TPU 订单狂增，谷歌扩产新一代芯片！谷歌首席科学家：我们使用 10 多年了，一直非常满意

AI前线2025-12-20

作者 | 褚杏娟根据最新报道，随着谷歌 TPU 芯片需求大涨，谷歌扩大了对联发科合作定制新一代 TPU v7e 的订单，订单量比原规划激增数倍。消息称，联发科为谷歌操刀定制的首款 TPU v7e 将于下季度末进入风险性试产，并再拿下谷歌下一代 TPU v8e 的订单。联发科大单获得了台积电的先进封装产能支持，2027 年台积电提供给联发科谷歌项目的 CoWoS 产能更将暴增 7 倍以上。尽管承认...

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Google Chief Scientist: We have been using it for more than 10 years and have been very satisfied","themeId":null,"isJumpTheme":false,"ttsUrl":null,"symbols_score_info":{"GOOG":0.9,"GOOGL":1.97,"USJW.SI":0.6},"content_text":"作者 | 褚杏娟根据最新报道，随着谷歌 TPU 芯片需求大涨，谷歌扩大了对联发科合作定制新一代 TPU v7e 的订单，订单量比原规划激增数倍。消息称，联发科为谷歌操刀定制的首款 TPU v7e 将于下季度末进入风险性试产，并再拿下谷歌下一代 TPU v8e 的订单。联发科大单获得了台积电的先进封装产能支持，2027 年台积电提供给联发科谷歌项目的 CoWoS 产能更将暴增 7 倍以上。尽管承认谷歌在过去 10 年中取得了进步，但英伟达认为其大约领先谷歌 TPU 两年。由于人工智能模型变化迅速，英伟达认为谷歌很难让云服务提供商采用 TPU，因为 TPU 是为更特定的模型类型而设计的。相比之下，英伟达相信其更灵活、可编程的平台仍然是构建大规模云端人工智能基础设施的最佳选择。但无论如何，谷歌确实让英伟达产生了些许危机。近日，在 NeurIPS 大会期间，谷歌 DeepMind、谷歌研究院的首席科学家兼 Gemini 项目联合技术负责人 Jeff Dean 做客 Laude Lounge 节目，聊到了 TPU 和 Pathways 等基础系统是如何出现的，下面是其在节目中的相关对话。主持人：谷歌最近发布了一款新型 TPU 芯片。第七代 TPU 芯片有什么特别之处？Jeff Dean：就像每一代后续的 TPU 芯片一样，它都比上一代更出色。它有很多新功能，这些芯片会连接成我们称之为集群（pods）的大型配置。我记得每个集群大概有 9216 块芯片。而且它的性能提升非常显著，尤其是在处理 FP4 这类低精度浮点格式时。这对大模型训练、推理以及很多类似场景都非常有用。所以我们对此非常兴奋。主持人：很棒。往大了说，谷歌最初开发 TPU 是为了满足内部需求。谷歌是全球顶尖的人工智能应用公司和人工智能研究机构，据我了解，最初的动机是希望掌控完整的垂直整合技术栈。之后你们最终开放了这些技术的使用权，在加速器态系统中参与全球竞争，与其他设计和销售加速器的企业同台竞技。现在很多人都对 TPU 的巨大市场潜力感到兴奋。在你看来，你在谷歌的角色如何平衡两方面目标：一方面是谷歌内部对 TPU 的使用需求，另一方面是在竞争激烈的市场中参与竞争，让谷歌之外的数百万人、数十亿人都能通过购买 TPU 获得这些技术优势？Jeff Dean：TPU 项目最初确实是为了满足我们内部需求，一开始主要聚焦于推理。早在 2013 年，我们就意识到深度学习方法将会非常成功。而且每次我们用更多数据训练更大规模的模型时，在语音和视觉等领域的效果都会更好。当时我做了一些粗略估算，如果我们想把这个性能更优但计算密集型的语音模型推广给 1 亿用户，让他们每天使用几分钟，所需的计算量会非常惊人。如果用 CPU 来处理，我们实际上需要把谷歌的电脑数量增加一倍，才能推出这个改进后的语音模型。所以，这就是我们的初衷：如果我们设计专门用于这类机器学习计算的硬件，也就是密集低精度线性代数相关的硬件，就能大幅提升效率。事实也证明了这一点。第一代 TPU 的能效比当时的 CPU 或 GPU 高出 30 到 70 倍，速度也快 15 到 30 倍。主持人：你是说那是 2015 年的事？Jeff Dean：是的。我们 2013 年开始进行这个思想实验，2015 年这些芯片才部署到我们的数据中心。我们还就此发表了一篇论文，当时还是前 Transformer 架构时代。主持人：前 Transformer 架构时代啊。Jeff Dean：对。当时我们主要关注语音识别和视觉卷积模型。我们在第一代 TPUv1 的设计末期，特意加了一点设计改动，让它也支持长短期记忆网络。当时长短期记忆网络在语言建模领域很流行，这一改动也让我们能够支持语言翻译任务。之后的 TPU 版本则更侧重于更大规模的系统，不再只是单一的 PCIe 卡，而是完整的机器学习超级计算机，包括最新的 Ironwood 芯片。每一代 TPU 都在能效、性价比等我们关注的方面都有很大提升，这让我们能够支持更大规模的训练任务，也能处理更多用户的请求。主持人：Transformer 架构本身也是在谷歌诞生的，时间线差不多。但 TPU 是在这之前发明的，之后 Transformer 架构才出现。