Improving Accuracy and Performance Through Automatic Model Generation for Gate-Level Circuit PDES with Reverse Computation

Abstract

Gate-level circuit simulation is an important step in the design and validation of complex circuits. This step of the process relies on existing libraries for gate specifications. We start with a generic gate model for Rensselaer's Optimistic Simulation System (ROSS), a parallel discrete-event simulation framework. This generic model encompasses all functionality needed by optimistic simulation using reverse computation. We then describe a parser system which uses a standardized gate library to create a specific model for simulation. The generated model is comprised of several function including those needed for an accurate model of timing behavior. To quantify the improvements that an automatically generated model can have over a hand written model we compare two gate library models: an automatically generated LSI-10K library model and a previously investigated, handwritten, simplified GTECH library model. We conclude that the automatically generated model is a more accurate model of actual hardware. The generated model also represents the timing behavior with an approximately 50 times higher degree of fidelity. In comparison to previous results, we find that the automatically generated model is able to achieve better optimistic simulation performance when measured against conservative simulation. We identify peak optimistic performance when using 128 MPI-Ranks on eight nodes of an IBM Blue Gene/Q machine.