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.Comment: This is a technical report accompanying a TACAS'11 pape