AMD 苏姿丰确认 EPYC 担任 Google TPU 8tx 主机处理器

非常高兴能与大家分享我们 @Google 的 AI 与基础设施团队取得的一项重大里程碑。 今天，我们通过以下产品扩展了我们的第八代 TPU 产品组合： • TPU 8i Max：专为超大规模上下文窗口和每机架最高计算密度而打造 • TPU 8tx：专为安全、机密推理而设计 这标志着我们首次在一年内、于同一代产品中推出四款不同的 TPU 系统。 对开发者而言，硬件的价值取决于软件栈。我们希望你们能够像我们在 Google 内部一样，轻松高效地基于 TPU 进行构建。现在，你可以： ↳ 通过 TorchTPU 运行原生 PyTorch 和 Hugging Face 模型（无需重写任何代码） ↳ 借助开源 TPU Sync 将 KV 传输延迟降低 90% 以上 ↳ 通过 Agent Compute Engine 消除闲置算力浪费 在我们的博客上阅读更多关于最新 TPU 的内容：https://t.co/8eaFhq3jhi 我期待与不断拓展 AI 与计算边界的开发者、研究人员、工程师以及各机构建立联系！

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Thrilled to share a big milestone from our AI & Infrastructure team at @Google. Today we’re expanding our 8th generation TPU portfolio with: • TPU 8i Max: Built for massive context windows and the highest compute density per rack • TPU 8tx: Purpose-built for secure, confidential inference This marks the first time we’ve introduced four distinct TPU systems in a single generation, in one year. For developers, hardware is only as good as the software stack. And we want you to be able to build with TPUs as easily and efficiently as we do at Google. You can now: ↳ Run native PyTorch & Hugging Face models via TorchTPU (zero code rewrites) ↳ Cut KV transfer latency >90% with open-source TPU Sync ↳ Eliminate idle compute waste with Agent Compute Engine Read more about our newest TPUs on our blog: https://t.co/8eaFhq3jhi I look forward to connecting with builders, researchers, engineers and organizations pushing the boundaries of AI and computing!