AnalogGym: An Open and Practical Testing Suite for Analog Circuit Synthesis

Fuente: arXiv
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Hauptverfasser: Li, Jintao, Zhi, Haochang, Lyu, Ruiyu, Li, Wangzhen, Bi, Zhaori, Zhu, Keren, Zeng, Yanhan, Shan, Weiwei, Yan, Changhao, Yang, Fan, Li, Yun, Zeng, Xuan
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Veröffentlicht: 2024
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author Li, Jintao
Zhi, Haochang
Lyu, Ruiyu
Li, Wangzhen
Bi, Zhaori
Zhu, Keren
Zeng, Yanhan
Shan, Weiwei
Yan, Changhao
Yang, Fan
Li, Yun
Zeng, Xuan
author_facet Li, Jintao
Zhi, Haochang
Lyu, Ruiyu
Li, Wangzhen
Bi, Zhaori
Zhu, Keren
Zeng, Yanhan
Shan, Weiwei
Yan, Changhao
Yang, Fan
Li, Yun
Zeng, Xuan
contents Recent advances in machine learning (ML) for automating analog circuit synthesis have been significant, yet challenges remain. A critical gap is the lack of a standardized evaluation framework, compounded by various process design kits (PDKs), simulation tools, and a limited variety of circuit topologies. These factors hinder direct comparisons and the validation of algorithms. To address these shortcomings, we introduced AnalogGym, an open-source testing suite designed to provide fair and comprehensive evaluations. AnalogGym includes 30 circuit topologies in five categories: sensing front ends, voltage references, low dropout regulators, amplifiers, and phase-locked loops. It supports several technology nodes for academic and commercial applications and is compatible with commercial simulators such as Cadence Spectre, Synopsys HSPICE, and the open-source simulator Ngspice. AnalogGym standardizes the assessment of ML algorithms in analog circuit synthesis and promotes reproducibility with its open datasets and detailed benchmark specifications. AnalogGym's user-friendly design allows researchers to easily adapt it for robust, transparent comparisons of state-of-the-art methods, while also exposing them to real-world industrial design challenges, enhancing the practical relevance of their work. Additionally, we have conducted a comprehensive comparison study of various analog sizing methods on AnalogGym, highlighting the capabilities and advantages of different approaches. AnalogGym is available in the GitHub repository https://github.com/CODA-Team/AnalogGym. The documentation is also available at http://coda-team.github.io/AnalogGym/.
format Preprint
id arxiv_https___arxiv_org_abs_2409_08534
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle AnalogGym: An Open and Practical Testing Suite for Analog Circuit Synthesis
Li, Jintao
Zhi, Haochang
Lyu, Ruiyu
Li, Wangzhen
Bi, Zhaori
Zhu, Keren
Zeng, Yanhan
Shan, Weiwei
Yan, Changhao
Yang, Fan
Li, Yun
Zeng, Xuan
Hardware Architecture
Recent advances in machine learning (ML) for automating analog circuit synthesis have been significant, yet challenges remain. A critical gap is the lack of a standardized evaluation framework, compounded by various process design kits (PDKs), simulation tools, and a limited variety of circuit topologies. These factors hinder direct comparisons and the validation of algorithms. To address these shortcomings, we introduced AnalogGym, an open-source testing suite designed to provide fair and comprehensive evaluations. AnalogGym includes 30 circuit topologies in five categories: sensing front ends, voltage references, low dropout regulators, amplifiers, and phase-locked loops. It supports several technology nodes for academic and commercial applications and is compatible with commercial simulators such as Cadence Spectre, Synopsys HSPICE, and the open-source simulator Ngspice. AnalogGym standardizes the assessment of ML algorithms in analog circuit synthesis and promotes reproducibility with its open datasets and detailed benchmark specifications. AnalogGym's user-friendly design allows researchers to easily adapt it for robust, transparent comparisons of state-of-the-art methods, while also exposing them to real-world industrial design challenges, enhancing the practical relevance of their work. Additionally, we have conducted a comprehensive comparison study of various analog sizing methods on AnalogGym, highlighting the capabilities and advantages of different approaches. AnalogGym is available in the GitHub repository https://github.com/CODA-Team/AnalogGym. The documentation is also available at http://coda-team.github.io/AnalogGym/.
title AnalogGym: An Open and Practical Testing Suite for Analog Circuit Synthesis
topic Hardware Architecture
url https://arxiv.org/abs/2409.08534