(APIServer pid=2634246) INFO 07-12 14:47:36 [api_utils.py:339] 
(APIServer pid=2634246) INFO 07-12 14:47:36 [api_utils.py:339]        █     █     █▄   ▄█
(APIServer pid=2634246) INFO 07-12 14:47:36 [api_utils.py:339]  ▄▄ ▄█ █     █     █ ▀▄▀ █  version 0.24.1.dev3+g668cfb7e2
(APIServer pid=2634246) INFO 07-12 14:47:36 [api_utils.py:339]   █▄█▀ █     █     █     █  model   /home/admin/cpfs/wjh/models/Qwen/Qwen3-30B-A3B
(APIServer pid=2634246) INFO 07-12 14:47:36 [api_utils.py:339]    ▀▀  ▀▀▀▀▀ ▀▀▀▀▀ ▀     ▀
(APIServer pid=2634246) INFO 07-12 14:47:36 [api_utils.py:339] 
(APIServer pid=2634246) INFO 07-12 14:47:36 [api_utils.py:273] non-default args: {'model_tag': '/home/admin/cpfs/wjh/models/Qwen/Qwen3-30B-A3B', 'host': '127.0.0.1', 'port': 8501, 'model': '/home/admin/cpfs/wjh/models/Qwen/Qwen3-30B-A3B', 'served_model_name': ['qwen3-30b-a3b-community'], 'max_num_batched_tokens': 8192, 'max_num_seqs': 16, 'shutdown_timeout': 120}
(APIServer pid=2634246) INFO 07-12 14:47:48 [model.py:598] Resolved architecture: Qwen3MoeForCausalLM
(APIServer pid=2634246) INFO 07-12 14:47:48 [model.py:1725] Using max model len 40960
(APIServer pid=2634246) INFO 07-12 14:47:48 [scheduler.py:252] Chunked prefill is enabled with max_num_batched_tokens=8192.
(APIServer pid=2634246) INFO 07-12 14:47:48 [vllm.py:1006] Asynchronous scheduling is enabled.
(APIServer pid=2634246) INFO 07-12 14:47:48 [kernel.py:276] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native'])
(EngineCore pid=2635032) INFO 07-12 14:47:59 [core.py:114] Initializing a V1 LLM engine (v0.24.1.dev3+g668cfb7e2) with config: model='/home/admin/cpfs/wjh/models/Qwen/Qwen3-30B-A3B', speculative_config=None, tokenizer='/home/admin/cpfs/wjh/models/Qwen/Qwen3-30B-A3B', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=False, dtype=torch.bfloat16, max_seq_len=40960, download_dir=None, load_format=auto, tensor_parallel_size=1, pipeline_parallel_size=1, data_parallel_size=1, decode_context_parallel_size=1, dcp_comm_backend=ag_rs, disable_custom_all_reduce=False, quantization=None, quantization_config=None, enforce_eager=False, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=cuda, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_any_whitespace=False, disable_additional_properties=False, reasoning_parser='', reasoning_parser_plugin='', enable_in_reasoning=False), observability_config=ObservabilityConfig(show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None, kv_cache_metrics=False, kv_cache_metrics_sample=0.01, cudagraph_metrics=False, enable_layerwise_nvtx_tracing=False, enable_mfu_metrics=False, enable_mm_processor_stats=False, enable_logging_iteration_details=False, jit_monitor_verbose=False), seed=0, served_model_name=qwen3-30b-a3b-community, enable_prefix_caching=True, enable_chunked_prefill=True, pooler_config=None, compilation_config={'mode': <CompilationMode.VLLM_COMPILE: 3>, 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['none'], 'ir_enable_torch_wrap': True, 'splitting_ops': ['vllm::unified_attention_with_output', 'vllm::unified_mla_attention_with_output', 'vllm::mamba_mixer2', 'vllm::mamba_mixer', 'vllm::short_conv', 'vllm::linear_attention', 