Analysis of computation-communication issues in dynamic dataflow architectures

This paper presents analytical results of computation-communication issues in dynamic dataflow architectures. The study is based on a generalized architecture which 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 queueing network violates properties required for product from solution, a few approximations have been used. These approximations yield a multi-chain 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, we are able 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.