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136 lines
6.6 KiB
136 lines
6.6 KiB
#include "src/solver/GmmxxNondeterministicLinearEquationSolver.h"
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#include <utility>
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#include "src/settings/Settings.h"
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#include "src/adapters/GmmxxAdapter.h"
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#include "src/utility/vector.h"
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namespace storm {
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namespace solver {
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template<typename ValueType>
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GmmxxNondeterministicLinearEquationSolver<ValueType>::GmmxxNondeterministicLinearEquationSolver() {
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// Get the settings object to customize solving.
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storm::settings::Settings* settings = storm::settings::Settings::getInstance();
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// Get appropriate settings.
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maximalNumberOfIterations = settings->getOptionByLongName("maxiter").getArgument(0).getValueAsUnsignedInteger();
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precision = settings->getOptionByLongName("precision").getArgument(0).getValueAsDouble();
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relative = !settings->isSet("absolute");
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}
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template<typename ValueType>
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GmmxxNondeterministicLinearEquationSolver<ValueType>::GmmxxNondeterministicLinearEquationSolver(double precision, uint_fast64_t maximalNumberOfIterations, bool relative) : precision(precision), relative(relative), maximalNumberOfIterations(maximalNumberOfIterations) {
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// Intentionally left empty.
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}
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template<typename ValueType>
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NondeterministicLinearEquationSolver<ValueType>* GmmxxNondeterministicLinearEquationSolver<ValueType>::clone() const {
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return new GmmxxNondeterministicLinearEquationSolver<ValueType>(*this);
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}
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template<typename ValueType>
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void GmmxxNondeterministicLinearEquationSolver<ValueType>::solveEquationSystem(bool minimize, storm::storage::SparseMatrix<ValueType> const& A, std::vector<ValueType>& x, std::vector<ValueType> const& b, std::vector<ValueType>* multiplyResult, std::vector<ValueType>* newX) const {
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// Transform the transition probability matrix to the gmm++ format to use its arithmetic.
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std::unique_ptr<gmm::csr_matrix<ValueType>> gmmxxMatrix = storm::adapters::GmmxxAdapter::toGmmxxSparseMatrix<ValueType>(A);
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// Set up the environment for the power method. If scratch memory was not provided, we need to create it.
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bool multiplyResultMemoryProvided = true;
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if (multiplyResult == nullptr) {
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multiplyResult = new std::vector<ValueType>(A.getRowCount());
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multiplyResultMemoryProvided = false;
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}
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std::vector<ValueType>* currentX = &x;
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bool xMemoryProvided = true;
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if (newX == nullptr) {
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newX = new std::vector<ValueType>(x.size());
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xMemoryProvided = false;
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}
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uint_fast64_t iterations = 0;
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bool converged = false;
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// Keep track of which of the vectors for x is the auxiliary copy.
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std::vector<ValueType>* copyX = newX;
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// Proceed with the iterations as long as the method did not converge or reach the user-specified maximum number
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// of iterations.
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while (!converged && iterations < maximalNumberOfIterations) {
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// Compute x' = A*x + b.
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gmm::mult(*gmmxxMatrix, *currentX, *multiplyResult);
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gmm::add(b, *multiplyResult);
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// Reduce the vector x by applying min/max over all nondeterministic choices.
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if (minimize) {
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storm::utility::vector::reduceVectorMin(*multiplyResult, *newX, A.getRowGroupIndices());
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} else {
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storm::utility::vector::reduceVectorMax(*multiplyResult, *newX, A.getRowGroupIndices());
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}
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// Determine whether the method converged.
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converged = storm::utility::vector::equalModuloPrecision(*currentX, *newX, this->precision, this->relative);
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// Update environment variables.
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std::swap(currentX, newX);
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++iterations;
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}
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// Check if the solver converged and issue a warning otherwise.
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if (converged) {
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LOG4CPLUS_INFO(logger, "Iterative solver converged after " << iterations << " iterations.");
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} else {
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LOG4CPLUS_WARN(logger, "Iterative solver did not converge after " << iterations << " iterations.");
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}
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// If we performed an odd number of iterations, we need to swap the x and currentX, because the newest result
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// is currently stored in currentX, but x is the output vector.
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if (currentX == copyX) {
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std::swap(x, *currentX);
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}
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if (!xMemoryProvided) {
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delete copyX;
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}
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if (!multiplyResultMemoryProvided) {
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delete multiplyResult;
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}
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}
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template<typename ValueType>
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void GmmxxNondeterministicLinearEquationSolver<ValueType>::performMatrixVectorMultiplication(bool minimize, storm::storage::SparseMatrix<ValueType> const& A, std::vector<ValueType>& x, std::vector<ValueType>* b, uint_fast64_t n, std::vector<ValueType>* multiplyResult) const {
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// Transform the transition probability matrix to the gmm++ format to use its arithmetic.
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std::unique_ptr<gmm::csr_matrix<ValueType>> gmmxxMatrix = storm::adapters::GmmxxAdapter::toGmmxxSparseMatrix<ValueType>(A);
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bool multiplyResultMemoryProvided = true;
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if (multiplyResult == nullptr) {
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multiplyResult = new std::vector<ValueType>(A.getRowCount());
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multiplyResultMemoryProvided = false;
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}
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// Now perform matrix-vector multiplication as long as we meet the bound of the formula.
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for (uint_fast64_t i = 0; i < n; ++i) {
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gmm::mult(*gmmxxMatrix, x, *multiplyResult);
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if (b != nullptr) {
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gmm::add(*b, *multiplyResult);
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}
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if (minimize) {
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storm::utility::vector::reduceVectorMin(*multiplyResult, x, A.getRowGroupIndices());
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} else {
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storm::utility::vector::reduceVectorMax(*multiplyResult, x, A.getRowGroupIndices());
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}
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}
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if (!multiplyResultMemoryProvided) {
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delete multiplyResult;
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}
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}
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// Explicitly instantiate the solver.
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template class GmmxxNondeterministicLinearEquationSolver<double>;
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} // namespace solver
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} // namespace storm
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