LibAbs: An Efficient and Accurate Timing Macro-Modeling Algorithm for Large Hierarchical Designs

Tin-Yin Lai, Tsung-Wei Huang, Martin D. F. Wong

Research output: Chapter in book/report/conference proceedingChapterpeer-review

11 Citations (Scopus)


The ever-increasing design complexity is driving the need of fast and accurate macro-modeling algorithms to accelerate the hierarchical timing. We introduce LibAbs, an effective macro-modeling algorithm that efficiently supports high accuracy, high compression rate, and multi-threading. LibAbs applies tree-based graph reduction techniques to reduce the model size with comparable accuracy values to the flat model under multi-threaded environment. LibAbs outperforms existing tools including top winners from TAU 2016 macro-modeling contest in terms of model size, accuracy, and runtime on industry benchmarks. The in-context usage of our abstracted model has also demonstrated promising performance for timing-driven optimizations in large hierarchical designs.
Original languageEnglish
Title of host publication54th ACM/IEEE Design Automation Conference - Proceedings
PublisherAssociation for Computing Machinery (ACM)
Number of pages6
ISBN (Electronic)9781450349277
Publication statusPublished - Jun 2017
Event54th ACM/IEEE Design Automation Conference, DAC 2017 - Austin, United States
Duration: 18 Jun 201722 Jun 2017 (Conference proceedings) (Conference proceedings)

Publication series

NameACM/IEEE Design Automation Conference - Proceedings
ISSN (Print)0738-100X


Conference54th ACM/IEEE Design Automation Conference, DAC 2017
Country/TerritoryUnited States
Internet address

User-Defined Keywords

  • Timing macro-modeling
  • Static timing analysis


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