从语义到伙伴：代理高层综合的共生进化
From Pragmas to Partners: A Symbiotic Evolution of Agentic High-Level Synthesis
AI总结：
本文探讨了在代理时代高层综合（HLS）的重要性，提出HLS作为代理优化的自然层次，并提出HLS工具的局限性及代理在其中的潜在作用。
摘要：
大语言模型的兴起引发了对AI驱动硬件设计的兴趣，提出了一个问题：在代理时代，高层综合（HLS）是否仍然重要？我们认为HLS仍然至关重要。尽管我们预计成熟的代理硬件系统会同时利用HLS和RTL，本文专注于HLS及其在促进代理优化中的作用。HLS提供更快的迭代周期、可移植性和设计可变性，使其成为代理优化的自然层次。本文立场论文做出了三个贡献。首先，我们解释了为什么HLS既是实用的抽象层，也是代理硬件设计的黄金参考。其次，我们识别了当前HLS工具的关键局限性，即性能反馈不足、接口僵化和调试性有限，这些问题只有代理才能独特地解决。第三，我们提出了一种代理HLS共生进化的分类法，阐明了随着系统从共驾者发展到自主设计伙伴，责任从人类设计师转移到AI代理的过程。
英文摘要：
The rise of large language models has sparked interest in AI-driven hardware design, raising the question: does high-level synthesis (HLS) still matter in the agentic era? We argue that HLS remains essential. While we expect mature agentic hardware systems to leverage both HLS and RTL, this paper focuses on HLS and its role in enabling agentic optimization. HLS offers faster iteration cycles, portability, and design permutability that make it a natural layer for agentic optimization. This position paper makes three contributions. First, we explain why HLS serves as a practical abstraction layer and a golden reference for agentic hardware design. Second, we identify key limitations of current HLS tools, namely inadequate performance feedback, rigid interfaces, and limited debuggability that agents are uniquely positioned to address. Third, we propose a taxonomy for the symbiotic evolution of agentic HLS, clarifying how responsibility shifts from human designers to AI agents as systems advance from copilots to autonomous design partners.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
