BTTF：用多智能体框架自动化芯片验证中的波形调试
Back to the Future: Rethinking EDA Infrastructure for Agentic Systems in Chip Design Verification
做芯片验证的朋友可以看看，这篇用 SQLite 加多智能体把波形调试从手动翻日志变成自然语言查询，150 条查询准确率 95% 以上。
论文 BTTF 针对 LLM 在 EDA 领域的应用现状提出改进：现有约 74.6% 的研究集中在静态 RTL 代码生成，仿真后验证与波形调试仍靠人工。BTTF 将海量仿真数据转成 SQLite 关系型数据库，再由多智能体引擎把自然语言验证查询转成 schema 感知的 SQL，并把信号异常与带版本号的 RTL 仓库关联。在 150 条查询的基准上，BTTF 达到 95.33% 的执行准确率。
Back to the Future: Rethinking EDA Infrastructure for Agentic Systems in Chip Design Verification
The unprecedented computational scale of modern artificial intelligence depends on complex, multi-billion-transistor Systems-on-Chip, yet the workflows that verify these chips remain stubbornly manual. Although Large Language Models (LLMs) have made rapid inroads into Electronic Design Automation (EDA), approximately 74.6% of existing studies target static Register-Transfer Level (RTL) code generation, leaving post-simulation verification and interactive waveform debugging largely untouched. We introduce Back-to-the-Future (BTTF), an end-to-end agentic framework that closes this infrastructural gap. BTTF distills massive, unstructured simulation dumps into a normalized relational SQLite database and couples it with a collaborative multi-agent orchestration engine that translates natural-language verification queries into schema-aware SQL while correlating signal anomalies with versioned RTL repositories. Across a 150-query benchmark, BTTF attains 95.33% execution accuracy, charting a practical path toward autonomous EDA verification.
- shao__meng10-07 02:51原文
