MenTeR: A fully-automated Multi-agenT workflow for end-to-end RF/Analog Circuits Netlist Design
Pin-Han Chen, Yu-Sheng Lin, Wei-Cheng Lee, Tin-Yu Leu, Po-Hsiang Hsu, Anjana Dissanayake, Sungjin Oh, Chinq-Shiun Chiu

TL;DR
MenTeR is an automated multi-agent system that streamlines RF/Analog circuit design by reducing manual effort, accelerating development, and enabling broader exploration of design options through collaborative AI agents.
Contribution
Introduces MenTeR, a multi-agent framework that automates end-to-end RF/Analog circuit design, reducing reliance on expert intuition and trial-and-error methods.
Findings
Accelerates RF/Analog circuit design process.
Enhances exploration of design space.
Demonstrates robustness in real-world applications.
Abstract
RF/Analog design is essential for bridging digital technologies with real-world signals, ensuring the functionality and reliability of a wide range of electronic systems. However, analog design procedures are often intricate, time-consuming and reliant on expert intuition, and hinder the time and cost efficiency of circuit development. To overcome the limitations of the manual circuit design, we introduce MenTeR - a multiagent workflow integrated into an end-to-end analog design framework. By employing multiple specialized AI agents that collaboratively address different aspects of the design process, such as specification understanding, circuit optimization, and test bench validation, MenTeR reduces the dependency on frequent trial-and-error-style intervention. MenTeR not only accelerates the design cycle time but also facilitates a broader exploration of the design space,…
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Taxonomy
TopicsVLSI and FPGA Design Techniques · Evolutionary Algorithms and Applications · Machine Learning in Materials Science
