<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>AI 芯片 on Pengcheng's Blog</title><link>https://pengchengneo.github.io/tags/ai-%E8%8A%AF%E7%89%87/</link><description>Recent content in AI 芯片 on Pengcheng's Blog</description><generator>Hugo -- gohugo.io</generator><language>zh-CN</language><copyright>© 2026 Pengcheng</copyright><lastBuildDate>Mon, 24 Aug 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://pengchengneo.github.io/tags/ai-%E8%8A%AF%E7%89%87/index.xml" rel="self" type="application/rss+xml"/><item><title>AI 芯片架构全景：GPU、TPU、Trainium、WSE 与 LPU</title><link>https://pengchengneo.github.io/posts/ai-chip-architectures-zh/</link><pubDate>Mon, 24 Aug 2026 00:00:00 +0000</pubDate><guid>https://pengchengneo.github.io/posts/ai-chip-architectures-zh/</guid><description>系统比较 NVIDIA GPU、Google TPU、AMD GPU、Cerebras WSE、AWS Trainium 与 Groq LPU 的设计理念、计算与内存架构、扩展方式和软件栈。</description></item></channel></rss>