VR2-0678
① SA Source
- Source: 開啟完整 SA 文章
- Section:
Ethernet-Based Cluster Deployments - Line hint:
847
Context Before
The last factor in favor of adoption of CPO that we would like to mention is the fact that some of Nvidia’s CPO switch SKUs contain the integrated fiber shuffle and can simplify the installation and maintenance of multi-plane network architectures. Recall that the SN6800 contains four Switch ASICs in a multi-plane configuration connected to ports via an integrated fiber shuffle, delivering 409.6T aggregate bandwidth, while the SN6810 uses one Switch ASIC, but without any integrated fiber shuffle, to deliver 102.4T aggregate bandwidth.
But first, we will explain why we think multi-plane networking architectures are here to stay as an important preface.
Evidence
Large-scale cluster deployments where cluster sizes exceed 100k GPUs typically utilize multi-plane network architectures because single-plane network architectures do not have enough logical ports at current switch generations to support larger networks without resorting to a high number of switch layers of 3 or more layers
Context After
Recall from above that a Vera Rubin NVL72 cluster built with Q3400-X800 switches at 1.6T logical ports per GPU cannot scale beyond the maximum cluster size of 93,312 GPUs. Even if future switch generations continue to double the maximum possible switching capacity per switch box, the per GPU bandwidth is also expected to double, which means that the effective logical port count in a cluster network is unlikely to change.
What this means is that deployment of large-scale GPU clusters will continue to require multi-plane network architectures. Do note however that multi-plane networking architectures are not limited by size and we have also seen NVIDIA reference architecture deployments with multi-plane clusters that are significantly below 100k GPUs each.
② Atomic Claim
超過 10 萬顆 GPUs 的 large-scale cluster 通常採 multi-plane network architecture，因現有 switch 世代的 single-plane network logical port 數量不足，若不用 multi-plane，就必須採 3 層以上的高 layer 數 switch network。
- Epistemic Mode:
ASSERTED - Mapping Status:
PARTIAL
③ Semantic Frame
{
"attribute": "LAYER_COUNT",
"context_nodes": [],
"entity": {
"id": "04_knowledge_base/GPU",
"label": "GPUs"
},
"frame_type": "ATTRIBUTE",
"qualifiers": {
"condition_text": null,
"numeric_mentions": [
"10",
"3"
],
"temporal_mentions": []
},
"value": {
"numeric_mentions": [
"10",
"3"
],
"value_text": "超過 10 萬顆 GPUs 的 large-scale cluster 通常採 multi-plane network architecture，因現有 switch 世代的 single-plane network logical port 數量不足，若不用 multi-plane，就必須採 3 層以上的高 layer 數 switch network。"
}
}④ Canonical Entity Mapping
| Role | Surface Label | Canonical Target |
|---|---|---|
| entity | GPUs | GPU |
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。