There was a problem when starting up, and the console reported an error `cuCtxCreate(): invalid argument`
Below is the log file
Below is the information of nvidia-smi
I am curious why the first time I execute `hc_cuCtxCreate` to check device_available_mem, no exception is triggered
https://github.com/hashcat/hashcat/blob/...nd.c#L5365
But the second time when create context for each device, the program outputs invalid argument
https://github.com/hashcat/hashcat/blob/...nd.c#L9638
Unfortunately, there are so many statements in between that I can't debug whether the exception is caused by cuda_context or cuda_device.
So can anyone help me figure out what's going wrong here?
Below is the log file
Code:
$ cat ./example0.sh
./hashcat -m 0 -t 32 -a 7 example0.hash ?a?a?a?a example.dict
$ sh ./example0.sh
hashcat (v6.2.6) starting
nvmlDeviceGetFanSpeed(): Not Supported
CUDA API (CUDA 11.7)
====================
* Device #1: Tesla T4, 7583/7680 MB, 40MCU
OpenCL API (OpenCL 3.0 CUDA 11.7.101) - Platform #1 [NVIDIA Corporation]
========================================================================
* Device #2: Tesla T4, skipped
Minimum password length supported by kernel: 0
Maximum password length supported by kernel: 256
Dictionary cache hit:
* Filename..: example.dict
* Passwords.: 128416
* Bytes.....: 1069601
* Keyspace..: 128416
Hashes: 6494 digests; 6494 unique digests, 1 unique salts
Bitmaps: 16 bits, 65536 entries, 0x0000ffff mask, 262144 bytes, 5/13 rotates
Optimizers applied:
* Zero-Byte
* Early-Skip
* Not-Salted
* Not-Iterated
* Single-Salt
* Raw-Hash
[color=#ffdc00]ATTENTION! Pure (unoptimized) backend kernels selected.[/color]
[color=#ffdc00]Pure kernels can crack longer passwords, but drastically reduce performance.[/color]
[color=#ffdc00]If you want to switch to optimized kernels, append -O to your commandline.[/color]
[color=#ffdc00]See the above message to find out about the exact limits.[/color]
Watchdog: Temperature abort trigger set to 90c
[color=#e82a1f][b]cuCtxCreate(): invalid argument[/b][/color]
Started: Fri Feb 7 21:28:49 2025
Stopped: Fri Feb 7 21:28:51 2025Below is the information of nvidia-smi
Code:
$ nvidia-smi
Fri Feb 7 21:31:22 2025
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 515.65.01 Driver Version: 515.65.01 CUDA Version: 11.7 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 Tesla T4 On | 00000000:00:0A.0 Off | 0 |
| N/A 67C P0 41W / 70W | 0MiB / 7680MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+I am curious why the first time I execute `hc_cuCtxCreate` to check device_available_mem, no exception is triggered
https://github.com/hashcat/hashcat/blob/...nd.c#L5365
But the second time when create context for each device, the program outputs invalid argument
https://github.com/hashcat/hashcat/blob/...nd.c#L9638
Unfortunately, there are so many statements in between that I can't debug whether the exception is caused by cuda_context or cuda_device.
So can anyone help me figure out what's going wrong here?
