Task 38578961

Name wu_dea916fb-GIANNI_GPROTO7-0-1-RND5952_0
Workunit 31544403
Created 27 Sep 2025, 7:49:41 UTC
Sent 27 Sep 2025, 7:49:56 UTC
Report deadline 2 Oct 2025, 7:49:56 UTC
Received 27 Sep 2025, 8:45:00 UTC
Server state Over
Outcome Computation error
Client state Compute error
Exit status 195 (0x000000C3) EXIT_CHILD_FAILED
Computer ID 642323
Run time 2 min 22 sec
CPU time 22 sec
Validate state Invalid
Credit 0.00
Device peak FLOPS 55,497.90 GFLOPS
Application version LLM: LLMs for chemistry v1.01 (cuda124L)
windows_x86_64
Peak working set size 927.61 MB
Peak swap size 4.60 GB
Peak disk usage 6.14 GB

Stderr output

<core_client_version>8.2.4</core_client_version>
<![CDATA[
<message>
The operating system cannot run (null).
 (0xc3) - exit code 195 (0xc3)</message>
<stderr_txt>
04:42:06 (15012): wrapper (7.9.26016): starting
04:42:06 (15012): wrapper: running Library/usr/bin/tar.exe (xjvf input.tar.bz2)
tasks.json
run.bat
conf.yaml
main_generation-0.1.0-py3-none-any.whl
run.sh
04:42:07 (15012): Library/usr/bin/tar.exe exited; CPU time 0.015625
04:42:07 (15012): wrapper: running C:/Windows/system32/cmd.exe (/c call Scripts\activate.bat && Scripts\conda-unpack.exe && run.bat)

Generating train split: 0 examples [00:00, ? examples/s]
Generating train split: 2500 examples [00:00, 249970.44 examples/s]
D:\ProgramData\BOINC\slots\2\Lib\site-packages\torch\cuda\__init__.py:235: UserWarning: 
NVIDIA GeForce RTX 5090 with CUDA capability sm_120 is not compatible with the current PyTorch installation.
The current PyTorch install supports CUDA capabilities sm_50 sm_60 sm_61 sm_70 sm_75 sm_80 sm_86 sm_90.
If you want to use the NVIDIA GeForce RTX 5090 GPU with PyTorch, please check the instructions at https://pytorch.org/get-started/locally/

