We present a tool called Grouped PEPA Analyser (GPA) that allows fast analysis of large scale models described in the stochastic process algebra PEPA. GPA employs the techniques for approximations of transient moments in PEPA models with ordinary differential equations (ODEs), which allow analysis of systems with state spaces far beyond the limits of standard techniques. These moments provide useful information about the evolution of the model over time. Additionally, GPA implements a recently developed extension for moments of accumulated rewards, giving access to measures representing important factors in performance modeling such as energy consumption. GPA is also able to use these moments to calculate bounds on various passage time probabilities as well as completion times of the accumulated rewards. We describe the features of GPA in detail and briefly mention some design issues. We also present a technique that GPA implements for analysing more complex PEPA models with a higher degree of accuracy.
Information from pubs.doc.ic.ac.uk/gpa-massive-pepa-analysis.