no code implementations • 28 Oct 2022 • Haiguang Liao, Vinay Patil, Xuliang Dong, Devika Shanbhag, Elias Fallon, Taylor Hogan, Mirko Spasojevic, Levent Burak Kara
Our automatic power plane generation approach is based on genetic optimization combined with a multilayer perceptron and is able to automatically generate power planes across a diverse set of problems with varying levels of difficulty.
no code implementations • 15 Nov 2020 • Dhruv Vashisht, Harshit Rampal, Haiguang Liao, Yang Lu, Devika Shanbhag, Elias Fallon, Levent Burak Kara
Physical design and production of Integrated Circuits (IC) is becoming increasingly more challenging as the sophistication in IC technology is steadily increasing.
no code implementations • 26 Oct 2020 • Haiguang Liao, Qingyi Dong, Weiyi Qi, Elias Fallon, Levent Burak Kara
The key advantage of this approach is that the router can learn a policy in an offline setting with supervision, while improving the run-time performance nearly 100x over the genetic solver.
no code implementations • 20 Apr 2020 • Haiguang Liao, Qingyi Dong, Xuliang Dong, Wentai Zhang, Wangyang Zhang, Weiyi Qi, Elias Fallon, Levent Burak Kara
We also discover a similarity between the attention router and the baseline genetic router in terms of positive correlations in cost and routing patterns, which demonstrate the attention router's ability to be utilized not only as a detailed router but also as a predictor for routability and congestion.
1 code implementation • 20 Jun 2019 • Haiguang Liao, Wentai Zhang, Xuliang Dong, Barnabas Poczos, Kenji Shimada, Levent Burak Kara
At the heart of the proposed method is deep reinforcement learning that enables an agent to produce an optimal policy for routing based on the variety of problems it is presented with leveraging the conjoint optimization mechanism of deep reinforcement learning.