Late Breaking Results: Warpage-Aware Generative Floorplanning for Reliable Advanced Packaging
This paper presents the first warpage-aware generative learningbased floorplanning algorithm to effectively model the warpage effect and optimize the die floorplan on a fixed outlined substrate. With more heterogeneous materials and dense interconnects in advanced packaging, warpage is a main reliability concern and may degrade system performance. We present a novel transformer-based encoding scheme to learn node and edge representations, followed by parallel decoding and warpage-aware legalization to jointly minimize die displacement and warpage. Experimental results show that our algorithm improves warpage by 9.9% and wirelength by 8.3% on average, compared with the state-of-the-art work.
Authors
- Cheng-Yen Li
- Yao‐Wen Chang (ORCID: https://orcid.org/0000-0002-0564-5719)
- Min-Hung Chen
- Tung-Chieh Chen (ORCID: https://orcid.org/0009-0000-3163-3634)
- Chenghao Su
Institutions
- Synopsys (Switzerland) (CH)
- National Taiwan University of Science and Technology (TW)
- National Taiwan University (TW)
Publication Details
- Published
- 2025-06-22
- DOI
- https://doi.org/10.1109/dac63849.2025.11132923
- Citations
- 1
- Primary Topic
- Manufacturing Process and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 1.24