Perfect Simulation of Stochastic Automata Networks
ASMTA '08 Proceedings of the 15th international conference on Analytical and Stochastic Modeling Techniques and Applications
Modelling Grid5000 point availability with SAN
Electronic Notes in Theoretical Computer Science (ENTCS)
Collaboration of discrete-time Markov chains: Tensor and product form
Performance Evaluation
Simulation of Markovian models using bootstrap method
Proceedings of the 2010 Summer Computer Simulation Conference
Performance Evaluation of Software Development Teams: a Practical Case Study
Electronic Notes in Theoretical Computer Science (ENTCS)
Stationary solution approximation using a memory-efficient perfect sampling technique
Proceedings of the 44th Annual Simulation Symposium
Efficient vector-descriptor product exploiting time-memory trade-offs
ACM SIGMETRICS Performance Evaluation Review
Performance evaluation of business processes through a formal transformation to SAN
EPEW'11 Proceedings of the 8th European conference on Computer Performance Engineering
SAN lite-solver: a user-friendly software tool to solve SAN models
Proceedings of the 2012 Symposium on Theory of Modeling and Simulation - DEVS Integrative M&S Symposium
A Structured Stochastic Model for Prediction of Geological Stratal Stacking Patterns
Electronic Notes in Theoretical Computer Science (ENTCS)
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PEPS is a tool package for modeling and solving models expressed in Stochastic Automata Networks (SAN). The SAN formalism defines a compact storage scheme for the transition matrix of the Markov chain and it uses tensor algebra to handle the basic vector matrix multiplications. This paper presents a short timeline of PEPS previous versions and the new features included in version 2007.