Abstract
We initiate the study of probabilistic parallel programs with dynamic process creation and synchronisation. To this end, we introduce probabilistic split-join systems (pSJSs), a model for parallel programs, generalising both probabilistic pushdown systems (a model for sequential probabilistic procedural programs which is equivalent to recursive Markov chains) and stochastic branching processes (a classical mathematical model with applications in various areas such as biology, physics, and language processing). Our pSJS model allows for a possibly recursive spawning of parallel processes; the spawned processes can synchronise and return values. We study the basic performance measures of pSJSs, especially the distribution and expectation of space, work and time. Our results extend and improve previously known results on the subsumed models. We also show how to do performance analysis in practice, and present two case studies illustrating the modelling power of pSJSs.
The first author is supported by a postdoctoral fellowship of the German Academic Exchange Service (DAAD). The second author is supported by EPSRC grant EP/G050112/1.
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Kiefer, S., Wojtczak, D. (2011). On Probabilistic Parallel Programs with Process Creation and Synchronisation. In: Abdulla, P.A., Leino, K.R.M. (eds) Tools and Algorithms for the Construction and Analysis of Systems. TACAS 2011. Lecture Notes in Computer Science, vol 6605. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19835-9_28
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