说句话就能设计模拟芯片？英伟达参与合作，华人团队打造AI芯片算法HeaRT，推理准确率超97%

DeepTech深科技02-18

说一句话就能设计模拟芯片的时代来了？假如你想做一个智能花盆，让花盆可以根据土壤湿度自动浇水，那么你需要一棵专门的芯片来控制。现在，你只需要告诉一款 AI 算法你需要一个能够检测湿度、控制水泵和功耗尽可能低的芯片，软件就能自动从数据库里找出最合适的设计方案，甚至帮你把具体参数都算好。你不需要了解晶体管的工作原理，也不需要知道电路怎么画，只需要“会说人话”，就能设计专属于自己的芯片。这便是美国德州大学...

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Nvidia participated in the cooperation, and the Chinese team built the AI chip algorithm HeaRT, with an inference accuracy rate of over 97%","themeId":null,"isJumpTheme":false,"ttsUrl":null,"symbols_score_info":{"NVDG":0.6,"NVDU":0.6,"NVDX":0.6,"NVDY":0.6,"SNVD.UK":0.6,"NVDL":0.6,"NVDA":1.86,"2NVD.UK":0.6,"DIPS":0.6,"NVDS":0.6,"NVD":0.6,"NVII":0.6,"3NVD.UK":0.6,"NVDW":0.6,"NVDS.UK":0.6,"NVIW.SI":0.6,"NVD2.UK":0.6,"NVDQ":0.6,"NVD3.UK":0.6,"NVDD":0.6},"content_text":"说一句话就能设计模拟芯片的时代来了？假如你想做一个智能花盆，让花盆可以根据土壤湿度自动浇水，那么你需要一棵专门的芯片来控制。现在，你只需要告诉一款 AI 算法你需要一个能够检测湿度、控制水泵和功耗尽可能低的芯片，软件就能自动从数据库里找出最合适的设计方案，甚至帮你把具体参数都算好。你不需要了解晶体管的工作原理，也不需要知道电路怎么画，只需要“会说人话”，就能设计专属于自己的芯片。这便是美国德州大学奥斯汀分校潘志刚（David Z. Pan）教授和英伟达等合作者打造的一款名为 HeaRT 的 AI 算法。HeaRT 能学会人类设计师的思维方式，它会把一个复杂的电路像剥洋葱一样一层一层剥开，先找到电流的主干道，然后沿着主干道找到一个个功能模块，再把这些模块拆成更小的子模块。最终，整个复杂的电路变成了一棵有层次的电路思维树。测试中，面对 40 个不同复杂程度的电路，HeaRT 从最简单的几十个元件到最复杂的几百个元件，它的推理准确率始终保持在 97% 以上，一次成功的概率超过 98%。也就是说，它基本不会出错，而且第一次就能给出正确答案。更令人惊讶的是它的速度，它只需要查看不到一半的电路，就能准确理解整个电路。在处理复杂电路时，它的实时效率是传统方法的两倍之多。（来源：https://arxiv.org/pdf/2511.19669）潘志刚告诉 DeepTech：“其灵感来源于人类电路设计中所采用的层次化抽象原则，而这一视角在既有研究中长期被忽视。通过构建一个仿照人类设计思维的层次化电路推理树（Hierarchical Circuit Reasoning Tree），HeaRT 实现了高效、实时且具备上下文感知能力的推理，并能够生成与具体查询条件相关的推理轨迹，从而显著提升可解释性、可调试性以及推理驱动的下游应用能力。”他继续说道：“根据我们与英伟达的研究人员以及多家领先公司的模拟及混合信号（AMS，Analog and Mixed-Signal）设计工程师的早期交流反馈，这项工作获得了非常积极的反响。”HeaRT 并非一次性看完整个电路就完事了。而是先从上往下拆解，再从下往上理解：叶子模块有什么作用？这些小模块组合起来能够实现什么功能？最终，整个电路在它脑子里不再是死板的线条，而是一个有逻辑、有层次、有功能的活生生的系统。这个过程，和人类顶级芯片设计师的思考方式一模一样。有了这棵电路思维树，令人意想不到的事情发生了。以前修改电路设计方案，就像装修房子一样要砸承重墙，牵一发而动全身。想优化一点点性能，可能得把整个电路重新设计一遍。芯片设计师们把这叫做灾难性遗忘。之前辛辛苦苦设计的模块，改着改着就忘了为什么这样设计，最后只能推倒重来。HeaRT 不一样。它知道电路里哪些是承重墙，哪些是隔断墙。当设计要求发生变化，比如需要手机芯片变得更加省电，它不会把整个电路发个底朝天，而是会精准定位到最影响功耗的那几个模块，只对这些模块加以优化，其他部分原封不动。这意味着 HeaRT 将模拟芯片设计从少数精英的专属技能，变成了每个人都能接触的工具。在实验中，HeaRT 已经展现出了这种能力。