# vLLM-Ascend在银河麒麟桌面版上不开Eager就报错，开了性能暴跌，换服务器版就正常，这是系统差异导致的吗？ **URL:** \ **Category:** General\ **Created:** [September 4, 2026, 6:07am UTC](https://discuss.vllm.ai/t/vllm-ascend-eager/2938 "2026-09-04T06:07:55Z")\ **Posts on this page:** 2\ **Page:** 1
**Author:** ![oeyoews](https://yyz2.discourse-cdn.com/flex036/user_avatar/discuss.vllm.ai/oeyoews/32/1566_2.png) [@oeyoews](https://discuss.vllm.ai/u/oeyoews)\ **Post date:** [September 4, 2026, 6:07am UTC](https://discuss.vllm.ai/t/vllm-ascend-eager/2938/1 "2026-09-04T06:07:55Z")
vllm-ascend（310p) 是否支持银河麒麟桌面版操作系统， 如果不开启eager mode, 就会提示下面这个报错， 但是如果开启eager mode, 吞吐 仅仅只有 5~6 tokens/s ， 如果把 桌面版操作系统换成银河麒麟服务器版本， 不用开启eager的情况下，吞吐速度就会有成倍的提升 ```auto ant to get the accurate stacktrace, please set the environment variable ASCEND_LAUNCH_BLOCKING=1. (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] Note: ASCEND_LAUNCH_BLOCKING=1 will force ops to run in synchronous mode, resulting in performance degradation. Please unset ASCEND_LAUNCH_BLOCKING in time after debugging. (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] [ERROR] 2026-09-04-05:30:44 (PID:243, Device:1, RankID:-1) ERR00100 PTA call acl api failed. (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] [PID: 243] 2026-09-04-05:28:07.503.485 Invalid_Argument(EH0012): aclrtAllocatorGetByStream failed. Parameter stream is invalid. Reason: The stream is not registered with any allocator. (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] TraceBack (most recent call last): (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] Asynchronous copy task failed. Reason: The pageable memory copy task does not support graph capture. (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] The argument is invalid. Reason: rtMemcpyAsync execution failed. (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] During handling of the above exception, another exception occurred: (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] Traceback (most recent call last): (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] File "/vllm-workspace/vllm/vllm/v1/executor/multiproc_executor.py", line 999, in worker_busy_loop (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] output = func(*args, **kwargs) (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] ^^^^^^^^^^^^^^^^^^^^^ (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] File "/vllm-workspace/vllm-ascend/vllm_ascend/worker/worker.py", line 778, in compile_or_warm_up_model (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] npugraph_memory_bytes = self.model_runner.capture_model() (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] File "/vllm-workspace/vllm-ascend/vllm_ascend/worker/model_runner_v1.py", line 5010, in capture_model (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] with _torch_cuda_wrapper(), _replace_gpu_model_runner_function_wrapper(parent_module_name): (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] ^^^^^^^^^^^^^^^^^^^^^ (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] File "/usr/local/python3.12.13/lib/python3.12/contextlib.py", line 158, in __exit__ (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] self.gen.throw(value) (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] File "/vllm-workspace/vllm-ascend/vllm_ascend/worker/model_runner_v1.py", line 5117, in _torch_cuda_wrapper (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] raise RuntimeError(f"NPUModelRunner init failed, error is {e}") (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] RuntimeError: NPUModelRunner init failed, error is NPUModelRunner failed, error is The Inner error is reported as above. The process exits for this inner error, and the current copy params are srclen=8, dstlen=8, kind=1. (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] Since the operator is called asynchronously, the stacktrace may be inaccurate. If you want to get the accurate stacktrace, please set the environment variable ASCEND_LAUNCH_BLOCKING=1. (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] Note: ASCEND_LAUNCH_BLOCKING=1 will force ops to run in synchronous mode, resulting in performance degradation. Please unset ASCEND_LAUNCH_BLOCKING in time after debugging. (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] [ERROR] 2026-09-04-05:30:44 (PID:243, Device:1, RankID:-1) ERR00100 PTA call acl api failed. (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] [PID: 243] 2026-09-04-05:28:07.503.485 Invalid_Argument(EH0012): aclrtAllocatorGetByStream failed. Parameter stream is invalid. Reason: The stream is not registered with any allocator. (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] TraceBack (most recent call last): (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] Asynchronous copy task failed. Reason: The pageable memory copy task does not support graph capture. (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] The argument is invalid. Reason: rtMemcpyAsync execution failed. (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] (Worker_TP1 pid=243) ERROR 09-04 05:30:46 [multiproc_executor.py:1007] ``` ---
**Author:** ![RunLLM](https://yyz2.discourse-cdn.com/flex036/user_avatar/discuss.vllm.ai/runllm/32/233_2.png) [@RunLLM](https://discuss.vllm.ai/u/RunLLM)\ **Post date:** [September 4, 2026, 6:08am UTC](https://discuss.vllm.ai/t/vllm-ascend-eager/2938/2 "2026-09-04T06:08:13Z")
目前数据源中没有明确说明 vllm-ascend（310p）是否官方支持银河麒麟桌面版操作系统，仅有对硬件、驱动、环境变量等常见问题的排查建议。你遇到的“aclrtAllocatorGetByStream failed…stream is not registered with any allocator”以及“pageable memory copy task does not support graph capture”等报错，似乎与桌面版操作系统的内存管理或驱动兼容性有关，导致 graph capture（非eager模式）失败，只能退回到eager模式，吞吐下降明显。据你的描述，换成银河麒麟服务器版后问题消失，吞吐提升，这进一步说明桌面版OS与NPU驱动/ACL API的兼容性可能存在问题。 我的理解是，vLLM官方文档和相关issue主要建议遇到此类底层报错时，优先排查驱动、硬件、操作系统兼容性，并未针对银河麒麟桌面版做过适配说明。建议优先使用银河麒麟服务器版等官方推荐的企业级Linux发行版，避免桌面版OS带来的兼容性问题。如需进一步定位，可尝试升级驱动、核查ACL API支持列表，或联系NPU/操作系统厂商获取支持。你需要更详细的排查建议或日志分析方法吗？ Sources: - [vLLM Troubleshooting](https://docs.vllm.ai/en/latest/usage/troubleshooting/) - [vLLM Known Issues](https://docs.vllm.ai/en/latest/usage/troubleshooting/#known-issues) Sources: - [vLLM Troubleshooting](https://docs.vllm.ai/en/latest/usage/troubleshooting/) - [vLLM Known Issues](https://docs.vllm.ai/en/latest/usage/troubleshooting/#known-issues) Hint: Mention @Herald in the post for followups.