NIEK2-0123
① SA Source
- Source: 開啟完整 SA 文章
- Section:
GPU and LPU Integration: Attention FFN Disaggregation (AFD) - Line hint:
119
Context Before
Source: SemiAnalysis
Evidence
In addition to splitting batches into micro-batches and computation pipelining like standard pipeline parallelism, the tokens dispatched to the LPUs are combined back to the source GPUs, so they ping pong between the GPUs and the LPUs
Context After
Source: MegaScale-Infer
② Atomic Claim
除了像標準 pipeline parallelism 一樣把 batch 切成 micro-batches 並進行運算 pipeline 外，送往 LPU 的 token 還會再 combine 回來源 GPUs，使資料在 GPUs 與 LPU 之間來回傳遞。
- Epistemic Mode:
ASSERTED - Mapping Status:
PARTIAL
③ Semantic Frame
{
"attribute": "UNSPECIFIED_ATTRIBUTE",
"context_nodes": [
{
"id": "04_knowledge_base/GPU",
"label": "GPUs"
}
],
"entity": {
"id": "04_knowledge_base/Pipeline parallelism",
"label": "pipeline parallelism"
},
"frame_type": "ATTRIBUTE",
"qualifiers": {
"condition_text": null,
"numeric_mentions": [],
"temporal_mentions": []
},
"value": {
"numeric_mentions": [],
"value_text": "除了像標準 pipeline parallelism 一樣把 batch 切成 micro-batches 並進行運算 pipeline 外，送往 LPU 的 token 還會再 combine 回來源 GPUs，使資料在 GPUs 與 LPU 之間來回傳遞。"
}
}④ Canonical Entity Mapping
| Role | Surface Label | Canonical Target |
|---|---|---|
| entity | pipeline parallelism | 04_knowledge_base/Pipeline parallelism |
| context_0 | 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。