(by S. Tongsima, T. O'Neil, and E. H.-M. Sha) in Proceedings of the 1999 IEEE International Conference On Acoustics, Speech, and Signal Processing, Phoenix, Arizona, March 1999, Vol 4, pp.1889-1892.
It is known that in many applications, because of selection statements, e.g., ifstatement, the computation time of a node can be represented by a random variable. This paper focuses on any iterative application (containing loops) reflecting those uncertainties. Such an application can then be transformed to a probabilistic dataflow graph. A challenging problem is to derive graph transformation techniques which can produce a good schedule. This paper introduces two timing models, the timeinvariant and time variant models, to characterize the nature of these applications. Furthermore, for the timeinvariant model, we propose a means of selecting a minimum rate-optimal unfolding factor which guarantees the best schedule length. We also propose a good estimation for choosing an unfolding factor for a graph under the timevariant model.
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