NIEK2-0186
① SA Source
- Source: 開啟完整 SA 文章
- Section:
Nvidia’s CPO Roadmap - Line hint:
207
Context Before
Lastly, there is the inter-rack C2C. Each LPU has 4x100G lanes that go to the OSFP cages to connect LPUs across 4 racks. There are various configurations that can be used for this inter-rack scale up. One option is 4x100G from each LPU going to one OSFP cage, each OSFP escaping 800G of C2C from 2 LPUs. However, for greater fan out the preferred configuration seems to be each 100G lane from the LPU going to 4 individual cages, with each cage escaping 800G of C2C from 8 LPUs. In terms of how the racks are networked together it appears to be a daisy chain configuration, with each Node0 connected to 2 other Node 0. This can all be achieved within the reach of 100G AECs, though optics can be used if necessary.
Nvidia’s CPO Roadmap
Evidence
Though many had their hopes up for CPO to be used for scale-up within the rack for Rubin Ultra Kyber, Nvidia’s focus was instead on using CPO to enable larger world size compute systems
Context After
Source: SemiAnalysis AI Networking Model ↗, Nvidia
② Atomic Claim
許多人原先期待 CPO 會用在 Rubin Ultra Kyber 的機櫃內 scale-up，但 Nvidia 的重點其實是利用 CPO 建構更大的 world-size 運算系統。
- Epistemic Mode:
ASSERTED - Mapping Status:
PARTIAL
③ Semantic Frame
{
"attribute": "SCALABILITY",
"context_nodes": [
{
"id": "04_knowledge_base/Rubin Ultra",
"label": "Rubin Ultra"
},
{
"id": "04_knowledge_base/NVIDIA Kyber Rack",
"label": "Kyber"
},
{
"id": "02_companies/NVDA",
"label": "Nvidia"
}
],
"entity": {
"id": "04_knowledge_base/CPO",
"label": "CPO"
},
"frame_type": "ATTRIBUTE",
"qualifiers": {
"condition_text": null,
"numeric_mentions": [],
"temporal_mentions": []
},
"value": {
"numeric_mentions": [],
"value_text": "許多人原先期待 CPO 會用在 Rubin Ultra Kyber 的機櫃內 scale-up，但 Nvidia 的重點其實是利用 CPO 建構更大的 world-size 運算系統。"
}
}④ Canonical Entity Mapping
| Role | Surface Label | Canonical Target |
|---|---|---|
| entity | CPO | CPO |
| context_0 | Rubin Ultra | 04_knowledge_base/Rubin Ultra |
| context_1 | Kyber | 04_knowledge_base/NVIDIA Kyber Rack |
| context_2 | Nvidia | NVDA |
⑤ Human Review
請在 Properties 逐項確認：
- 原文 → Atomic Claim 是否忠實
- Atomic Claim → Semantic Frame 是否忠實
- Canonical Entity mapping 是否正確
- Epistemic mode 是否保留原文語氣
- 最後選擇
review_action
Review state
Markdown 內文不是正式 approval。只有 Apply bridge 寫入的 Decision Ledger event 才是正式決策。