IX2-0460
① SA Source
- Source: 開啟完整 SA 文章
- Section:
Disaggregated Prefill - Line hint:
672
Context Before
Source: DistServe ↗
Disaggregation also enables independent scaling and optimization of each phase. With separate nodes, each phase can be tuned independently: different parallelism strategies, different batch sizes, and different memory allocation ratios. The ratio of prefill to decode nodes can also be matched to the workload’s input-output length ratio. For instance, prefill-dominated workloads (long input, short output e.g., summarization, RAG, agentic coding with large context windows) allocate more prefill instances. Decode-dominated workloads (short input, long output e.g., chain-of-thought reasoning, long-form generation) allocate more decode instances. Workloads with high cache hit rates also tend toward more decode, since reused KV cache entries from shared system prompts or multi-turn conversation history skip prefill entirely.
Evidence
The key cost of disaggregation is KV cache transfer
Context After
② Atomic Claim
Disaggregation 的主要成本是 KV cache transfer。
- Epistemic Mode:
ASSERTED - Mapping Status:
COMPLETE
③ Semantic Frame
{
"attribute": "COST",
"context_nodes": [],
"entity": {
"id": "04_knowledge_base/KV cache",
"label": "KV cache"
},
"frame_type": "ATTRIBUTE",
"qualifiers": {
"condition_text": null,
"numeric_mentions": [],
"temporal_mentions": []
},
"value": {
"numeric_mentions": [],
"value_text": "Disaggregation 的主要成本是 KV cache transfer。"
}
}④ Canonical Entity Mapping
| Role | Surface Label | Canonical Target |
|---|---|---|
| entity | KV cache | 04_knowledge_base/KV cache |
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。