An advanced cell polynomial-base modeling for logic synthesis

Abstract

This paper presents an advance cell modeling technique based on the polynomial expressions for physical and logic design. Till now, there lacks a modeling method to handle multiple operating points such as input slew, output capacitance, voltage, process, temperature, etc. at one time for the logic synthesis and physical design. Our novel curve-fitting algorithm for cell modeling can process a table with thousands of data points in only one modeling equation compared to piecewise equations used in the existing methods. The data storage requirements and CPU run time are significantly reduced without compromising the accuracy of the data. This ensures that the novel curve-fitting algorithm can exactly recover the original data points in a short period of time. In addition, the table-partitioning algorithm is developed to reduce the storage requirements and flatten the peak situation occurring at some of the unsampled data. Furthermore, in order to filter the 'pass' points with 99% of all data points, the algorithm is developed to select the best order for input variables, which further causes a shortening of the CPU run time. Our benchmark shows that the new approach has significantly better accuracy and less storage for both the sampling data and unsampling data.