Fix multiprocessing start method for CUDA compatibility in LMCache kv_cache_sharing_lmcache_v1.py

[usberkeley]

Purpose

1）Fix #29591
2）delete lmcache/disagg_prefill_lmcache_v0.py：vLLM V0 architecture has already been deprecated.

When using CUDA with multiprocessing, Python's default multiprocessing start method (fork) can cause CUDA context initialization failures in child processes, leading to errors.

Test Plan

None

Test Result

None

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Essential Elements of an Effective PR Description Checklist

• 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.
• The test results, such as pasting the results comparison before and after, or e2e results
• (Optional) The necessary documentation update, such as updating supported_models.md and examples for a new model.
• (Optional) Release notes update. If your change is user facing, please update the release notes draft in the Google Doc.

[mergify]

Documentation preview: https://vllm--29592.org.readthedocs.build/en/29592/

[gemini-code-assist]

Code Review

This pull request correctly addresses a CUDA compatibility issue in the kv_cache_sharing_lmcache_v1.py example. By setting the multiprocessing start method to 'spawn', it prevents potential CUDA context initialization failures in child processes that can occur with the default 'fork' method. The implementation is sound, using multiprocessing.set_start_method('spawn', force=True) to ensure the correct context is established, which is a robust approach for a standalone example script. The changes are well-justified and improve the reliability of the example in CUDA environments. The code looks good, and I have no high or critical severity comments.

[usberkeley]

Hi @YaoJiayi

Could you please take a look and review when you have time? Thank you very much!

[LucasWilkinson]

cc @NickLucche @njhill (please redirect if you are not the right person; not sure who the LMCache owner is)