SA260324R-0127::SPLIT01

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① SA Source

Context Before

Speculative Decoding

A different way LPUs could improve decode phase latencies is by accelerating a speculative decoding setup, where we deploy draft models or Multi-Token Prediction (MTP) layers onto LPUs.

Evidence

For a decoding step of context N tokens, adding k additional tokens during forward pass (a warm prefill of k new tokens) marginally increases the latency when k << N. Using this property, speculative decoding uses a small draft model or MTP layers to predict k new tokens, saving time since small models have lower latency per decode step. To verify the draft tokens, the main model only needs one warm prefill of k new tokens, at the latency cost of roughly a single decode step. Speculative decoding usually boosts output token per decode step by 1.5 to 2 tokens, depending on the draft model / MTP accuracy. With its low latency capabilities, LPUs can further increase the latency savings and improve throughput.

Context After

image

Source: SemiAnalysis

② Atomic Claim

憑藉低 latency 能力,LPU 可進一步提高 latency savings。

  • Epistemic Mode: ASSERTED
  • Mapping Status: COMPLETE

③ Semantic Frame

{
  "attribute": "LATENCY_SAVINGS_EFFECT",
  "context_nodes": [],
  "entity": {
    "id": "04_knowledge_base/Groq LPU",
    "label": "LPU"
  },
  "frame_type": "ATTRIBUTE",
  "qualifiers": {
    "condition_text": "with low latency capabilities",
    "numeric_mentions": [],
    "temporal_mentions": []
  },
  "value": {
    "numeric_mentions": [],
    "value_text": "further increase latency savings"
  }
}

④ Canonical Entity Mapping

RoleSurface LabelCanonical Target
entityLPU04_knowledge_base/Groq LPU

⑤ V2 Draft(需要修正時直接編輯)

Inline repair

只編輯以下三個 Draft 區塊。完成後將 review_action 設為 REQUEST_REPAIR,再手動執行 Repair Preview。
執行腳本前,Draft 不會寫入 Claim Store 或 Graph。

V2 Atomic Claim Draft

憑藉低 latency 能力,LPU 可進一步提高 latency savings。

V2 Semantic Frame Draft

{
  "attribute": "LATENCY_SAVINGS_EFFECT",
  "context_nodes": [],
  "entity": {
    "id": "04_knowledge_base/Groq LPU",
    "label": "LPU"
  },
  "frame_type": "ATTRIBUTE",
  "qualifiers": {
    "condition_text": "with low latency capabilities",
    "numeric_mentions": [],
    "temporal_mentions": []
  },
  "value": {
    "numeric_mentions": [],
    "value_text": "further increase latency savings"
  }
}

V2 Revision Metadata Draft

{
  "epistemic_mode": "ASSERTED",
  "mapping_status": "COMPLETE"
}

⑥ 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。