Book Description
The continued scaling of digital integrated circuits has led to an increasingly larger impact of process, supply voltage, and temperature (PVT) variations. The effect of these variations on logic cell and interconnect delays has introduced challenges to both circuit performance (timing) verification and optimization. In order for us to fully take advantage of the benefits of technology scaling, it is essential that "variation-aware" techniques for performance verification and optimization be developed and used in modern design flows.In this thesis such techniques for both performance verification and optimization are presented. First, we present a fast method for finding the worst-case slacks over all process and environmental corners. This method uses the standard set of PVT corners available in industry, and provides large runtime gains while maintaining a high degree of accuracy. After that, we propose an efficient block-based parameterized timing analysis technique that can accurately capture circuit delays at every point in the parameter space, by reporting all paths that can become critical. This method employs parameterized static timing analysis (PSTA) variability models, and allows one to easily examine local robustness to parameters in different regions of the parameter space. Next, we introduce an optimization method that alters clock network lines so that a circuit meets its timing constraints at all PVT settings under PSTA variability models. This is formulated as a Linear Program (LP), which is based on a clock skew optimization formulation, and as a result it can be solved efficiently. Finally, we present a method that uses characterized, pre-silicon, PSTA variational timing models to identify speedpaths that can best explain the observed delay measurements during silicon debug. This is a crucial step, required for both "fixing"' failing paths and for accurate learning from silicon data.
