{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T16:34:59Z","timestamp":1773246899167,"version":"3.50.1"},"reference-count":29,"publisher":"Association for Computing Machinery (ACM)","issue":"3","funder":[{"name":"Major Key Project of PCL","award":["PCL2023A03"],"award-info":[{"award-number":["PCL2023A03"]}]},{"DOI":"10.13039\/501100003392","name":"Natural Science Foundation of Fujian Province","doi-asserted-by":"crossref","award":["2024J09045"],"award-info":[{"award-number":["2024J09045"]}],"id":[{"id":"10.13039\/501100003392","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Des. Autom. Electron. Syst."],"published-print":{"date-parts":[[2026,5,31]]},"abstract":"<jats:p>Routing is a critical stage in achieving timing closure in integrated circuit design. Due to the time-consuming flow of detailed routing (DR), the lack of accurate routing information, and the impact of congestion during global routing (GR), rapidly obtaining precise timing information at the global routing stage to guide subsequent timing optimization is a significant challenge. These challenges lead to substantial discrepancies between the estimated timing at GR stage and the actual results after post-DR, resulting in inaccurate evaluations of chip performance. To address this issue, we propose an effective timing prediction and optimization framework, AiTPO. The innovative KAN-UNet heterogeneous timing prediction model effectively combines UNet and KAN networks. By fusing spatial features extracted by UNet with numerical data, the model gains the capability to learn complex relationships across multi-modal data, thereby enhancing robustness and accuracy. Additionally, with the accurate timing evaluation, we introduce two timing optimization strategies during global routing to enhance timing performance. The first strategy involves net ordering based on predicted significant delay nets, prioritizing the routing of more timing-critical nets to reduce detours caused by congestion. The second strategy employs timing estimation to select the most optimal topology from multiple candidates generated by the enhanced A* algorithm, where congestion is considered as a cost factor. Which contributes to optimizing Worst Negative Slack (WNS) and Total Negative Slack (TNS). Experimental results on the real circuits under 28nm process node show that the wire delay prediction accuracy with the proposed KAN-UNet model improves by 34.6% and 25.4% in terms of Mean Absolute Error (MAE) and Max Absolute Error (MaxAE), respectively, compared to GR-based estimations and demonstrate the effectiveness of our timing optimization strategies, which lead to a 2.0% and 4.2% improvement in TNS and WNS, respectively.<\/jats:p>","DOI":"10.1145\/3735639","type":"journal-article","created":{"date-parts":[[2025,5,13]],"date-time":"2025-05-13T07:02:51Z","timestamp":1747119771000},"page":"1-28","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["AiTPO: KAN-UNet Heterogeneous Network for Timing Prediction and Optimization at Global Routing"],"prefix":"10.1145","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-4829-7737","authenticated-orcid":false,"given":"He","family":"Liu","sequence":"first","affiliation":[{"name":"School of Electronic and Computer Engineering, Peking University","place":["Shenzhen, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-3686-4576","authenticated-orcid":false,"given":"Zhisheng","family":"Zeng","sequence":"additional","affiliation":[{"name":"Peng Cheng Laboratory","place":["Shenzhen, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-4496-4317","authenticated-orcid":false,"given":"Simin","family":"Tao","sequence":"additional","affiliation":[{"name":"Peng Cheng Laboratory","place":["Shenzhen, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-1762-479X","authenticated-orcid":false,"given":"Zhipeng","family":"Huang","sequence":"additional","affiliation":[{"name":"Peng Cheng Laboratory","place":["Shenzhen, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0804-7236","authenticated-orcid":false,"given":"Yifan","family":"Li","sequence":"additional","affiliation":[{"name":"Peng Cheng Laboratory","place":["Shenzhen, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4045-6806","authenticated-orcid":false,"given":"Biwei","family":"Xie","sequence":"additional","affiliation":[{"name":"Institute of Computing Technology Chinese Academy of Sciences","place":["Beijing, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7429-5495","authenticated-orcid":false,"given":"Wei","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Electronic and Computer Engineering, Peking University","place":["Shenzhen, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7145-9391","authenticated-orcid":false,"given":"Xingquan","family":"Li","sequence":"additional","affiliation":[{"name":"Peng Cheng Laboratory","place":["Shenzhen, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2026,2,11]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/DAC18072.2020.9218712"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1145\/3698364.3709131"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1145\/3551901.3556475"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1145\/3626959"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2007.907068"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1109\/TVLSI.2010.2102780"},{"key":"e_1_3_2_8_2","first-page":"315","volume-title":"Proceedings of the 14th International Conference on Artificial Intelligence and Statistics","author":"Glorot Xavier","year":"2011","unstructured":"Xavier Glorot, Antoine Bordes, and Yoshua Bengio. 2011. 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