你认为，随着 Transformer 架构的发展改变了我们如今的世界，谷歌拥有这种垂直整合的硬件栈，两者之间是否存在协同设计的偶然性？Jeff Dean：每一代 TPU 的开发，我们都非常努力地利用协同设计的机会。我们有很多研究人员会思考未来 2 年半到 6 年内我们可能会运行哪些机器学习计算。作为硬件设计者，你需要预测这个发展迅速的领域，这并不容易。但有很多人在关注这个领域的发展方向，他们会提出一些可能有趣的想法。虽然我们还不确定这些想法是否可行，但我们可以在硬件中加入相关的硬件特性或功能。如果这些想法最终被证明很重要，我们的硬件就能及时提供支持。就算这些投入没有得到回报，也只是在芯片面积上占用了一小部分空间，不算太大的损失，但我们确实需要为这些重要的潜在需求做好准备。这是一项很有趣的预测工作，需要预测整个机器学习领域的发展方向，然后判断我们需要什么样的硬件支持。主持人：纵观您在谷歌的过往，从 MapReduce 到 Google File System，这些最初都是为谷歌内部需求而发明的系统，最终都对外发布了。您见证了谷歌创造并向世界展示价值，然后通过 TPU 架构等公开发布。您是否认为，随着 Ironwood 的发布，世界其他地方也即将迎来拐点，获得谷歌曾经享有的优势？对于一位研究人员来说，影响力的实现就是我们追求的时刻，您是否感觉 TPU 正处于这个关键的拐点？Jeff Dean：是的，我们使用 TPU 已经超过十年了，一直对它们非常满意。协同设计的特性使它们非常适合我们想运行的各种机器学习计算。多年来，我们也通过我们的云 TPU（Cloud TPU）项目对外出租。现在，许多客户正将它们用于各种不同的任务。我们在 TPU 之上构建了一系列软件层，让它们使用起来非常方便。目前，使用 TPU 最成熟的途径是 JAX 框架，它运行在我们内部构建的 Pathways 系统之上，而 Pathways 又运行在 XLA 编译器（一个带有 TPU 后端的机器学习编译器）之上。Pathways 的意义在于，我们所有的 Gemini 模型开发、研究和大规模训练任务都运行在这个技术栈上。Pathways 是一个我们从大约七年前开始构建的优秀系统，它能够给你一种单一系统映像的错觉，跨越数千或数万个芯片。你可以运行一个单独的 Python 进程来驱动你的 JAX 代码，它不会显示为单个 TPU 节点上的四个设备，而是显示为你的 JAX 进程可以访问 2 万个设备。它运行起来非常自然，系统会在底层自动找出应该使用哪种传输机制和哪个网络：在 TPU Pod 内部使用高速互连，跨越 Pod 边界时使用数据中心网络，跨越城市区域时使用长距离链接（Long-distance Links）等等。我们实际上运行着非常大规模的训练任务，其中一个 Python 进程驱动着位于多个城市的多个 TPU Pod。参考链接：https://www.youtube.com/watch?v=9u21oWjI7Xk&t=31s声明：本文为 InfoQ 翻译整理，不代表平台观点，未经许可禁止转载。技术人的年度仪式感！#InfoQ 年度盘点与趋势洞察 启动！《2025 年度盘点与趋势洞察》由 InfoQ 技术编辑组策划。覆盖大模型、Agent、具身智能、AI Native 开发范式、AI 工具链与开发、AI+ 传统行业等方向，通过长期跟踪、与业内专家深度访谈等方式，对重点领域进行关键技术进展、核心事件和产业趋势的洞察盘点。力求以体系化视角帮助读者理解年度技术演化的底层逻辑、创新方向与落地价值，并为新一年决策提供参考。内容将在 InfoQ 媒体矩阵陆续放出，欢迎大家持续关注。今日荐文AI编码工具变 “格式化神器”？Claude CLI半年频当“系统杀手”，多位开发者痛斥：心血都没了！知情人士回应豆包手机被约谈；传MiniMax、智谱计划很快香港IPO；OpenAI被曝使用Agent Skills | AI周报张涛首次回应争议，Manus 为什么没有被替代？GPT-5.2全力出击！碾压44类专业工作，实测编程同价位无对手、深度推理封神，但速度太拉胯了28岁外来人“手撕”近 20 年元老？Meta全面内战：算力争夺、“开源”祭旗，每周工作70小时，亚历山大王真“压力山大”你也“在看”吗？","kind":"news","is_publish_news":true,"is_publish_highlight":false,"is_publish_live":false,"is_publish_wemedia":null,"editions":null,"column":"","sentiment":"1","news_tag":"productRelease","news_rank":0,"symbols":[],"gpt_button":0,"need_auth":false,"code":"91000000","status":"200"},"commentList":[],"isCommentEnd":true,"newsSizeData":{"likeSize":1,"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":"4.36.2","shortVersion":"4.36.2","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/2592125201","isCrawlerRequest":true}