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[CICD] : iluvatar adapt Iluvatar BI-V150 to the vLLM 0.24 line - #526

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xmhubj merged 6 commits into
flagos-ai:mainfrom
BrianPei:feat/iluvatar-vllm0.24
Sep 20, 2026
Merged

xmhubj merged 6 commits into
flagos-ai:mainfrom
BrianPei:feat/iluvatar-vllm0.24

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@hooray03

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Summary

Adapt Iluvatar BI-V150 CI support to the vLLM 0.24 line.

Changes

  • Add the Iluvatar platform and CI configuration.
  • Add an Iluvatar-specific Dockerfile based on the validated vLLM 0.24 CoreX image.
  • Register Iluvatar in the platform configuration and Docker build script.
  • Add BI-V150 test configuration through device_overrides.
  • Mount the required host CoreX driver libraries into the CI container.
  • Disable the multimodal processor cache for serving tests to avoid stale cross-request features.
  • Exclude CUDA graph tests that are not supported by the current CoreX runtime.

No operator or Python implementation files are changed.

Comment thread .github/configs/iluvatar.yml Outdated
# existing Qwen3.6 cases.
container_volumes:
- /dev:/dev
- /tmp:/tmp

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why mount /tmp from the host?

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I revalidated the container without the host /tmp bind mount. Device detection, tensor smoke, and plugin setup/import all passed, so the mount has been removed.

Comment thread .github/configs/iluvatar.yml Outdated
- /dev:/dev
- /tmp:/tmp
- /lib/modules:/lib/modules
- /sys:/sys

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why we mount /sys from the host?

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The redundant mount has been removed.

--shm-size=64g
--env GEMS_VENDOR=iluvatar
--env VLLM_PLUGINS=fl
--env CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7

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Is this necessary? can it be removed?

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This runner exposes 16 BI-V150 devices, while the current CI cases and TP8 validation are intended to use 8 devices. The variable limits the job to devices 0-7 and prevents it from consuming the full runner. I believe it should be kept unless device isolation is already enforced at the runner level.

tests:
e2e:
inference:
qwen3_6: ["27b_tp4_eager"]

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we need to test graph mode.

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Agreed

inference:
qwen3_6: ["27b_tp4_eager"]
serving:
qwen3_6: ["35b_a3b_tp4_eager"]

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we need to test graph mode.

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Agreed

# CoreX does not support torch.cuda graph capture. The two capture
# cases abort the shared pytest process and invalidate later results.
exclude:
- compilation/test_graph_capture.py

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need to confirm the conclusion.

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Updated

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why need to exclude those test cases?

@xmhubj

xmhubj commented Sep 16, 2026

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The iluvatar workflow didn't run. You may need to modify workflows/ci.yml to enable test on iluvatar.

@hooray03
hooray03 force-pushed the feat/iluvatar-vllm0.24 branch from 4eb7bbe to 6a5944e Compare September 16, 2026 07:37
Comment thread tests/platforms/iluvatar.yaml Outdated
# CoreX 4.5 returns ixErrorNotSupported from CUDA graph capture_begin.
# These modules require graph support during import or execution.
exclude:
- worker/test_model_runner.py

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why we need to exclude those test cases?

@hooray03

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/rerun-failed-ci

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🚀 Re-triggered failed CI jobs for this PR (requested by @hooray03).

@hooray03
hooray03 force-pushed the feat/iluvatar-vllm0.24 branch from 6a5944e to 5cdb292 Compare September 18, 2026 03:30
@xmhubj
xmhubj merged commit 8014b10 into flagos-ai:main Sep 20, 2026
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2 participants