A novel high-throughput method for table look-up based analog design automation

Analog circuit synthesis ofen requires repeated evaluations of circuit under design to reach the final design goals. Circuit simulations using SPICE can provide accurate assessment of circuit performance. Spice simulations are costly and incur significant overhead. A faster transistor-level evaluation is needed to provide higher throughput for synthesis applications. Further, miniaturization of FET’s has added physical effects into SPICE models, which complicated their equations with every generation. That complication has forced analog synthesis tool developers and circuit designers alike to perform circuit evaluations using SPICE.Analog circuit design tools largely failed in their declared goal, to take over circuit optimization tasks from human designers mainly due to over simplications using custom-developed equations for evaluating circuit performance. Since it is more and more difficult to accurately capture transistor behavior with each new generation of silicon technology, a more practical approach to analog design automation is to keep human engineers at the center of the design flow by providing them with as much needed decision-supporting data as quickly as possible. Mapping the trade-off landscape of a topology with respect to design specifications, for example, can save designers trial and error time. This approach to analog design automation requires less accuracy from the simulation sign-off tools, such as SPICE. However, it demands much faster response for circuit performance evaluations with sufficient accuracy.In this paper, a new solution to both calculation overheads and model complexity is proposed. The proposed fast evaluation method uses a novel look-up table (LUT) algorithm to extract circuit information from complex physics-based transistor models used by SPICE. The model makes use of contemporary memory space, by replacing equations with look-up tables in addition to advanced interpolation methods. The achieved improvement is over 100× throughput and complete decoupling from physical phenomena compared to SPICE run-time, in exchange for few gigabytes of data per device. Examples are shown for the effectiveness of replacing SPICE with our model in a transistor sizing flow, while keeping 99% of the samples inside the 5% error range on 180 nm and 40 nm CMOS processes. The proposed solution is not intended to replace sign-off quality tools, such as SPICE. Rather, it is intended to be used as a fast performance evaluator in analog design automation flows.