ML/DL-Based Signal Integrity Optimization for InFO Routing

Bo Kai Kang, Hao Ju Chang, Hung Ming Chen, Chien Nan Jimmy Liu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Signal integrity (SI) has been a critical concern in IC/package routing due to the importance in timing and function. However, very few researches discuss related issues in advanced packaging solutions such as InFO (Integrated Fan-Out) structure. This work proposes a new InFO routing flow that improves SI and makes the InFO router SI-aware by integrating well-trained ML/DL models. First, we adopt multiple shielding structures to reduce the impact of crosstalk and obtain eye diagrams to verify the SI improvement. Next, we utilize eye diagram simulation results obtained from the previous step to train the models. Lastly, we integrate the ML/DL models into the InFO router. To evaluate the SI improvement, we apply our new InFO routing flow on several HBM3 testcases, and observe SI improvement in worst eye height ranging from 7.69% to 11.27% and in average eye height ranging from 8.52% to 9.54%.

Original languageEnglish
Title of host publication2024 22nd IEEE Interregional NEWCAS Conference, NEWCAS 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages343-347
Number of pages5
ISBN (Electronic)9798350361759
DOIs
StatePublished - 2024
Event22nd IEEE Interregional NEWCAS Conference, NEWCAS 2024 - Sherbrooke, Canada
Duration: 16 Jun 202419 Jun 2024

Publication series

Name2024 22nd IEEE Interregional NEWCAS Conference, NEWCAS 2024

Conference

Conference22nd IEEE Interregional NEWCAS Conference, NEWCAS 2024
Country/TerritoryCanada
CitySherbrooke
Period16/06/2419/06/24

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