Performance models of multiprocessor systems
Performance models of multiprocessor systems
PVM: Parallel virtual machine: a users' guide and tutorial for networked parallel computing
PVM: Parallel virtual machine: a users' guide and tutorial for networked parallel computing
ACM Computing Surveys (CSUR)
SPNP: Stochastic Petri Net Package
PNPM '89 The Proceedings of the Third International Workshop on Petri Nets and Performance Models
Parallel Shared-Memory State-Space Exploration in Stochastic Modeling
IRREGULAR '97 Proceedings of the 4th International Symposium on Solving Irregularly Structured Problems in Parallel
Parallel State Space Exploration for GSPN Models
Proceedings of the 16th International Conference on Application and Theory of Petri Nets
SPNL: Processes as Language-Oriented Building Blocks of Stochastic Petri Nets
Proceedings of the 9th International Conference on Computer Performance Evaluation: Modelling Techniques and Tools
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
On the success of stochastic Petri nets
PNPM '95 Proceedings of the Sixth 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
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This paper presents parallel approaches to the complete transient numerical analysis of stochastic reward nets (SRNs) for both shared and distributed-memory machines. Parallelization concepts and implementation issues are discussed for the three main analysis steps that are (1) generation of the underlying continuous-time Markov chain (CTMC), (2) solving the CTMC numerically for the desired time points and (3) converting the results back to the net level by evaluating reward based result measure functions. The distributed-memory approach implements dynamic load balancing mechanisms in step (1) to guarantee an equal distribution of the state space onto the main memories of the clustered machines. The shared-memory algorithms are based on elaborated synchronization mechanisms which allow parallel read and write access to the global irregular data structure of the CTMC. Performance measurements on different architectures and a comparison of the approaches are given. All the algorithms are integrated in PANDA which consequently is a parallel SRN modeling tool suitable for different multiprocessor platforms.