clm_4dc9e2402e7340ffb3821ef4b4aa8cd3_r1

NIEK2-0063

① SA Source

• Source: 開啟完整 SA 文章
• Section: SRAM and Memory Hierarchy
• Line hint: 57

Context Before

SRAM and Memory Hierarchy

We have written about the role of SRAM in the memory hierarchy, but the quick recap is that SRAM is very fast (low latency and high bandwidth) but this comes at the expense of density and therefore cost.

Evidence

This is why Nvidia has decided to combine these architectures to get the best of both worlds: accelerate parts of decode that are more latency sensitive

Context After

Source: SemiAnalysis

② Atomic Claim

因此 Nvidia 決定結合兩種架構，以加速 decode 中對延遲較敏感的部分。

• Epistemic Mode: ASSERTED
• Mapping Status: COMPLETE

③ Semantic Frame

{
  "attribute": "LATENCY",
  "context_nodes": [
    {
      "id": "04_knowledge_base/Decode",
      "label": "decode"
    }
  ],
  "entity": {
    "id": "02_companies/NVDA",
    "label": "Nvidia"
  },
  "frame_type": "ATTRIBUTE",
  "qualifiers": {
    "condition_text": null,
    "numeric_mentions": [],
    "temporal_mentions": []
  },
  "value": {
    "numeric_mentions": [],
    "value_text": "因此 Nvidia 決定結合兩種架構，以加速 decode 中對延遲較敏感的部分。"
  }
}

④ Canonical Entity Mapping

Role	Surface Label	Canonical Target
entity	Nvidia	NVDA
context_0	decode	Decode

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。