'vllm::plamo2_mamba_mixer', 'vllm::qwen_gdn_attention_core', 'vllm::gdn_attention_core_xpu', 'vllm::olmo_hybrid_gdn_full_forward', 'vllm::kda_attention', 'vllm::sparse_attn_indexer', 'vllm::rocm_aiter_sparse_attn_indexer', 'vllm::deepseek_v4_attention', 'vllm::unified_kv_cache_update', 'vllm::unified_mla_kv_cache_update'], 'compile_mm_encoder': False, 'cudagraph_mm_encoder': False, 'encoder_cudagraph_token_budgets': [], 'encoder_cudagraph_max_vision_items_per_batch': 0, 'encoder_cudagraph_max_frames_per_batch': None, 'compile_sizes': [], 'compile_ranges_endpoints': [8192], 'inductor_compile_config': {'enable_auto_functionalized_v2': False, 'size_asserts': False, 'alignment_asserts': False, 'scalar_asserts': False, 'combo_kernels': True, 'benchmark_combo_kernel': True}, 'inductor_passes': {}, 'cudagraph_mode': <CUDAGraphMode.FULL_AND_PIECEWISE: (2, 1)>, 'cudagraph_num_of_warmups': 1, 'cudagraph_capture_sizes': [1, 2, 4, 8, 16, 24, 32], 'cudagraph_copy_inputs': False, 'cudagraph_specialize_lora': True, 'use_inductor_graph_partition': False, 'pass_config': {'fuse_norm_quant': False, 'fuse_act_quant': False, 'fuse_attn_quant': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False, 'fuse_rope_kvcache_cat_mla': False, 'fuse_act_padding': False}, 'max_cudagraph_capture_size': 32, 'dynamic_shapes_config': {'type': <DynamicShapesType.BACKED: 'backed'>, 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': False, 'static_all_moe_layers': []}, kernel_config=KernelConfig(ir_op_priority=IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']), enable_flashinfer_autotune=True, moe_backend='auto', linear_backend='auto')
(EngineCore pid=2635032) INFO 07-12 14:48:01 [parallel_state.py:1588] world_size=1 rank=0 local_rank=0 distributed_init_method=tcp://172.27.132.244:56823 backend=nccl
(EngineCore pid=2635032) INFO 07-12 14:48:01 [parallel_state.py:1923] rank 0 in world size 1 is assigned as DP rank 0, PP rank 0, PCP rank 0, TP rank 0, EP rank 0, EPLB rank N/A
(EngineCore pid=2635032) INFO 07-12 14:48:03 [topk_topp_sampler.py:55] Using FlashInfer for top-p & top-k sampling.
(EngineCore pid=2635032) INFO 07-12 14:48:03 [gpu_model_runner.py:5164] Starting to load model /home/admin/cpfs/wjh/models/Qwen/Qwen3-30B-A3B...
(EngineCore pid=2635032) INFO 07-12 14:48:04 [cuda.py:480] Using FLASH_ATTN attention backend out of potential backends: ['FLASH_ATTN', 'FLASHINFER', 'TRITON_ATTN', 'FLEX_ATTENTION'].
(EngineCore pid=2635032) INFO 07-12 14:48:04 [flash_attn.py:670] Using FlashAttention version 3
(EngineCore pid=2635032) INFO 07-12 14:48:04 [unquantized.py:247] Using TRITON Unquantized MoE backend out of potential backends: ['TRITON', 'BATCHED_TRITON', 'FlashInfer TRTLLM', 'FlashInfer CUTLASS'].
(EngineCore pid=2635032) INFO 07-12 14:48:04 [weight_utils.py:849] Filesystem type for checkpoints: FUSE.ALIYUN-ALINAS-EFC. Checkpoint size: 56.87 GiB. Available RAM: 1284.19 GiB.
(EngineCore pid=2635032) INFO 07-12 14:48:04 [weight_utils.py:872] Auto-prefetch is disabled because the filesystem (FUSE.ALIYUN-ALINAS-EFC) is not a recognized network FS (NFS/Lustre). If you want to force prefetching, start vLLM with --safetensors-load-strategy=prefetch.
