arXiv:2607.25283cs.AIcs.AR2026-07

用自然语言生成可验证的硬件设计,支持系统级闭环反馈。

ContractHIL-HLS: Contract-Aligned Multi-Agent Workflow with Hardware-in-the-Loop Feedback for HLS Design

论文配图:ContractHIL-HLS: Contract-Aligned Multi-Agent Workflow with Hardware-in-the-Loop Feedback for HLS Design
图 1 · 摘自论文原文
  • 通过结构化契约将自然语言需求转为接口与约束
  • 实测单样本通过率提升至70.4%,五次尝试通过率达76.6%
  • 适合需快速迭代的硬件加速器开发人员

本文提出ContractHIL-HLS,一种面向实用高层次综合(HLS)工程的多智能体工作流。该工作流引入结构化契约作为语义对齐与任务执行的核心载体,将自然语言需求转化为明确接口、约束、验证检查和回滚规则;通过反馈HLS、Vivado、PYNQ运行时、功耗及故障证据,将大模型辅助HLS从核级扩展至系统与板级闭环;按语义降维与执行任务划分智能体:契约智能体负责将自然语言降至契约,HTML智能体以持久化结构化HTML呈现契约,硬件在环智能体则基于实测证据实施与修正设计。在94个本地可执行的HLS-Eval任务上,结构化契约使单样本测试通过率从64.0%提升至70.2%,完整流程达70.4% pass@1和76.6% pass@5。为验证板级能力,进一步在实测的ML-KEM/ML-DSA后量子密码安全消息加速器上评估,保留双比特流架构后,平均文本运行时间从207.3毫秒降至52.4毫秒,且两幅图像均保持正布线时序裕量并完成解密验证。代码已开源于BJUT-CS316-LAB/ContractHIL-HLS。

原文摘要 · Abstract (English)

This paper presents ContractHIL-HLS, a contract-aligned multi-agent workflow for practical high-level synthesis (HLS) engineering. The workflow makes three contributions. First, it introduces a structured contract as the semantic-alignment and task-execution artifact that translates natural language requirements into explicit interfaces, constraints, validation checks, and rollback rules. Second, it incorporates hardware information into the feedback loop by feeding HLS, Vivado, PYNQ runtime, power, and failure evidence back into generation, thereby extending LLM-assisted HLS from kernel code toward system- and board-level closure. Third, it decomposes agents by semantic lowering and execution tasks rather than by conversational roles: a Contract Agent lowers natural language into the contract, an HTML Agent renders the contract as persistent structured HTML, and a Hardware-in-the-Loop Agent implements and revises the design with measured evidence. We evaluate ContractHIL-HLS in two parts. On 94 locally executable HLS-Eval tasks, the structured contract provides the largest small design gain, improving the estimated single-sample testbench pass rate from 64.0% to 70.2%; the full flow reaches 70.4% pass@1 and 76.6% pass@5. Because HLS-Eval does not exercise board-level design, we also validate ContractHIL-HLS on a board tested ML-KEM/ML-DSA post-quantum cryptography (PQC) secure-message accelerator, where the retained dual-bitstream organization reduces six-message average text runtime from 207.3 ms to 52.4 ms with positive routed WNS on both images while preserving decrypted-message verification. We open-source our work at BJUT-CS316-LAB/ContractHIL-HLS (https://github.com/BJUT-CS316-LAB/ContractHIL-HLS).

硬件生成多智能体闭环反馈

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