IX2-0530

① SA Source

Context Before

We have made a few core architectural changes to the InferenceX repository to make it easier to understand and reproduce benchmarks. Additionally, we have fully subscribed to AI usage to maximize productivity and increase developer velocity.

Core Changes Since InferenceXv1

Evidence

However, as we added more chips, disaggregated prefill, wide EP

Context After

We now trigger sweeps based on additions to a changelog at the root of the repo. When a developer makes a performance-impacting change to a given config, they add an entry to the changelog listing the affected config along with a brief description of the change. All configs are defined in a master configuration YAML file , which serves as the stateful representation of every data point to be swept, including core settings like ISL/OSL, EP, TP, DP, MTP, and so on. When a PR containing a changelog addition is merged, a workflow parses the referenced config keys, pulls the corresponding sweep definitions from the master config, and fans them out as individual GitHub Actions jobs. The jobs collect all data points for the full sweep and upload the results as artifacts.

Below is a high-level diagram of how InferenceX launches jobs.

② Atomic Claim

隨著更多晶片、disaggregated prefillwide EP 被加入測試範圍,sweep 的複雜度提高。

  • Epistemic Mode: ASSERTED
  • Mapping Status: COMPLETE

③ Semantic Frame

{
  "attribute": "LIFECYCLE_STATUS",
  "context_nodes": [
    {
      "id": "04_knowledge_base/Expert Parallelism",
      "label": "wide EP"
    }
  ],
  "entity": {
    "id": "04_knowledge_base/Disaggregated prefill",
    "label": "disaggregated prefill"
  },
  "frame_type": "ATTRIBUTE",
  "qualifiers": {
    "condition_text": null,
    "numeric_mentions": [],
    "temporal_mentions": []
  },
  "value": {
    "numeric_mentions": [],
    "value_text": "隨著更多晶片、disaggregated prefill 與 wide EP 被加入測試範圍,sweep 的複雜度提高。"
  }
}

④ Canonical Entity Mapping

RoleSurface LabelCanonical Target
entitydisaggregated prefill04_knowledge_base/Disaggregated prefill
context_0wide EP04_knowledge_base/Expert Parallelism

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。