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(EngineCore pid=2635032) INFO 07-12 14:48:19 [default_loader.py:430] Loading weights took 14.76 seconds
(EngineCore pid=2635032) INFO 07-12 14:48:19 [unquantized.py:312] Using MoEPrepareAndFinalizeNoDPEPModular
(EngineCore pid=2635032) INFO 07-12 14:48:20 [gpu_model_runner.py:5259] Model loading took 56.88 GiB memory and 15.453205 seconds
(EngineCore pid=2635032) INFO 07-12 14:48:29 [backends.py:1089] Using cache directory: /home/admin/cpfs/wjh/.cache/vllm/torch_compile_cache/f4a50989f8/rank_0_0/backbone for vLLM's torch.compile
(EngineCore pid=2635032) INFO 07-12 14:48:29 [backends.py:1148] Dynamo bytecode transform time: 9.28 s
(EngineCore pid=2635032) INFO 07-12 14:48:45 [backends.py:378] Cache the graph of compile range (1, 8192) for later use
(EngineCore pid=2635032) INFO 07-12 14:48:53 [backends.py:393] Compiling a graph for compile range (1, 8192) takes 22.95 s
(EngineCore pid=2635032) INFO 07-12 14:48:57 [decorators.py:708] saved AOT compiled function to /home/admin/cpfs/wjh/.cache/vllm/torch_compile_cache/torch_aot_compile/fe5a82dbe929018b7aea7dee05b5cd31a21fe2682aca78ee4cbf2b37c8a086d6/rank_0_0/model
(EngineCore pid=2635032) INFO 07-12 14:48:57 [monitor.py:53] torch.compile took 37.29 s in total
(EngineCore pid=2635032) INFO 07-12 14:48:58 [fused_moe.py:1058] Using configuration from /home/admin/cpfs/wjh/opprof-phase2-dash0-20260711/vllm-v0.24.0/vllm/model_executor/layers/fused_moe/configs/E=128,N=768,device_name=NVIDIA_H20.json for MoE layer.
(EngineCore pid=2635032) INFO 07-12 14:49:00 [monitor.py:81] Initial profiling/warmup run took 2.18 s
(EngineCore pid=2635032) INFO 07-12 14:49:07 [gpu_model_runner.py:6487] Profiling CUDA graph memory: PIECEWISE=7 (largest=32), FULL=5 (largest=16)
(EngineCore pid=2635032) INFO 07-12 14:49:12 [gpu_model_runner.py:6592] Estimated CUDA graph memory: 0.08 GiB total
(EngineCore pid=2635032) INFO 07-12 14:49:13 [gpu_worker.py:508] Available KV cache memory: 29.43 GiB
(EngineCore pid=2635032) INFO 07-12 14:49:13 [gpu_worker.py:523] CUDA graph memory profiling is enabled (default since v0.21.0). The current --gpu-memory-utilization=0.9200 is equivalent to --gpu-memory-utilization=0.9191 without CUDA graph memory profiling. To maintain the same effective KV cache size as before, increase --gpu-memory-utilization to 0.9209. To disable, set VLLM_MEMORY_PROFILER_ESTIMATE_CUDAGRAPHS=0.
(EngineCore pid=2635032) INFO 07-12 14:49:13 [kv_cache_utils.py:2146] GPU KV cache size: 321,456 tokens
(EngineCore pid=2635032) INFO 07-12 14:49:13 [kv_cache_utils.py:2147] Maximum concurrency for 40,960 tokens per request: 7.85x
(EngineCore pid=2635032) INFO 07-12 14:49:13 [deep_gemm.py:175] deep_gemm not found in site-packages, trying vendored vllm.third_party.deep_gemm
(EngineCore pid=2635032) INFO 07-12 14:49:13 [deep_gemm.py:202] DeepGEMM PDL enabled on vllm.third_party.deep_gemm.
(EngineCore pid=2635032) 2026-07-12 14:49:13,542 - INFO - autotuner.py:622 - flashinfer.jit: [Autotuner]: Autotuning process starts ...
(EngineCore pid=2635032) 2026-07-12 14:49:13,588 - INFO - autotuner.py:641 - flashinfer.jit: [Autotuner]: Autotuning process ends
(EngineCore pid=2635032) 
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(EngineCore pid=2635032) 
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(EngineCore pid=2635032) INFO 07-12 14:49:19 [gpu_model_runner.py:6660] Graph capturing finished in 6 secs, took 0.10 GiB
(EngineCore pid=2635032) INFO 07-12 14:49:19 [gpu_worker.py:667] CUDA graph pool memory: 0.1 GiB (actual), 0.08 GiB (estimated), difference: 0.02 GiB (15.7%).