  warnings.warn(
[W927 04:42:59.000000000 socket.cpp:759] [c10d] The client socket has failed to connect to [VENGEANCE]:62300 (system error: 10049 - The requested address is not valid in its context.).
[rank0]: Traceback (most recent call last):
[rank0]:   File "wheel_contents/aiengine/main_generation.py", line 87, in <module>
[rank0]:   File "wheel_contents/aiengine/model.py", line 36, in __init__
[rank0]:   File "D:\ProgramData\BOINC\slots\2\Lib\site-packages\vllm\utils.py", line 1096, in inner
[rank0]:     return fn(*args, **kwargs)
[rank0]:            ^^^^^^^^^^^^^^^^^^^
[rank0]:   File "D:\ProgramData\BOINC\slots\2\Lib\site-packages\vllm\entrypoints\llm.py", line 243, in __init__
[rank0]:     self.llm_engine = LLMEngine.from_engine_args(
[rank0]:                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^
[rank0]:   File "D:\ProgramData\BOINC\slots\2\Lib\site-packages\vllm\engine\llm_engine.py", line 521, in from_engine_args
[rank0]:     return engine_cls.from_vllm_config(
[rank0]:            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[rank0]:   File "D:\ProgramData\BOINC\slots\2\Lib\site-packages\vllm\engine\llm_engine.py", line 497, in from_vllm_config
[rank0]:     return cls(
[rank0]:            ^^^^
[rank0]:   File "D:\ProgramData\BOINC\slots\2\Lib\site-packages\vllm\engine\llm_engine.py", line 281, in __init__
[rank0]:     self.model_executor = executor_class(vllm_config=vllm_config, )
[rank0]:                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[rank0]:   File "D:\ProgramData\BOINC\slots\2\Lib\site-packages\vllm\executor\executor_base.py", line 52, in __init__
[rank0]:     self._init_executor()
[rank0]:   File "D:\ProgramData\BOINC\slots\2\Lib\site-packages\vllm\executor\uniproc_executor.py", line 47, in _init_executor
[rank0]:     self.collective_rpc("load_model")
[rank0]:   File "D:\ProgramData\BOINC\slots\2\Lib\site-packages\vllm\executor\uniproc_executor.py", line 56, in collective_rpc
[rank0]:     answer = run_method(self.driver_worker, method, args, kwargs)
[rank0]:              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[rank0]:   File "D:\ProgramData\BOINC\slots\2\Lib\site-packages\vllm\utils.py", line 2359, in run_method
[rank0]:     return func(*args, **kwargs)
[rank0]:            ^^^^^^^^^^^^^^^^^^^^^
[rank0]:   File "D:\ProgramData\BOINC\slots\2\Lib\site-packages\vllm\worker\worker.py", line 184, in load_model
[rank0]:     self.model_runner.load_model()
[rank0]:   File "D:\ProgramData\BOINC\slots\2\Lib\site-packages\vllm\worker\model_runner.py", line 1113, in load_model
[rank0]:     self.model = get_model(vllm_config=self.vllm_config)
[rank0]:                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[rank0]:   File "D:\ProgramData\BOINC\slots\2\Lib\site-packages\vllm\model_executor\model_loader\__init__.py", line 14, in get_model
[rank0]:     return loader.load_model(vllm_config=vllm_config)
[rank0]:            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[rank0]:   File "D:\ProgramData\BOINC\slots\2\Lib\site-packages\vllm\model_executor\model_loader\loader.py", line 1278, in load_model
[rank0]:     model = _initialize_model(vllm_config=vllm_config)
[rank0]:             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[rank0]:   File "D:\ProgramData\BOINC\slots\2\Lib\site-packages\vllm\model_executor\model_loader\loader.py", line 127, in _initialize_model
[rank0]:     return model_class(vllm_config=vllm_config, prefix=prefix)
[rank0]:            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[rank0]:   File "D:\ProgramData\BOINC\slots\2\Lib\site-packages\vllm\model_executor\models\qwen2.py", line 431, in __init__
[rank0]:     self.model = Qwen2Model(vllm_config=vllm_config,
[rank0]:                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[rank0]:   File "D:\ProgramData\BOINC\slots\2\Lib\site-packages\vllm\compilation\decorators.py", line 151, in __init__
[rank0]:     old_init(self, vllm_config=vllm_config, prefix=prefix, **kwargs)
[rank0]:   File "D:\ProgramData\BOINC\slots\2\Lib\site-packages\vllm\model_executor\models\qwen2.py", line 300, in __init__
[rank0]:     self.start_layer, self.end_layer, self.layers = make_layers(
[rank0]:                                                     ^^^^^^^^^^^^
[rank0]:   File "D:\ProgramData\BOINC\slots\2\Lib\site-packages\vllm\model_executor\models\utils.py", line 610, in make_layers
[rank0]:     maybe_offload_to_cpu(layer_fn(prefix=f"{prefix}.{idx}"))
[rank0]:                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[rank0]:   File "D:\ProgramData\BOINC\slots\2\Lib\site-packages\vllm\model_executor\models\qwen2.py", line 302, in <lambda>
[rank0]:     lambda prefix: Qwen2DecoderLayer(config=config,
[rank0]:                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[rank0]:   File "D:\ProgramData\BOINC\slots\2\Lib\site-packages\vllm\model_executor\models\qwen2.py", line 206, in __init__
[rank0]:     self.self_attn = Qwen2Attention(
[rank0]:                      ^^^^^^^^^^^^^^^
[rank0]:   File "D:\ProgramData\BOINC\slots\2\Lib\site-packages\vllm\model_executor\models\qwen2.py", line 153, in __init__
[rank0]:     self.rotary_emb = get_rope(
[rank0]:                       ^^^^^^^^^
[rank0]:   File "D:\ProgramData\BOINC\slots\2\Lib\site-packages\vllm\model_executor\layers\rotary_embedding.py", line 1180, in get_rope
[rank0]:     rotary_emb = RotaryEmbedding(head_size, rotary_dim, max_position, base,
[rank0]:                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[rank0]:   File "D:\ProgramData\BOINC\slots\2\Lib\site-packages\vllm\model_executor\layers\rotary_embedding.py", line 99, in __init__
[rank0]:     cache = self._compute_cos_sin_cache()
[rank0]:             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[rank0]:   File "D:\ProgramData\BOINC\slots\2\Lib\site-packages\vllm\model_executor\layers\rotary_embedding.py", line 116, in _compute_cos_sin_cache
[rank0]:     inv_freq = self._compute_inv_freq(self.base)
[rank0]:                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[rank0]:   File "D:\ProgramData\BOINC\slots\2\Lib\site-packages\vllm\model_executor\layers\rotary_embedding.py", line 110, in _compute_inv_freq
[rank0]:     inv_freq = 1.0 / (base**(torch.arange(
[rank0]:                              ^^^^^^^^^^^^^
[rank0]:   File "D:\ProgramData\BOINC\slots\2\Lib\site-packages\torch\utils\_device.py", line 104, in __torch_function__
[rank0]:     return func(*args, **kwargs)
[rank0]:            ^^^^^^^^^^^^^^^^^^^^^
[rank0]: RuntimeError: CUDA error: no kernel image is available for execution on the device
[rank0]: CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
[rank0]: For debugging consider passing CUDA_LAUNCH_BLOCKING=1
[rank0]: Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.

04:43:02 (15012): C:/Windows/system32/cmd.exe exited; CPU time 22.328125
04:43:02 (15012): app exit status: 0x16
04:43:02 (15012): called boinc_finish(195)
0 bytes in 0 Free Blocks.
256 bytes in 6 Normal Blocks.
1144 bytes in 1 CRT Blocks.
0 bytes in 0 Ignore Blocks.
0 bytes in 0 Client Blocks.
Largest number used: 0 bytes.
Total allocations: 918489 bytes.
Dumping objects ->
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Object dump complete.

</stderr_txt>
]]>


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