VR2R-0095
① SA Source
- Source: 開啟完整 SA 文章
- Section:
Rubin - Line hint:
81
Context Before
This means the sparser the workload, the closer the performance will be to the 50 PFLOPS marketed peak performance. NVIDIA thus brands the 50 PFLOPS figure as FP4 Inference while the 35 PFLOPS FP4 Training number is for dense workloads. As accuracy is preserved, this allows the marketing team to claim 5x FLOPs for Rubin over GB200, comparing 50 PFLOPS dynamically compressed FP4 to 10 PFLOPS dense FP4. Whether actual GEMM performance reaches 50 PFLOPS depends on how many zeros are in the tensor.
Evidence
The more zeros, the closer it can reach.
Context After
The less zeros in the tensor, the lower the speedup. Overall, we expect to see much greater traction for Rubin’s adaptive sparsity compression as opposed to structured sparsity thanks to the automatic implementation.
② Atomic Claim
Zeros 越多，performance 就越能接近該上限。
- Epistemic Mode:
ASSERTED - Mapping Status:
PARTIAL
③ Semantic Frame
{
"frame_type": "CLAIM_ONLY",
"qualifiers": {
"condition_text": "承接 VR2R-0094",
"numeric_mentions": [],
"temporal_mentions": []
},
"reason": "PRONOUN_REFERENCES_PRIOR_50_PFLOPS_CLAIM",
"statement": "Zeros 越多，performance 越能接近前述 50 PFLOPS。"
}④ Canonical Entity Mapping
| Role | Surface Label | Canonical Target |
|---|---|---|
| — | — | — |
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。