(EngineCore pid=2635032) INFO 07-12 14:49:19 [jit_monitor.py:60] Kernel JIT monitor activated — Triton JIT compilations during inference will be logged as warnings.
(EngineCore pid=2635032) INFO 07-12 14:49:19 [core.py:337] init engine (profile, create kv cache, warmup model) took 59.33 s (compilation: 37.29 s)
(EngineCore pid=2635032) INFO 07-12 14:49:20 [scheduler.py:282] OpProf telemetry enabled: /home/admin/cpfs/wjh/opprof-phase6-dash0-20260712/runs/phase6/cells/tp1_mns16/opprof/opprof-v1-dp0-pid2635032-1783867760160342792.jsonl
(EngineCore pid=2635032) INFO 07-12 14:49:20 [vllm.py:1006] Asynchronous scheduling is enabled.
(EngineCore pid=2635032) INFO 07-12 14:49:20 [kernel.py:276] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native'])
(APIServer pid=2634246) INFO 07-12 14:49:20 [api_server.py:577] Supported tasks: ['generate']
(APIServer pid=2634246) WARNING 07-12 14:49:20 [model.py:1477] Default vLLM sampling parameters have been overridden by the model's `generation_config.json`: `{'temperature': 0.6, 'top_k': 20, 'top_p': 0.95}`. If this is not intended, please relaunch vLLM instance with `--generation-config vllm`.
(APIServer pid=2634246) INFO 07-12 14:49:20 [hf.py:548] Detected the chat template content format to be 'string'. You can set `--chat-template-content-format` to override this.
(APIServer pid=2634246) INFO 07-12 14:49:20 [api_server.py:581] Starting vLLM server on http://127.0.0.1:8501
(APIServer pid=2634246) INFO 07-12 14:49:20 [launcher.py:37] Available routes are:
(APIServer pid=2634246) INFO 07-12 14:49:20 [launcher.py:46] Route: /openapi.json, Methods: HEAD, GET
(APIServer pid=2634246) INFO 07-12 14:49:20 [launcher.py:46] Route: /docs, Methods: HEAD, GET
(APIServer pid=2634246) INFO 07-12 14:49:20 [launcher.py:46] Route: /docs/oauth2-redirect, Methods: HEAD, GET
(APIServer pid=2634246) INFO 07-12 14:49:20 [launcher.py:46] Route: /redoc, Methods: HEAD, GET
(APIServer pid=2634246) INFO 07-12 14:49:20 [launcher.py:46] Route: /load, Methods: GET
(APIServer pid=2634246) INFO 07-12 14:49:20 [launcher.py:46] Route: /version, Methods: GET
(APIServer pid=2634246) INFO 07-12 14:49:20 [launcher.py:46] Route: /health, Methods: GET
(APIServer pid=2634246) INFO 07-12 14:49:20 [launcher.py:46] Route: /metrics, Methods: GET
(APIServer pid=2634246) INFO 07-12 14:49:20 [launcher.py:46] Route: /tokenize, Methods: POST
(APIServer pid=2634246) INFO 07-12 14:49:20 [launcher.py:46] Route: /detokenize, Methods: POST
(APIServer pid=2634246) INFO 07-12 14:49:20 [launcher.py:46] Route: /v1/models, Methods: GET
(APIServer pid=2634246) INFO 07-12 14:49:20 [launcher.py:46] Route: /ping, Methods: GET
(APIServer pid=2634246) INFO 07-12 14:49:20 [launcher.py:46] Route: /ping, Methods: POST
(APIServer pid=2634246) INFO 07-12 14:49:20 [launcher.py:46] Route: /invocations, Methods: POST
(APIServer pid=2634246) INFO 07-12 14:49:20 [launcher.py:46] Route: /v1/chat/completions, Methods: POST
(APIServer pid=2634246) INFO 07-12 14:49:20 [launcher.py:46] Route: /v1/chat/completions/batch, Methods: POST
(APIServer pid=2634246) INFO 07-12 14:49:20 [launcher.py:46] Route: /v1/responses, Methods: POST
(APIServer pid=2634246) INFO 07-12 14:49:20 [launcher.py:46] Route: /v1/responses/{response_id}, Methods: GET
