Fix scheduler yield on arm

[wangxiyuan]

Purpose

For Arm systems, os.sched_yield does not take effect, causing the GIL (Global Interpreter Lock) to remain unrelinquished and resulting in CPU bound issues. we should making the process execute time.sleep(0) instead to release the GIL.

Test Plan

Test Result

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• The purpose of the PR, such as "Fix some issue (link existing issues this PR will resolve)".
• The test plan, such as providing test command.
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Note

Ensures polling yields the GIL on ARM.

• Update vllm/distributed/utils.py: USE_SCHED_YIELD now also checks Platform.get_cpu_architecture() and disables os.sched_yield on ARM, falling back to time.sleep(0)
• Add imports for CpuArchEnum and Platform; update comments accordingly

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[gemini-code-assist]

Code Review

This pull request addresses a critical issue on ARM systems where os.sched_yield fails to relinquish the Global Interpreter Lock (GIL), leading to CPU-bound performance problems. The change correctly modifies the USE_SCHED_YIELD logic to fall back to time.sleep(0) on ARM architectures, ensuring proper GIL release and improving system responsiveness. The addition of the CpuArchEnum and Platform imports is appropriate for this detection. The code is clear and directly resolves the described problem.

[robertgshaw2-redhat]

Does this fix: #29369?

[heheda12345]

@tlrmchlsmth can you check this on gb200?

[tlrmchlsmth]

I or someone on my team will look into this, but I'm not sure what we should look out for.

What should we expect to see if the os.sched_yield isn't taking effect?

[amohoste]

We encountered a similar issue running P2P KV Cache sharing through vllm-ascend + LMCache-Ascend on ARM, Python 3.11.13. In this scenario, there is an async transfer function to load prefix caches while the main thread continues to do other work. When os.sched_yield is used, the async transfer function is typically starved for 100ms+ before the transfer operations are submitted to the device.

When applying the patch to use time.sleep(0) instead, the async_batched_write function to submit the transfer operations to the device completes within 1.2ms as expected

[wangxiyuan]

@heheda12345 @robertgshaw2-redhat @tlrmchlsmth Sorry for late reply. When running vLLM with world size >1 on arm machine, we can see that the worker process always use CPU 100% after the serve start.

Reproduce command:
vllm serve Qwen/Qwen3-0.6B --tensor-parallel-size 2.

Then the top result is:

I think this can be reproduced on GH200 as well.

[wangxiyuan]

@tlrmchlsmth would you mind take a look at this one? Thanks.