7f73c28a24
### What this PR does / why we need it?
This pull request mainly do the following things:
1. Add a doc for multi-node CI, The main content is the mechanism
principle and how to contribute
2. Simplify the config yaml for more developer-friendly
3. Optimized the mooncake installation script to prevent accidental
failures during installation
4. Fix the workflow to ensure the kubernetes can be apply correctly
5. Add Qwen3-235B-W8A8 disaggregated_prefill test
6. Add GLM-4.5 multi dp test
7. Add 2p1d 4nodes disaggregated_prefill test
8. Refactor nightly tests
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.11.0rc3
- vLLM main:
17c540a993
---------
Signed-off-by: wangli <wangli858794774@gmail.com>
69 lines
1.8 KiB
YAML
69 lines
1.8 KiB
YAML
test_name: "test Qwen3-235B-A22B multi-dp"
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model: "Qwen/Qwen3-235B-A22B"
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num_nodes: 2
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npu_per_node: 16
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env_common:
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VLLM_USE_MODELSCOPE: true
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OMP_PROC_BIND: false
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OMP_NUM_THREADS: 100
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HCCL_BUFFSIZE: 1024
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SERVER_PORT: 8080
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deployment:
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-
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server_cmd: >
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vllm serve "Qwen/Qwen3-235B-A22B"
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--host 0.0.0.0
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--port $SERVER_PORT
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--data-parallel-size 4
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--data-parallel-size-local 2
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--data-parallel-address $LOCAL_IP
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--data-parallel-rpc-port 13389
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--tensor-parallel-size 8
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--seed 1024
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--enable-expert-parallel
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--max-num-seqs 16
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--max-model-len 8192
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--max-num-batched-tokens 8192
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--trust-remote-code
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--no-enable-prefix-caching
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--gpu-memory-utilization 0.9
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-
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server_cmd: >
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vllm serve "Qwen/Qwen3-235B-A22B"
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--headless
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--data-parallel-size 4
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--data-parallel-size-local 2
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--data-parallel-start-rank 2
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--data-parallel-address $MASTER_IP
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--data-parallel-rpc-port 13389
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--tensor-parallel-size 8
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--seed 1024
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--max-num-seqs 16
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--max-model-len 8192
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--max-num-batched-tokens 8192
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--enable-expert-parallel
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--trust-remote-code
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--no-enable-prefix-caching
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--gpu-memory-utilization 0.9
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benchmarks:
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perf:
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case_type: performance
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dataset_path: vllm-ascend/GSM8K-in3500-bs400
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request_conf: vllm_api_stream_chat
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dataset_conf: gsm8k/gsm8k_gen_0_shot_cot_str_perf
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num_prompts: 1
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max_out_len: 2
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batch_size: 1
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baseline: 5
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threshold: 0.97
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acc:
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case_type: accuracy
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dataset_path: vllm-ascend/AIME2024
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request_conf: vllm_api_general_chat
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dataset_conf: aime2024/aime2024_gen_0_shot_chat_prompt
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max_out_len: 10
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batch_size: 32
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baseline: 1
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threshold: 1
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