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ChatEDA: A Large Language Model Powered Autonomous Agent for EDA

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arxiv 2308.10204 v4 pith:P3ERJIQM submitted 2023-08-20 cs.AR cs.AI

classification cs.ARcs.AI
keywords chatedalanguagetoolsagentautomageautonomousdesignlarge
verification ladder T0 review T1 audit T2 compute T3 formal
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The integration of a complex set of Electronic Design Automation (EDA) tools to enhance interoperability is a critical concern for circuit designers. Recent advancements in large language models (LLMs) have showcased their exceptional capabilities in natural language processing and comprehension, offering a novel approach to interfacing with EDA tools. This research paper introduces ChatEDA, an autonomous agent for EDA empowered by an LLM, AutoMage, complemented by EDA tools serving as executors. ChatEDA streamlines the design flow from the Register-Transfer Level (RTL) to the Graphic Data System Version II (GDSII) by effectively managing task decomposition, script generation, and task execution. Through comprehensive experimental evaluations, ChatEDA has demonstrated its proficiency in handling diverse requirements, and our fine-tuned AutoMage model has exhibited superior performance compared to GPT-4 and other similar LLMs.

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Cited by 5 Pith papers

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  3. Retrieve, Schedule, Reflect: LLM Agents for Chip QoR Optimization

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  4. MCP4EDA: LLM-Powered Model Context Protocol RTL-to-GDSII Automation with Backend Aware Synthesis Optimization

    cs.AR 2025-07 conditional novelty 6.0 of 10

    MCP4EDA is an MCP server that lets LLMs orchestrate the open-source RTL-to-GDSII flow and iteratively refine synthesis scripts from post-layout metrics.

  5. Spec2RTL-Agent: Automated Hardware Code Generation from Complex Specifications Using LLM Agent Systems

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    On three NIST crypto standards (AES, DSS, HMAC), Spec2RTL-Agent generates RTL via a multi-agent pipeline from pseudocode to Python to synthesizable C++, reporting 3/3 correct designs with about 4.3 human interventions...

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