Automatic Model Generation for Gate-Level Circuit PDES with Reverse Computation
提出一种自动生成门级电路仿真模型的方法，利用标准门库解析器生成比手工模型更精确的模型，并在OpenSPARC T2处理器仿真中验证了性能。
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, 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 that uses a standardized gate library to create a specific model for simulation. The generated model is composed of several functions, 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 -10 k 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. 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. To test the automatically generated model, we evaluate the performance of a simulation of a full-scale OpenSPARC T2 processor model. This model consists of nearly 6 million LPs. We achieve a peak performance of 1.63 million events per second during a conservative simulation. To understand the relatively weaker performance of optimistic simulation, we investigate hot spots of event activity and visually identify a workload imbalance.