A Markov reward model for reliable synchronous dataflow system design

The design of quality digital systems depends on models that accurately evaluate various options in the design space against a set of prioritized metrics. While individual models for evaluating area, performance, reliability, power, etc. are well established, models combining multiple metrics are less mature. This paper introduces a formal methodology for comprehensively analyzing performance, area and reliability in the design of synchronous dataflow systems using a novel Markov Reward Model. A Markov chain system reliability model is constructed for various design options in the presence of possible component failures, and high-level synthesis techniques are used to associate performance and area rewards with each state in the chain. The cumulative reward for a chain is then used to evaluate the corresponding design option with respect to the metrics of interest. Application of the model to a benchmark DSP circuit provides insights into reliable synchronous dataflow system design.