当要求其优化一个模拟前端电路并降低噪声的时候，它准确找到了最影响噪声的第一级放大模块，从数据库中检索出更加适合低噪声的架构，直接完成了传统方法需要多次迭代才能实现的优化，最终性能提升了 60% 一样，而设计思路的保留程度高达 59%。（来源：https://arxiv.org/pdf/2511.19669）潘志刚告诉 DeepTech：“我们的研究表明，基于层次化推理的方法可以在 AMS 设计自动化领域取得实质性突破。通过 HeaRT，我们首次将可解释推理系统性地引入一个长期依赖启发式黑箱方法的领域，使电路理解和分析变得清晰、可追溯。”实验结果显示，HeaRT 在推理质量上显著优于现有基于大模型的系统。更重要的是，他们首次系统性地强调了具备范围约束的自适应设计流程的重要性，该流程能够在规格变化时动态地进行拓扑检索与尺寸调整，仅修改必要的电路部分，从而真正实现设计意图的保留，而非每次都从零开始重新设计。得益于其基尔霍夫电流定律（KCL，Kirchhoff's Current Laws）一致的推理树结构，HeaRT 支持即插即用的模块化设计，使得不同抽象层级下的功能架构可以相互替换，同时保持电气正确性。这为在仅靠尺寸调整无法满足规格时，进行符合设计直觉的拓扑修改提供了清晰路径。此外，HeaRT 对不同类别的优化算法表现出良好的优化器无关性，进一步增强了鲁棒性与通用性。（来源：https://arxiv.org/pdf/2511.19669）潘志刚表示：“未来，我们已经规划了多条后续研究方向。其中一个重要方向是将 HeaRT 的层次化电路推理能力扩展到版图设计领域，这是减少当前设计流程中启发式依赖的自然下一步。虽然相关工作仍在进行中，细节暂不便公开，但我们的长期目标是构建一个从规格到可流片 GDSII 流格式（GDS，Graphic Design System）的端到端 AMS。”本次论文已经展示了若干具有代表性的下游优化场景，说明该框架如何为 AMS 设计自动化打开多条具有前景的发展路径。“我们目前也正在积极探索更加深入和复杂的应用方向，以进一步扩展并强化这些理念。”他说。参考资料：相关论文https://arxiv.org/pdf/2511.19669排版：胡巍巍","kind":"news","is_publish_news":true,"is_publish_highlight":false,"is_publish_live":false,"is_publish_wemedia":null,"editions":null,"column":"","sentiment":"0","news_tag":"","news_rank":0,"isVideo":false,"video":null,"symbols":[],"gpt_button":1,"need_auth":false,"need_login_tip":false,"code":"91000000","status":"200"},"commentList":[],"isCommentEnd":true,"newsSizeData":{"likeSize":0,"commentSize":0,"repostSize":0,"favoriteSize":0,"likeStatus":false,"favoriteStatus":false},"APP":{"userAgent":"Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; ClaudeBot/1.0; +claudebot@anthropic.com)","isDev":false,"isTTM":false,"tenantId":"TBCN","deviceId":"web-server-community-laohu8-v3","version":"4.43.1","shortVersion":"4.43.1","platform":"web","vendor":"web","appName":"laohu8","isIOS":false,"isAndroid":false,"isTiger":false,"isTHS":false,"isWeiXin":false,"isWeiXinMini":false,"isWeiBo":false,"isQQ":false,"isBaiduSwan":false,"isBaiduBox":false,"isDingTalk":false,"isToutiao":false,"isOnePlus":false,"isHuaWei":false,"isXiaomi":false,"isXiaomiWebView":false,"isOppo":false,"isVivo":false,"isSamsung":false,"isMobile":false},"href":"/m/news/2612241070","isCrawlerRequest":true}