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2020 – today
- 2024
[c5]Andrew B. Kahng, Seokhyeong Kang, Sayak Kundu, Kyungjun Min, Seonghyeon Park, Bodhisatta Pramanik:
PPA-Relevant Clustering-Driven Placement for Large-Scale VLSI Designs. DAC 2024: 330:1-330:6- [c4]Andrew B. Kahng
, Sayak Kundu, Shreyas Thumathy:
Scalable Flip-Flop Clustering Using Divide and Conquer For Capacitated K-Means. ACM Great Lakes Symposium on VLSI 2024: 177-184 - 2023
- [c3]Jinwook Jung, Andrew B. Kahng, Sayak Kundu, Zhiang Wang, Dooseok Yoon:
Invited Paper: IEEE CEDA DATC Emerging Foundations in IC Physical Design and MLCAD Research. ICCAD 2023: 1-7 - [c2]Chung-Kuan Cheng, Andrew B. Kahng, Sayak Kundu, Yucheng Wang, Zhiang Wang:
Assessment of Reinforcement Learning for Macro Placement. ISPD 2023: 158-166 - [i2]Chung-Kuan Cheng, Andrew B. Kahng, Sayak Kundu, Yucheng Wang, Zhiang Wang:
Assessment of Reinforcement Learning for Macro Placement. CoRR abs/2302.11014 (2023) - [i1]Hadi Esmaeilzadeh, Soroush Ghodrati, Andrew B. Kahng, Joon Kyung Kim, Sean Kinzer, Sayak Kundu, Rohan Mahapatra, Susmita Dey Manasi, Sachin S. Sapatnekar, Zhiang Wang, Ziqing Zeng:
An Open-Source ML-Based Full-Stack Optimization Framework for Machine Learning Accelerators. CoRR abs/2308.12120 (2023) - 2022
- [c1]Hadi Esmaeilzadeh, Soroush Ghodrati, Andrew B. Kahng, Joon Kyung Kim, Sean Kinzer, Sayak Kundu, Rohan Mahapatra, Susmita Dey Manasi, Sachin S. Sapatnekar, Zhiang Wang, Ziqing Zeng:
Physically Accurate Learning-based Performance Prediction of Hardware-accelerated ML Algorithms. MLCAD 2022: 119-126
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