(APIServer pid=2634246) INFO 07-12 14:49:20 [launcher.py:46] Route: /v1/responses/{response_id}/cancel, Methods: POST
(APIServer pid=2634246) INFO 07-12 14:49:20 [launcher.py:46] Route: /v1/completions, Methods: POST
(APIServer pid=2634246) INFO 07-12 14:49:20 [launcher.py:46] Route: /v1/messages, Methods: POST
(APIServer pid=2634246) INFO 07-12 14:49:20 [launcher.py:46] Route: /v1/messages/count_tokens, Methods: POST
(APIServer pid=2634246) INFO 07-12 14:49:20 [launcher.py:46] Route: /generative_scoring, Methods: POST
(APIServer pid=2634246) INFO 07-12 14:49:20 [launcher.py:46] Route: /inference/v1/generate, Methods: POST
(APIServer pid=2634246) INFO 07-12 14:49:20 [launcher.py:46] Route: /scale_elastic_ep, Methods: POST
(APIServer pid=2634246) INFO 07-12 14:49:20 [launcher.py:46] Route: /is_scaling_elastic_ep, Methods: POST
(APIServer pid=2634246) INFO 07-12 14:49:20 [launcher.py:46] Route: /v1/chat/completions/render, Methods: POST
(APIServer pid=2634246) INFO 07-12 14:49:20 [launcher.py:46] Route: /v1/completions/render, Methods: POST
(APIServer pid=2634246) INFO 07-12 14:49:20 [launcher.py:46] Route: /v1/chat/completions/derender, Methods: POST
(APIServer pid=2634246) INFO 07-12 14:49:20 [launcher.py:46] Route: /v1/completions/derender, Methods: POST
(APIServer pid=2634246) INFO:     Started server process [2634246]
(APIServer pid=2634246) INFO:     Waiting for application startup.
(APIServer pid=2634246) INFO:     Application startup complete.
(EngineCore pid=2635032) INFO 07-12 14:49:23 [core.py:1214] [shutdown] EngineCore: trigger received signal=SIGTERM
(APIServer pid=2634246) INFO 07-12 14:49:23 [launcher.py:100] [shutdown] API server: shutdown triggered
(APIServer pid=2634246) INFO 07-12 14:49:23 [launcher.py:116] [shutdown] API server: stopping engine client mode=drain timeout=120s
(EngineCore pid=2635032) INFO 07-12 14:49:23 [core.py:1333] [shutdown] EngineCore: start mode=drain timeout=120s
(EngineCore pid=2635032) INFO 07-12 14:49:23 [core.py:1364] [shutdown] EngineCore: request processing complete; starting resource teardown
(EngineCore pid=2635032) INFO 07-12 14:49:23 [core.py:1227] [shutdown] EngineCore: exiting busy loop
(APIServer pid=2634246) INFO 07-12 14:49:23 [core_client.py:655] [shutdown] MPClient: start timeout=120s
(APIServer pid=2634246) INFO 07-12 14:49:23 [core_client.py:657] [shutdown] MPClient: stopping engine manager
(APIServer pid=2634246) INFO:     Shutting down
(APIServer pid=2634246) INFO:     Waiting for application shutdown.
(APIServer pid=2634246) INFO:     Application shutdown complete.
(APIServer pid=2634246) INFO:     Finished server process [2634246]
(APIServer pid=2634246) INFO 07-12 14:49:24 [core_client.py:659] [shutdown] MPClient: engine manager stopped
(APIServer pid=2634246) INFO 07-12 14:49:24 [core_client.py:660] [shutdown] MPClient: cleaning up background resources
(APIServer pid=2634246) INFO 07-12 14:49:24 [core_client.py:662] [shutdown] MPClient: complete
/usr/lib/python3.12/multiprocessing/resource_tracker.py:254: UserWarning: resource_tracker: There appear to be 1 leaked semaphore objects to clean up at shutdown
  warnings.warn('resource_tracker: There appear to be %d '
