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The design automation of analog circuits is a longstanding challenge. This paper presents a reinforcement learning method enhanced by graph learning to automate the analog circuit parameter optimization at the pre-layout stage, i.e.,…

Machine Learning · Computer Science 2022-05-18 Weidong Cao , Mouhacine Benosman , Xuan Zhang , Rui Ma

The design automation of analog circuits is a longstanding challenge in the integrated circuit field. This paper presents a deep reinforcement learning method to expedite the design of analog circuits at the pre-layout stage, where the goal…

Machine Learning · Computer Science 2022-03-01 Weidong Cao , Mouhacine Benosman , Xuan Zhang , Rui Ma

Analog IC design relies on human experts to search for parameters that satisfy circuit specifications with their experience and intuitions, which is highly labor intensive, time consuming and suboptimal. Machine learning is a promising tool…

Machine Learning · Computer Science 2020-12-08 Hanrui Wang , Jiacheng Yang , Hae-Seung Lee , Song Han

In this work, we present a learning based approach to analog circuit design, where the goal is to optimize circuit performance subject to certain design constraints. One of the aspects that makes this problem challenging to optimize, is…

Machine Learning · Computer Science 2020-11-17 Wook Lee , Frans A. Oliehoek

The manual design of analog circuits is a tedious task of parameter tuning that requires hours of work by human experts. In this work, we make a significant step towards a fully automatic design method that is based on deep learning. The…

Machine Learning · Computer Science 2020-02-11 Michael Rotman , Lior Wolf

In recent years, analog circuits have received extensive attention and are widely used in many emerging applications. The high demand for analog circuits necessitates shorter circuit design cycles. To achieve the desired performance and…

Machine Learning · Computer Science 2024-05-17 Qi Xu , Lijie Wang , Jing Wang , Lin Cheng , Song Chen , Yi Kang

Automating analog and radio-frequency (RF) circuit design using machine learning (ML) significantly reduces the time and effort required for parameter optimization. This study explores supervised ML-based approaches for designing circuit…

Machine Learning · Computer Science 2025-01-22 Asal Mehradfar , Xuzhe Zhao , Yue Niu , Sara Babakniya , Mahdi Alesheikh , Hamidreza Aghasi , Salman Avestimehr

Domain specialization under energy constraints in deeply-scaled CMOS has been driving the need for agile development of Systems on a Chip (SoCs). While digital subsystems have design flows that are conducive to rapid iterations from…

Signal Processing · Electrical Eng. & Systems 2020-01-22 Keertana Settaluri , Ameer Haj-Ali , Qijing Huang , Kourosh Hakhamaneshi , Borivoje Nikolic

In this work, a new method for designing an analog circuit for deep sub-micron CMOS fabrication processes is proposed. The proposed method leverages the regression algorithms with the transistor circuit model to size a transistor in 0.18 um…

Other Computer Science · Computer Science 2024-01-31 Alireza Bagheri Rajeoni

Analog circuit topology synthesis is integral to Electronic Design Automation (EDA), enabling the automated creation of circuit structures tailored to specific design requirements. However, the vast design search space and strict constraint…

Computation and Language · Computer Science 2025-06-04 Prashanth Vijayaraghavan , Luyao Shi , Ehsan Degan , Vandana Mukherjee , Xin Zhang

We propose a machine learning-driven optimisation framework for analog circuit design in this paper. The primary objective is to determine the device sizes for the optimal performance of analog circuits for a given set of specifications.…

Neural and Evolutionary Computing · Computer Science 2024-12-16 Ria Rashid , Komala Krishna , Clint Pazhayidam George , Nandakumar Nambath

Analog and mixed-signal (AMS) integrated circuits (ICs) lie at the core of modern computing and communications systems. However, despite the continued rise in design complexity, advances in AMS automation remain limited. This reflects the…

Machine Learning · Computer Science 2026-02-16 Felicia B. Guo , Ken T. Ho , Andrei Vladimirescu , Borivoje Nikolic

This paper introduces new perspectives on analog design space search. To minimize the time-to-market, this endeavor better cast as constraint satisfaction problem than global optimization defined in prior arts. We incorporate model-based…

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 artificial intelligence. This paper presents TAG, a new…

Hardware Architecture · Computer Science 2022-09-09 Keren Zhu , Hao Chen , Walker J. Turner , George F. Kokai , Po-Hsuan Wei , David Z. Pan , Haoxing Ren

Analog circuit design is a significant task in modern chip technology, focusing on the selection of component types, connectivity, and parameters to ensure proper circuit functionality. Despite advances made by Large Language Models (LLMs)…

Machine Learning · Computer Science 2024-05-31 Yao Lai , Sungyoung Lee , Guojin Chen , Souradip Poddar , Mengkang Hu , David Z. Pan , Ping Luo

Post-layout simulation provides accurate guidance for analog circuit design, but post-layout performance is hard to be directly optimized at early design stages. Prior work on analog circuit sizing often utilizes pre-layout simulation…

Hardware Architecture · Computer Science 2023-10-24 Xiaohan Gao , Haoyi Zhang , Siyuan Ye , Mingjie Liu , David Z. Pan , Linxiao Shen , Runsheng Wang , Yibo Lin , Ru Huang

Analog and radio-frequency circuit design requires extensive exploration of both circuit topology and parameters to meet specific design criteria like power consumption and bandwidth. Designers must review state-of-the-art topology…

Hardware Architecture · Computer Science 2024-07-29 Asal Mehradfar , Xuzhe Zhao , Yue Niu , Sara Babakniya , Mahdi Alesheikh , Hamidreza Aghasi , Salman Avestimehr

Analog mixed-signal (AMS) circuit architecture has evolved towards more digital friendly due to technology scaling and demand for higher flexibility/reconfigurability. Meanwhile, the design complexity and cost of AMS circuits has…

Emerging Technologies · Computer Science 2021-12-16 Shiyu Su , Qiaochu Zhang , Mohsen Hassanpourghadi , Juzheng Liu , Rezwan A Rasul , Mike Shuo-Wei Chen

Analog/mixed-signal circuit design is one of the most complex and time-consuming stages in the whole chip design process. Due to various process, voltage, and temperature (PVT) variations from chip manufacturing, analog circuits inevitably…

Emerging Technologies · Computer Science 2022-07-15 Wei Shi , Hanrui Wang , Jiaqi Gu , Mingjie Liu , David Pan , Song Han , Nan Sun

Testing is essential for verifying and validating control designs, especially in safety-critical applications. In particular, the control system governing an automated driving vehicle must be proven reliable enough for its acceptance on the…

Systems and Control · Electrical Eng. & Systems 2023-09-11 Mengjia Zhu , Alberto Bemporad , Maximilian Kneissl , Hasan Esen
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