activity
20212024
most citedOptimizer Fusion: Efficient Training with Better Locality and Parallelism

2 citations · 3 across the 3 of their papers we have counts for

collaborators

5 papers

cs.ET2024

Automated Curvy Waveguide Routing for Large-Scale Photonic Integrated Circuits

Hongjian Zhou, Keren Zhu, Jiaqi Gu

As photonic integrated circuit (PIC) designs advance and grow in complexity, largely driven by innovations in photonic computing and interconnects, traditional manual physical desi…

cs.AI2024

LLM-Enhanced Bayesian Optimization for Efficient Analog Layout Constraint Generation

Guojin Chen, Keren Zhu, Seunggeun Kim +4

Analog layout synthesis faces significant challenges due to its dependence on manual processes, considerable time requirements, and performance instability. Current Bayesian Optimi…

cs.LG2023

Practical Layout-Aware Analog/Mixed-Signal Design Automation with Bayesian Neural Networks

Ahmet F. Budak, Keren Zhu, David Z. Pan

The high simulation cost has been a bottleneck of practical analog/mixed-signal design automation. Many learning-based algorithms require thousands of simulated data points, which…

cs.AR20221 cited

TAG: Learning Circuit Spatial Embedding From Layouts

Keren Zhu, Hao Chen, Walker J. Turner +4

Analog and mixed-signal (AMS) circuit designs still rely on human design expertise. Machine learning has been assisting circuit design automation by replacing human experience with…

cs.LG20212 cited

Optimizer Fusion: Efficient Training with Better Locality and Parallelism

Zixuan Jiang, Jiaqi Gu, Mingjie Liu +2

Machine learning frameworks adopt iterative optimizers to train neural networks. Conventional eager execution separates the updating of trainable parameters from forward and backwa…