Achieving Analog Layout Integrity through Learning and Migration Invited Talk

Mark Po Hung Lin, Hao Yu Chi, Abhishek Patyal, Zheng Yao Liu, Jun Jie Zhao, Chien-Nan Liu, Hung-Ming Chen

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations


Analog IC designers and design houses have been accumulating their own design knowledge and constructing their own analog design repositories, including various design specifications, applications, and process technologies. As most of the analog layouts are handcrafted art works, different designers/companies may have different layout guidelines and preferences. When generating a new layout for certain analog design which already exists or is similar to any of those in the repositories, but with different circuit parameters or process technology files, applying layout migration is usually more preferable than starting from scratch. This paper introduces a holistic framework and new layout generation methodology to achieve analog layout integrity through learning and migration. The introduced methodology can effectively and efficiently preserve the preferences of placement and routing topologies from legacy layouts to new ones.

Original languageEnglish
Article number9256451
JournalIEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD
StatePublished - 2 Nov 2020
Event39th IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2020 - Virtual, San Diego, United States
Duration: 2 Nov 20205 Nov 2020


  • Analog layout
  • analog placement
  • analog routing
  • building block
  • circuit classification
  • circuit identification
  • circuit structure analysis
  • layout pattern
  • layout template
  • machine learning
  • migration


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