3da2ba22eb
### What this PR does / why we need it? - Keeps enable_cpu_binding default on, but skips binding on non‑ARM CPUs inside bind_cpus, with a clear log. - Uses a table-driven binding policy: A3 uses NUMA‑balanced binding; other device types use NUMA‑affinity binding. - Updates docs to reflect the exact behavior and adds/updates unit tests for the new logic. ### Does this PR introduce _any_ user-facing change? - Yes. CPU binding is now enabled by default via additional_config, and documented in the user guide. - CPU binding behavior differs by device type (A3 vs. others). ### How was this patch tested? Added/updated unit tests: test_cpu_binding.py 1. test_binding_mode_table covers A2 vs A3 binding mode mapping. 2. test_build_cpu_pools_fallback_to_numa_balanced covers fallback when affinity info is missing. 3. TestBindingSwitch.test_is_arm_cpu covers ARM/x86/unknown arch detection. 4. test_bind_cpus_skip_non_arm covers non‑ARM skip path in bind_cpus. test_worker_v1.py 1. Updated mocks for enable_cpu_binding default True to align with new config default. - vLLM version: v0.14.1 - vLLM main: d7de043 --------- Signed-off-by: chenchuw886 <chenchuw@huawei.com> Co-authored-by: chenchuw886 <chenchuw@huawei.com>
40 lines
652 B
Plaintext
40 lines
652 B
Plaintext
# Should be mirrored in pyporject.toml
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cmake>=3.26
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decorator
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einops
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numpy<2.0.0
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packaging
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pip
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pybind11
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pyyaml
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scipy
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pandas
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psutil
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setuptools>=64
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setuptools-scm>=8
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torch==2.9.0
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torchvision
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torchaudio
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wheel
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xgrammar>=0.1.30
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pandas-stubs
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opencv-python-headless<=4.11.0.86 # Required to avoid numpy version conflict with vllm
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compressed_tensors>=0.11.0
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# requirements for disaggregated prefill
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msgpack
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quart
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# Required for N-gram speculative decoding
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numba
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# Install torch_npu
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#--pre
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#--extra-index-url https://mirrors.huaweicloud.com/ascend/repos/pypi
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torch-npu==2.9.0
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arctic-inference==0.1.1
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transformers>=4.57.4
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fastapi<0.124.0
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triton-ascend==3.2.0
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