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This survey provides a unified taxonomy for LLM-based agents in electronic design automation (EDA), categorizing systems by their input/output handoff roles across intra-, inter-, and extra-stage workflows. By analyzing 115 representative systems, the paper maps current research trends, benchmarks, and model mechanisms to clarify how AI is reshaping complex chip design pipelines. It concludes with a protocol roadmap that addresses fragmentation and identifies critical open problems for future agentic EDA development.
Sources coveringarXiv, livenews.co.nz
What this isA model's reading of the article and related coverage, written for aiqbench. Not the publisher's words.

Agentic Electronic Design Automation: A Handoff Perspective

arXiv2 min read

arXiv:2606.19795v2 Announce Type: replace-cross Abstract: Electronic design automation (EDA) is multi-stage and handoff-heavy, relying on transfers among humans, design artifacts, and multiple tools. LLM-based agents now participate in these transfers, yet the resulting research landscape is highly fragmented and lacks a unified perspective. This survey adopts the primary input--output pair as its organizing lens: for each agent system, we analyze its primary, supporting, and intermediate handoff objects and classify it according to the provenance of its primary input and the consumer boundary of its primary output. Intra-stage systems operate on objects within a single EDA stage, inter-stage systems transform EDA-native artifacts into forms usable by downstream stages, and extra-stage systems translate human intent into EDA artifacts. Based on this taxonomy, we survey 115 representative systems and examine them along multiple dimensions, including research trends, benchmarks, and model mechanisms. Finally, we outline an agentic EDA protocol roadmap and discuss open problems for future research.

Abstract:Electronic design automation (EDA) is multi-stage and handoff-heavy, relying on transfers among humans, design artifacts, and multiple tools. LLM-based agents now participate in these transfers, yet the resulting research landscape is highly fragmented and lacks a unified perspective. This survey adopts the primary input--output pair as its organizing lens: for each agent system, we analyze its primary, supporting, and intermediate handoff objects and classify it according to the provenance of its primary input and the consumer boundary of its primary output. Intra-stage systems operate on objects within a single EDA stage, inter-stage systems transform EDA-native artifacts into forms usable by downstream stages, and extra-stage systems translate human intent into EDA artifacts. Based on this taxonomy, we survey 115 representative systems and examine them along multiple dimensions, including research trends, benchmarks, and model mechanisms. Finally, we outline an agentic EDA protocol roadmap and discuss open problems for future research.

Software Engineering (cs.SE); Artificial Intelligence (cs.AI)

arXiv:2606.19795 [cs.SE]

(or arXiv:2606.19795v2 [cs.SE] for this version)

https://doi.org/10.48550/arXiv.2606.19795 Focus to learn more arXiv-issued DOI via DataCite

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Full text under the publisher's open licence · 243 words

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