newValue < currentValue : newValue > currentValue) {
currentValue = newValue; currentValue = newValue;
if (choices) { if (choices) {
*choiceIt = std::distance(rowIndications.begin(), rowIt) - *groupIt;
selectedChoice = currentRow - *groupIt;
} }
} }
} }
// Finally write value to target vector.
*resultIt = currentValue;
if (choices && (min ? currentValue < oldSelectedChoiceValue : currentValue > oldSelectedChoiceValue)) {
*choiceIt = selectedChoice;
}
} }
// Finally write value to target vector.
*resultIt = currentValue;
} }
} }
@ -1793,7 +1841,7 @@ namespace storm {
template<typename ValueType> template<typename ValueType>
void SparseMatrix<ValueType>::multiplyAndReduceParallel(OptimizationDirection const& dir, std::vector<uint64_t> const& rowGroupIndices, std::vector<ValueType> const& vector, std::vector<ValueType> const* summand, std::vector<ValueType>& result, std::vector<uint_fast64_t>* choices) const { void SparseMatrix<ValueType>::multiplyAndReduceParallel(OptimizationDirection const& dir, std::vector<uint64_t> const& rowGroupIndices, std::vector<ValueType> const& vector, std::vector<ValueType> const* summand, std::vector<ValueType>& result, std::vector<uint_fast64_t>* choices) const {
tbb::parallel_for(tbb::blocked_range<index_type>(0, rowGroupIndices.size() - 1, 10), TbbMultAddReduceFunctor<ValueType>(dir, rowGroupIndices, columnsAndValues, rowIndications, vector, result, summand, choices));
tbb::parallel_for(tbb::blocked_range<index_type>(0, rowGroupIndices.size() - 1, 100), TbbMultAddReduceFunctor<ValueType>(dir, rowGroupIndices, columnsAndValues, rowIndications, vector, result, summand, choices));
} }
#ifdef STORM_HAVE_CARL #ifdef STORM_HAVE_CARL

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