Efficient Circuit Structure Analysis for Automatic Behavioral Model Generation in Mixed-Signal System Simulation
| Autor: | Meng Jung Lee, Chien Nan Liu, Jing-Yang Jou, Yu Lan Lo, Yu Kang Lou, Ling Yen Song, Juinn Dar Huang, Ching Ho Lin |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
TK7800-8360
Computer Networks and Communications Computer science mixed-signal simulation 02 engineering and technology law.invention behavioral model law Encoding (memory) 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering Digital electronics business.industry 020208 electrical & electronic engineering Mixed-signal integrated circuit Partition (database) 020202 computer hardware & architecture Behavioral modeling Capacitor Computer engineering Hardware and Architecture Control and Systems Engineering Signal Processing Netlist Resistor Electronics business model generator |
| Zdroj: | Electronics, Vol 10, Iss 1088, p 1088 (2021) Electronics Volume 10 Issue 9 |
| ISSN: | 2079-9292 |
| Popis: | For mixed-signal systems, identifying the analog and digital circuit blocks in the transistor-level netlist has many benefits for system analysis and verification. However, existing approaches still have difficulty handling large mixed-signal designs with millions of transistors, especially when multiple analog structure patterns are included. In this paper, we propose an efficient structure recognition methodology to support analyzing highly complex designs with various circuit structures and different devices. In order to tackle the complexity of real cases, a hierarchical partition-based analysis methodology and an encoding-based fast screening technique are proposed in this work. To correctly ascertain the boundary of analog and digital structures, we propose an enhanced direct current connection (DCC) partition method and combine it with the analog structure analysis flow. The non-transistor devices, such as resistors and capacitors, are also included in our recognition flow to improve the recognition capability and accuracy. As demonstrated with two industrial cases, the behavioral models generated from the structure recognition results do help to improve the efficiency of the AMS system verification. |
| Databáze: | OpenAIRE |
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