Analysis of computation-communication issues in dynamic dataflow architectures.

Analytical results are presented for computation-communication issues in dynamic data architectures. The study is based on a generalized architecture that encompasses all the features of the proposed dynamic dataflow architectures. Based on the idea of characterizing dataflow graphs by their average parallelism, a queueing network model of the architecture is developed. Since the queing network violates the properties required for product-form solution, a few approximations have been used. These approximations yield a multichain closed queueing network in which the population of each chain is related to the average parallelism of the dataflow graph executed in the architecture. Based on the model, it is possible to study the effect on the performance of the system due to factors such as scalability, coarse-grain vs. fine-grain parallelism, degree of decentralized scheduling of dataflow instructions, and locality.