Graph-Based Algorithms for Boolean Function Manipulation
IEEE Transactions on Computers
Symbolic Boolean manipulation with ordered binary-decision diagrams
ACM Computing Surveys (CSUR)
Noncommittal barrier synchronization
Parallel Computing
Efficient descriptor-vector multiplications in stochastic automata networks
Journal of the ACM (JACM)
Automated parallelization of discrete state-space generation
Journal of Parallel and Distributed Computing - Special issue on dynamic load balancing
Model checking
Efficient encoding schemes for symbolic analysis of petri nets
Proceedings of the conference on Design, automation and test in Europe
Handbook of Process Algebra
Saturation: An Efficient Iteration Strategy for Symbolic State-Space Generation
TACAS 2001 Proceedings of the 7th International Conference on Tools and Algorithms for the Construction and Analysis of Systems
CAV '97 Proceedings of the 9th International Conference on Computer Aided Verification
Parallel State Space Exploration for GSPN Models
Proceedings of the 16th International Conference on Application and Theory of Petri Nets
Petri Net Analysis Using Boolean Manipulation
Proceedings of the 15th International Conference on Application and Theory of Petri Nets
Storage Alternatives for Large Structured State Spaces
Proceedings of the 9th International Conference on Computer Performance Evaluation: Modelling Techniques and Tools
Distributed State Space Generation of Discrete-State Stochastic Models
INFORMS Journal on Computing
INFORMS Journal on Computing
Numerical analysis of stochastic marked graph nets
PNPM '95 Proceedings of the Sixth International Workshop on Petri Nets and Performance Models
State Space Construction and Steady--State Solution of GSPNs on a Shared--Memory Multiprocessor
PNPM '97 Proceedings of the 6th International Workshop on Petri Nets and Performance Models
Analysis of large GSPN models: a distributed solution tool
PNPM '97 Proceedings of the 6th International Workshop on Petri Nets and Performance Models
A Data Structure for the Efficient Kronecker Solution of GSPNs
PNPM '99 Proceedings of the The 8th International Workshop on Petri Nets and Performance Models
PNPM '99 Proceedings of the The 8th International Workshop on Petri Nets and Performance Models
SMART: Simulation and Markovian Analyzer for Reliability and Timing
IPDS '96 Proceedings of the 2nd International Computer Performance and Dependability Symposium (IPDS '96)
ON THE USE OF KRONECKER OPERATORS FOR THE SOLUTION OF GENERALIZED STOCHASTIC PETRI NETS
ON THE USE OF KRONECKER OPERATORS FOR THE SOLUTION OF GENERALIZED STOCHASTIC PETRI NETS
Efficient symbolic state-space construction for asynchronous systems
ICATPN'00 Proceedings of the 21st international conference on Application and theory of petri nets
A Database Approach to Distributed State Space Generation
Electronic Notes in Theoretical Computer Science (ENTCS)
A distributed verification approach for modular Petri nets
Proceedings of the 2007 Summer Computer Simulation Conference
Efficient Probabilistic Model Checking on General Purpose Graphics Processors
Proceedings of the 16th International SPIN Workshop on Model Checking Software
Parallel explicit state reachability analysis and state space construction
ISPDC'03 Proceedings of the Second international conference on Parallel and distributed computing
Sequential and distributed on-the-fly computation of weak tau-confluence
Science of Computer Programming
Improving GPU sparse matrix-vector multiplication for probabilistic model checking
SPIN'12 Proceedings of the 19th international conference on Model Checking Software
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Both the logic and the stochastic analysis of discrete-state systems are hindered by the combinatorial growth of the state space underlying a high-level model. In this work, we consider two orthogonal approaches to cope with this "state-space explosion". Distributed algorithms that make use of the processors and memory overall available on a network of N workstations can manage models with state spaces approximately N times larger than what is possible on a single workstation. A second approach, constituting a fundamental paradigm shift, is instead based on decision diagrams and related implicit data structures that efficiently encode the state space or the transition rate matrix of a model, provided that it has some structure to guide its decomposition; with these implicit methods, enormous sets can be managed efficiently, but the numerical solution of the stochastic model, if desired, is still a bottleneck, as it requires vectors of the size of the state space.