蟹老板 @emphui
AI浪潮中的投资周期观察者，用数据与逻辑看清泡沫与机会 Joined March 2021-
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蟹老板 retweeted
這台 Wiwynn 在 Computex 2026 展的東西，表面上你看是「AI compute tray」，但其實重點根本不是 tray。重點是它在解一個很物理層的問題：AI accelerator 之間 Scale-Up 要怎麼互連，才不會被銅線、距離、功耗、散熱全部卡死。 它的做法就是 Co-Packaged Optics，CPO。簡單講，Broadcom 的 optical engine 不是放在外面交換器模組裡，而是直接跟 AI accelerator / GPU 包到同一個 substrate 上。每個 tray 裡面放兩顆 AI processor，然後光訊號直接從前面板一路進到 chip-level optical engine。這就不是「網路線插一插」那種概念了，這比較像你把高速公路出口直接開到工廠門口，貨車不用再繞市區。 前面板那邊有 detachable Fiber Array Unit，FAU，Broadcom 跟 Senko 的方案都有展示。黃色的 optical fiber 負責雙向流量，特別是 Scale-Up clustering 用的。這邊很關鍵，因為 Scale-Up 不是單純把機器連起來而已，它要的是 accelerator 之間像在同一個巨大系統裡面講話。你 latency 一高、bandwidth 一卡，整個 cluster 就開始搞笑。 然後中間那一排是 External Laser Source，ELS，也是 Broadcom 的。它透過 PM fiber，把光送到 optical engine，讓 silicon photonics 可以傳資料。也就是說，資料傳輸用的是光，但光源本身被拉出來集中管理。這有點像餐廳後場：火源不要每個爐子亂裝一套，集中供應，前面只管煮，效率跟維修都比較可控。 但 CPO 爽歸爽，問題馬上來：熱。 所以這個設計直接 100% liquid cooling，fanless。不是「GPU 水冷一下」而已，是整個 tray 裡面會發熱的東西都進水冷迴路：GPU、CPU、RAM、power module，甚至 external laser source 都吃冷板。它用 system manifold 把單一入口的冷卻液分配到各個熱源，避免某些元件先吃到已經被加熱過的水。這其實很狠，因為 AI rack 以後不是誰算力強就贏，是誰能把熱穩定帶走，誰才撐得住。 電力這邊目前 demo 是 50V input。但 Wiwynn 也在看 HVDC，例如 800V 或 +/-400V。這方向不意外，因為 rack power density 一直往上衝，低壓大電流會讓線材、銅損、配電全部變成災難。你不能一邊說我要 mega Scale-Up cluster，一邊還用傳統配電方式硬撐，最後不是效率血虧，就是機櫃裡面變烤箱。 整體拓撲也很清楚：這些 compute trays 塞進 dedicated compute rack，然後透過前面板 optical patch panel 接到多個 switch racks，組成大型 Scale-Up AI cluster。 所以這台東西真正想講的是： AI 伺服器已經不是「GPU 多放幾顆」的時代了。現在卡的是 L5 連接、L3 散熱、L6 封裝、L2 電力，全部一起卡。CPO 把光拉到 chip 旁邊，liquid cooling 把熱抽走，HVDC 則是下一步要解電力配送。 credit to : youtube.com/@casperharry
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@jassion767 虽然我也重胜宏，但不要这么水，你可以吹胜宏大板拿下一供了，大家只会觉得你疯了，不会觉得脑子不好使。长点脑子的都知道大板是rebin的必然选择。
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