Publications

Book chapters

  1. V. A. Chhabria and S. S. Sapatnekar, “Deep Learning for Analyzing Power Delivery Networks and Thermal Networks,” in Machine Learning Applications in Electronic Design Automation, J. Hu and H. Ren, eds., Springer, New York, NY, 2023.

Journals

  1. [TCAD’25] Z. Wang, P. S. Nalla, J. Sun, A. A. Goksoy, S. K. Mandal, J.-S. Seo, V. A. Chhabria, J.Zhang, C. Chakrabarti, U. Y. Ogras, and Y. Cao, “HISIM: Analytical Performance Modeling and Design Space Exploration of 2.5D/3D Integration for AI Computing,” in the IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 2025.
  2. [TODAES’23] V. A. Chhabria, W. Jiang, A. B. Kahng, and S. S. Sapatnekar, “A Machine Learning Approach to Improving Timing Consistency between Global Route and Detailed Route,” in the ACM Transactions on Design Automation of Electronic Systems (TODAES), 2023.
  3. [TODAES’22] V. A. Chhabria, V. Ahuja, A. Prabhu, N. Patil, P. Jain, and S. S. Sapatnekar, “Encoder-Decoder Networks for Analyzing Thermal and Power Delivery Networks,” in the ACM Transactions on Design Automation of Electronic Systems (TODAES), 2022.
  4. [TCAD’21] V. A. Chhabria and S. S. Sapatnekar, “OpeNPDN: A Neural-network-based Framework for Power Delivery Network Synthesis,“ in the IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 2021.

