Parameterized Macromodeling for Analog System-Level Design Exploration

In this paper we propose a novel parameterized macromodeling technique for analog circuits. Unlike traditional macromodels that are only extracted for a small variation space, our proposed approach captures a significantly larger analog design space to facilitate system-level design exploration. Combining a novel piece-wise approximation algorithm and a new multi-point modelorder-reduction approach, the proposed method generates compact macromodels covering the entire feasible design space. Our experiments demonstrate that using such models can achieve more than 60? speed-up while incurring less than 4% overall error when varying design parameters by an order of magnitude. Categories and Subject Descriptors: B.7.2 [Integrated Circuits]: Design Aids ? simulation General Terms: Algorithms, Design

• Type: Conference
• Year: 2007
• Where: DAC
• Authors: Jian Wang, Xin Li, Lawrence T. Pileggi
• Keywords: Analog Design Space, DAC 2007, Design Automation, Feasible Design Space, System-level Design Exploration