Arc Model and DDG: Deadlock Avoidance and Detection in Torus NoC

Abstract

Wraparound channels in Torus Network-on-Chip (NoC) help in reducing overall hop counts traversed by traffic. However, the cyclic paths created by wraparound channel make Torus NoC deadlock prone. Turn model and Channel Dependency Graph (CDG) are two classical approaches used for detecting and avoiding deadlock in NoC. In this work, we propose an Arc model for avoiding deadlock in Torus NoC. Arc model is an extension to Turn model and is useful for deadlock avoidance in Torus. Directional Dependency Graph (DDG) is also presented in this work by combining both Turn model and CDG for detecting deadlock in Torus NoC. DDG is a simpler approach for identifying deadlock scenarios, formulating deadlock avoidance and showing deadlock freedom while using Arc model along with a set of Turns.