Increasing within-die variation, combined with larger numbers of critical and near-critical paths and higher operating frequencies, has increased the sensitivity of chips to path delay faults. A component of within-die variation comes from optical lithography, including the optical proximity effect, lens aberrations, and flare. This paper presents a methodology to generate test sets to diagnose these sources of within-die variation. Specifically, a delay fault diagnosis algorithm is developed to link failing signatures to a set of physical mechanisms originating from lithography. The algorithm relies on layout-dependent timing analysis, path enumeration, test pattern generation, and correlation of pass/fail signatures to diagnose delay faults caused by lithography. The effectiveness of diagnosis is evaluated for ISCAS85 benchmark circuits.

As semiconductor technology advances into the nanoscale era and more functional blocks are added into systems-on-chip, the interface between circuit design and manufacturing is becoming blurred. An increasing number of features, traditionally ignored by designers, are influencing both circuit performance and yield. As a result, design tools need to incorporate new factors. One important source of circuit-performance degradation comes from deterministic within-die variation from lithography imperfections and Cu-interconnect chemical-mechanical polishing (CMP). To determine how these within-die variations impact circuit performance, we need a new analysis tool. Thus, we have proposed a methodology to involve layout-dependent within-die variations in static timing analysis. Our methodology combines a set of scripts and commercial tools to analyze a full chip. The tool has been applied to analyze delay of ISCAS85 benchmark circuits in the presence of imperfect lithography and CMP variation