Stochastic Automata Network for Performance Evaluation of Heterogeneous SoC Communication

To meet ever increasing demand for performance of emerging System-on-Chip (SoC) applications, designer employ techniques for concurrent communication between components. Hence communication architecture becomes complex and major performance bottleneck. An early performance evaluation of communication architecture is the key to reduce design time, time-to-market and consequently cost of the system. Moreover, it helps to optimize system performance by selecting appropriate communication architecture. However, performance model of concurrent communication is complex to describe and hard to solve. In this paper, we propose methodology for performance evaluation of bus based communication architectures, modeling for which is based on modular Stochastic Automata Network (SAN). We employ Generalized Semi Markov Process (GSMP) model for each module of the SAN that emulates dynamic behavior of a Processing Element (PE) of an SoC architecture. The proposed modeling approach provides an early estimation of performance parameters viz. memory bandwidth, average queue length at memory and average waiting time seen by a processing element; while we provide parameters viz. number of processing elements, the mean computation time of processing elements and the first and second moments of connection time between processing elements and memories, as input to the model.