Conferences

  1. [IGSC’24] C. C. Sudarshan, Aman Arora, and V. A. Chhabria, “Beyond the Surface: The Necessity for Detailed Metrics in Corporate Sustainability Reports,” Proceedings of International Green and Sustainable Computing Conference (IGSC), 2024.
  2. [ICCAD’24] N. Karmokar, S.-W. Tam, T. V. Dinh, V. A. Chhabria, R. Harjani, and S. S. Sapatnekar, “Analyzing the Impact of FinFET Self-Heating on the Performance of RF Power Amplifiers,” Proceedings of IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2024
  3. [ICCAD’24] V. A. Chhabria, B.-Y. Wu, U. Sharma, K.Kunal, A. Rovinsk, and S. S. Sapatnekar, “Generative Methods in EDA: Innovations in Dataset Generation and EDA Tool Assistants,” Proceedings of IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2024. (Invited paper)
  4. [ICCAD’24] V. A. Chhabria, V. Gopalakrishnan, A. B. Kahng, S. Kundu, Z. Wang, B.-Y. Wu, D. Yoon, “Strengthening the Foundations of IC Physical Design and ML EDA Research,” Proceedings of IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2024. (Invited paper)
  5. [ICCAD’24] B.-Y. Wu, R. Liang, G. Pradipta, A. Agnesina, H. Ren, V. A. Chhabria, “2024 ICCAD CAD Contest Problem C: Scalable Logic Gate Sizing using ML Techniques and GPU Acceleration,” Proceedings of IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2024. (Invited paper)
  6. [MLCAD’24] W. Jiang, V. A. Chhabria, and S. S. Sapatnekar, “IR-Aware ECO Timing Optimization Using Reinforcement Learning,” ACM/IEEE International Symposium on Machine Learning for CAD (MLCAD), 2024. (Best paper nominated).
  7. [MLCAD’24] U. Sharma, B.-Y. Wu, S. R. D. Kankipati, V. A. Chhabria, and A. Rovinski, “OpenROAD-Assistant: An Open-Source Large Language Model for Physical Design Tasks,” ACM/IEEE International Symposium on Machine Learning for CAD (MLCAD), 2024.
  8. [ISLPED’24] V. Gopalakrishnan, B.-Y. Wu, and V. A. Chhabria, “ML-INSIGHT: Machine Learning for Inrush Current Prediction and Power Switch Network Improvement,” Proceedings of ACM/IEEE International Symposium on Low Power Electronics and Design (ISPLED), 2024.
  9. [LAD’24] B.-Y. Wu, U. Sharma, S. R. D. Kankipati, A. Yadav, B. K. George, S. R. Guntupalli, A. Rovinski, and V. A. Chhabria, “EDA-Corpus: A Large Language Model Dataset for Enhanced Interaction with OpenROAD,” Proceeding of IEEE International Workshop on LLM-Aided Design (LAD), 2024. (Best paper nominated).
  10. [VTS’24] V. A. Chhabria, W. Jiang, A. B. Kahng, R. Liang, H. Ren, S. S. Sapatnekar, and B.-Y. Wu, “OpenROAD and CircuitOps: Infrastructure for ML EDA Research and Education,” Proceedings of the IEEE VLSI Test Symposium (VTS), 2024.
  11. [DAC’24] C. C. Sudarshan, Aman Arora, and  V. A. Chhabria, “GreenFPGA: Evaluating FPGAs as Environmentally Sustainable Computing Solutions, “Proceedings of ACM/IEEE Design Automation Conference (DAC), 2024.
  12. [HPCA’24] C. C. Sudarshan, N. Matkar, S. Vrudhula, S. S. Sapatnekar, and V. A. Chhabria “ECO-CHIP: Estimation of Carbon Footprint of Chiplet-based Architectures for Sustainable VLSI,” Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 2024.
  13. [ASP-DAC’24] Z. Wang, J. Sun, A. Goksoy, S. K. Mandal, Y. Liu, JS Seo, C. Chakrabarti, U. Y. Ogras, V. A. Chhabria, J. Zhang, and Y. Cao “Exploiting 2.5 D/3D Heterogeneous Integration for AI Computing,” Proceedings of the IEEE Asia and South Pacific Design Automation Conference (ASP-DAC), 2024.
  14. [ASICON’23] Z. Wang, J. Sun, A. Goksoy, S.K. Mandal, JS Seo, C. Chakrabarti, U. Y. Ogras, V. A. Chhabria, and Y. Cao. “Benchmarking Heterogeneous Integration with 2.5 D/3D Interconnect Modeling, ” Proceedings of the International Conference on ASIC (ASICON), 2023.
  15. [ISPD’23] N. Evmorfopoulos, M. A. A. Shohel, Olympia Axelou, Pavlos Stoikos, V. A. Chhabria, and S. S. Sapatnekar, “Recent Progress in the Analysis of Electromigration and Stress Migration in Large Multisegment Interconnects,” Proceedings of the International Symposium on Physical Design (ISPD), 2023.
  16. [ICCAD’23] G. S. P. Kadagala, and V. A. Chhabria, “ICCAD CAD Contest Problem C: Static IR Drop Estimation Using Machine Learning,” Proceedings of IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2023.
  17. [ICCAD’23] M. A. A. Shohel, V. A. Chhabria, Nestor Evmorfopoulos, and S. S. Sapatnekar, “Frequency-Domain Transient Electromigration Analysis Using Circuit Theory,” Proceedings of IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2023.
