A Novel Criticality Computation Method in Statistical Timing Analysis

The impact of process variations increases as technology scales to nanometer region. Under large process variations, the path and arc/node criticality [18] provide effective metrics in guiding circuit optimization. To facilitate the criticality computation considering the correlation, we define the critical region for the path and arc/node in a timing graph, and propose an efficient method to compute the criticality for paths and arcs/nodes simultaneously by a single breadth-first graph traversal during the backward propagation. Instead of choosing a set of paths for analysis prematurely, we develop a new property of the path criticality to prune those paths with low criticality at very earlier stages, so that our path criticality computation method has linear complexity with respect of the timing edges in a timing graph. To improve the computation accuracy, cutset and path criticality properties are exploited to calibrate the computation results. The experimental results on ISCAS benchmark circuits show that our criticality computation method can achieve high accuracy with fast speed.