[feat](eplb): support eplb on rocm platform

[PerryZhang01]

Purpose

Support EPLB feature on rocm platform.

Test Plan

export VLLM_USE_V1=1
export SAFETENSORS_FAST_GPU=1
export VLLM_ROCM_USE_AITER=1
export VLLM_ROCM_USE_AITER_MOE=1
export VLLM_USE_TRITON_FLASH_ATTN=0
export NCCL_DEBUG=WARN
export VLLM_RPC_TIMEOUT=1800000
export VLLM_ROCM_USE_AITER_MHA=0
export VLLM_ROCM_USE_TRITON_ROPE=1

export VLLM_ROCM_USE_AITER_FAKE_BALANCED_EXPERTS=1
export VLLM_ROCM_USE_AITER_FUSION_SHARED_EXPERTS=0

model_path="/data/pretrained-models/deepseek-ai/DeepSeek-V3"

# export AITER_REBUILD=1
# rm ~/.cache/vllm/torch_compile_cache/ -r
vllm serve $model_path \
--tensor-parallel-size 8 \
--max-num-batched-tokens 32768 \
--trust-remote-code \
--no-enable-prefix-caching \
--disable-log-requests \
--compilation-config '{"cudagraph_mode": "FULL_AND_PIECEWISE"}' \
--gpu_memory_utilization 0.9 \
--block-size 1 \
--enable-expert-parallel \
--enable-eplb \
--num-redundant-experts 8 \
--eplb-log-balancedness \
--eplb-window-size 3000 \
--eplb-step-interval 1000 \

model_path="/data/pretrained-models/deepseek-ai/DeepSeek-V3"

# python -m vllm.benchmarks.serve
# vllm bench serve \
python -m vllm.entrypoints.cli.main bench serve \
    --host localhost \
    --port 8000 \
    --model ${model_path} \
    --dataset-name random \
    --random-input-len 3584 \
    --random-output-len 1024 \
    --max-concurrency 64 \
    --num-prompts 64 \
    --seed 123 \
    --percentile-metrics ttft,tpot,itl,e2el \
    --ignore-eos \

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.
• 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.