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| Main Authors: | , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2512.23189 |
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| _version_ | 1866908818926993408 |
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| author | Zang, Zelin Song, Yuhang Wang, Aili Ling, Bingo Wing-Kuen Sun, Qi Lei, Zhen Yang, Fuji Zhuo, Cheng Luo, Jiebo |
| author_facet | Zang, Zelin Song, Yuhang Wang, Aili Ling, Bingo Wing-Kuen Sun, Qi Lei, Zhen Yang, Fuji Zhuo, Cheng Luo, Jiebo |
| contents | The semiconductor industry faces a critical "Productivity Gap" where design complexity outpaces human capacity. While the "AI for EDA" revolution (L2) successfully optimized specific point problems, a paradigm shift toward Agentic EDA (L3) is emerging, evolving from passive prediction to autonomous orchestration of the RTL-to-GDSII flow. This survey presents the first systematic framework for this transition, framing Agentic EDA not merely as "Chat with Tools," but as a Constrained Neuro-Symbolic Optimization problem. We propose a novel taxonomy rooted in a Cognitive Stack--Perception (aligning multimodal semantics), Cognition (planning under strict constraints), and Action (deterministic tool execution)--to dissect how probabilistic agents navigate zero-tolerance physical laws. Through this lens, we analyze the landscape: (1) in Frontend, the shift from one-shot generation to dual-loop syntactic-semantic repair; (2) in Backend, the dichotomy between algorithm-centric solvers and agent-centric orchestrators that treat executable code as a latent space. Finally, we critically examine the Trustworthiness gap, advocating for Sim-to-Silicon benchmarks and formal grounding to transform brittle prototypes into resilient engineering systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_23189 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | The Dawn of Agentic EDA: A Survey of Autonomous Digital Chip Design Zang, Zelin Song, Yuhang Wang, Aili Ling, Bingo Wing-Kuen Sun, Qi Lei, Zhen Yang, Fuji Zhuo, Cheng Luo, Jiebo Systems and Control The semiconductor industry faces a critical "Productivity Gap" where design complexity outpaces human capacity. While the "AI for EDA" revolution (L2) successfully optimized specific point problems, a paradigm shift toward Agentic EDA (L3) is emerging, evolving from passive prediction to autonomous orchestration of the RTL-to-GDSII flow. This survey presents the first systematic framework for this transition, framing Agentic EDA not merely as "Chat with Tools," but as a Constrained Neuro-Symbolic Optimization problem. We propose a novel taxonomy rooted in a Cognitive Stack--Perception (aligning multimodal semantics), Cognition (planning under strict constraints), and Action (deterministic tool execution)--to dissect how probabilistic agents navigate zero-tolerance physical laws. Through this lens, we analyze the landscape: (1) in Frontend, the shift from one-shot generation to dual-loop syntactic-semantic repair; (2) in Backend, the dichotomy between algorithm-centric solvers and agent-centric orchestrators that treat executable code as a latent space. Finally, we critically examine the Trustworthiness gap, advocating for Sim-to-Silicon benchmarks and formal grounding to transform brittle prototypes into resilient engineering systems. |
| title | The Dawn of Agentic EDA: A Survey of Autonomous Digital Chip Design |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2512.23189 |