  18. [ICCAD’23] Rongjian Liang, Anthony Agnesina, G. Pradipta, V. A. Chhabria, and H. Ren, “CircuitOps: An ML Infrastructure Enabling Generative AI for VLSI Circuit Optimization,” Proceedings of IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2023.
  19. [ISQED’23] V. A. Chhabria and S. Sapatnekar, “Analysis of Pattern-dependent Rapid Thermal Annealing Effects on SRAM Design,” Proceedings of IEEE International Symposium on Quality Electronic Design (ISQED), 2023.
  20. [MLCAD’22] V. A. Chhabria, W. Jiang, A. B. Kahng, and S. Sapatnekar, “From Global Route to Detailed Route: ML for Fast and Accurate Wire Parasitics and Timing Prediction,” Proceedings of ACM/IEEE Workshop on Machine Learning for CAD (MLCAD), 2022.
  21. [MLCAD’22] V. A. Chhabria, B. Keller, Y. Zhang, S. Vollola, S. Pratty, H. Ren, and B. Khailany, “XT-PRAGGMA: Crosstalk Pessimism Reduction Achieved with GPU Gate-level Simulations and Machine Learning,” Proceedings of ACM/IEEE Workshop on Machine Learning for CAD (MLCAD), 2022.
  22. [ICCAD’21] V. A. Chhabria, K.Kunal, M. Zabihi, and S. S. Sapatnekar, “BeGAN: Power Grid Benchmark Generation Using a Process-portable GAN-based Methodology,” Proceedings of IEEE/ACM International Conference On Computer Aided Design (ICCAD), 2021.
  23. [ICCAD’21] M. A. A. Shohel, V. A. Chhabria, Nestor Evmorfopoulos, and S. S. Sapatnekar, “Analytical Modeling of Transient Electromigration Stress based on Boundary Reflections,” Proceedings of IEEE/ACM International Conference On Computer Aided Design (ICCAD), 2021 (Best Paper Award).
  24. [DAC’21] M. A. A. Shohel, V. A. Chhabria, and S. S. Sapatnekar, “A New, Computationally Efficient “Blech Criterion” for Immortality in General Interconnects,” Proceedings of ACM/IEEE Design Automation Conference (DAC), 2021.
  25. [DATE’21] V. A. Chhabria, Y. Zhang, H. Ren, B. Keller, B. Khailany, and S. S. Sapatnekar, “MAVIREC: ML-Aided Vectored IR-Drop Estimation and Classification,” Proceedings of Design, Automation, and Test in Europe (DATE), 2021.
  26. [ASP-DAC’21] V. A. Chhabria, V. Ahuja, A. Prabhu, N. Patil, P. Jain, and S. S. Sapatnekar, “Thermal and IR Drop Analysis Using Convolutional Encoder-Decoder Networks,” Proceedings of Asia and South Pacific Design Automation Conference (ASP-DAC), 2021.
  27. [ASP-DAC’20] V. A. Chhabria, A. B Kahng, M. Kim, U. Mallappa, S. S. Sapatnekar, and B. Xu, “Template-based PDN Synthesis in Floorplan and Placement Using Classifier and CNN Techniques,” Proceedings of Asia and South Pacific Design Automation Conference (ASP-DAC), 2020.
  28. [ISQED’19] V. A. Chhabria and S. S. Sapatnekar, “Impact of Self-heating on Performance and Reliability in FinFET and GAAFET Designs,” Proceedings of IEEE International Symposium on Quality Electronic Design (ISQED), 2019.
  29. [DAC’19] T. Ajayi, V. A. Chhabria, M. Fogac¸a, S. Hashemi, A. Hosny, A. B. Kahng, M. Kim, J. Lee, U. Mallappa, M. Neseem, G. Pradipta, S. Reda, M. Saligane, S. S. Sapatnekar, C. Sechen, M. Shalan,W. Swartz, L.Wang, Z.Wang, M. Woo, and B. Xu, “INVITED: Toward an Open-Source Digital Flow: First Learnings from the OpenROAD Project,” Proceedings of ACM/IEEE Design Automation Conference (DAC), 2019.
  30. [GOMACTECH’19] T. Ajayi, D. Blaauw, T.-B. Chan, C.-K. Cheng, V. A. Chhabria, D. K. Choo, M. Coltella, S. Dobre, R. Dreslinski, M. Fogac¸a, S. Hashemi, A. Hosny, A. B. Kahng, M. Kim, J. Li, Z. Liang, U. Mallappa, P. Penzes, G. Pradipta, S. Reda, A. Rovinski, K. Samadi, S. S. Sapatnekar, L. Saul, C. Sechen, V. Srinivas, W. Swartz, D. Sylvester, D. Urquhart, L. Wang, M. Woo, and B. Xu, “OpenROAD: Toward a Self-Driving, Open-Source Digital Layout Implementation Tool Chain”, Proceedings of Government Microcircuit Applications and Critical Technology Conference (GOMACTECH), 2019.

Archived

  1. M. A. A. Shohel, V. A. Chhabria, and S. S. Sapatnekar, “A Linear-Time Algorithm for Steady-State Analysis of Electromigration in General Interconnects,” arXiv:2112.13451 [cs.AR], 2022.
  2. V. A. Chhabria, Y. Zhang, H. Ren, B. Keller, B. Khailany and S. S. Sapatnekar, “MAVIREC: ML-Aided Vectored IR-Drop Estimation and Classification,” arXiv:2012.10597 [cs.AR], 2021.

Patents

  1. V. A. Chhabria, B. A. Keller, Y. Zhang, B. Khailany, and H. Ren, ”Reducing Crosstalk Pessimism using GPU-accelerated Gate Simulation and Machine Learning,” US Patent App. 17/540,167, 2023.
  2. V. A. Chhabria, Y. Zhang, H. Ren, and B. Khailany, ”Determining IR Drop using ML,” U.S. Patent App. 17/211,695, 2022.