[main][Prefill Perf] Optimize Quantized MoE Performance by Reducing All2All Communication

[SlightwindSec]

This PR significantly optimizes performance for quantized Mixture of Experts (MoE) layers by changing the order of quantization and communication operations.

In the previous implementation, the all2all operation was performed on unquantized hidden_states (in FP16/BF16) before quantization, resulting in substantial communication overhead. By performing quantization on each EP rank first and then sending the much smaller quantized data, we reduce the communication volume by nearly 50%.

Additionally, this PR includes a minor optimization to cast int inputs to float for the argsort operation, forcing it to run on a faster NPU core instead of the AICPU.

These changes lead to a clear and significant performance gain in MoE quantization scenarios.

• vLLM version: v0.10.0
• vLLM main: vllm-project/vllm@7175817

[github-actions]

👋 Hi! Thank you for contributing to the vLLM Ascend project. The following points will speed up your PR merge:‌‌

• A PR should do only one thing, smaller PRs enable faster reviews.
• Every PR should include unit tests and end-to-end tests ‌to ensure it works and is not broken by other future PRs.
• Write the commit message by fulfilling the PR description to help reviewer and future developers understand.

If CI fails, you can run linting and testing checks locally according Contributing and Testing.

[codecov]

Codecov Report

❌ Patch coverage is 96.87500% with 2 lines in your changes missing coverage. Please review.
✅ Project coverage is 76.72%. Comparing base (ad366bf) to head (f55f351).
⚠️ Report is 615 commits behind head on main.

Files with missing lines	Patch %	Lines
vllm_ascend/quantization/w8a8_dynamic.py	93.75%	2 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #2195      +/-   ##
==========================================
+ Coverage   76.41%   76.72%   +0.30%     
==========================================
  Files         113      111       -2     
  Lines       12553    12516      -37     
==========================================
+ Hits         9593     9603      +10     
+ Misses       2960     2913      -47     

Flag	Coverage Δ
unittests	76.72% <96.87%> (+0.30%)	⬆️

Flags with carried forward coverage won't be shown. Click here to find out more.

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

🚀 New features to boost your workflow:

• ❄️ Test Analytics: Detect flaky tests, report on failures, and find test suite problems.