Circuit Optimization

Circuit optimization aims to find the most efficient and effective circuit designs, minimizing resource consumption while maximizing performance. Current research focuses on developing advanced algorithms, including reinforcement learning and hybrid approaches combining graph neural networks with transformers, to navigate the vast design space and predict optimal circuit configurations. These methods are significantly improving the speed and accuracy of analog and quantum circuit design, impacting fields ranging from integrated circuit manufacturing to quantum computing. The incorporation of domain knowledge into these algorithms further enhances their efficiency and generalizability.

Papers

August 10, 2024

Efficient Quantum Gradient and Higher-order Derivative Estimation via Generalized Hadamard Test
Dantong Li, Dikshant Dulal, Mykhailo Ohorodnikov, Hanrui Wang, Yongshan Ding
Variational Quantum Algorithm Parameterized Quantum Circuit Near Term Quantum Hadamard Layer Quantum Natural Gradient Circuit Optimization

July 17, 2023

Quarl: A Learning-Based Quantum Circuit Optimizer
Zikun Li, Jinjun Peng, Yixuan Mei, Sina Lin, Yi Wu, Oded Padon, Zhihao Jia
Quantum Circuit Global Reasoning Circuit Optimization

July 23, 2022

The prediction of the quality of results in Logic Synthesis using Transformer and Graph Neural Networks
Chenghao Yang, Zhongda Wang, Yinshui Xia, Zhufei Chu
Graph Neural Network Transformer Based Human Prediction Quality Issue Logic Synthesis Optimal Synthesis Circuit Optimization

July 13, 2022

RobustAnalog: Fast Variation-Aware Analog Circuit Design Via Multi-task RL
Wei Shi, Hanrui Wang, Jiaqi Gu, Mingjie Liu, David Pan, Song Han, Nan Sun
Analog Circuit Design Analog Design Circuit Optimization

April 27, 2022

Domain Knowledge-Infused Deep Learning for Automated Analog/Radio-Frequency Circuit Parameter Optimization
Weidong Cao, Mouhacine Benosman, Xuan Zhang, Rui Ma
Deep Learning Internet Service Domain Analog Bit Analog Circuit Analog Circuit Design Analog Design Circuit Optimization

February 26, 2022

Domain Knowledge-Based Automated Analog Circuit Design with Deep Reinforcement Learning
Weidong Cao, Mouhacine Benosman, Xuan Zhang, Rui Ma
Deep Reinforcement Learning Internet Service Domain Analog Circuit Analog Circuit Design Analog Design Circuit Optimization

Circuit Optimization

Papers

Efficient Quantum Gradient and Higher-order Derivative Estimation via Generalized Hadamard Test

Quarl: A Learning-Based Quantum Circuit Optimizer

The prediction of the quality of results in Logic Synthesis using Transformer and Graph Neural Networks

RobustAnalog: Fast Variation-Aware Analog Circuit Design Via Multi-task RL

Domain Knowledge-Infused Deep Learning for Automated Analog/Radio-Frequency Circuit Parameter Optimization

Domain Knowledge-Based Automated Analog Circuit Design with Deep Reinforcement Learning