santolp / pyrit

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Occasional SystemError?: CUDA_ERROR_UNKNOWN message #327

Closed GoogleCodeExporter closed 8 years ago

GoogleCodeExporter commented 8 years ago
What steps will reproduce the problem?
1. run any pyrit db command (batch, list_essids)
2. then, all pyrit commands fail, even list_cores.
3.

What is the expected output? What do you see instead?

root@bt:~# pyrit list_cores Pyrit 0.3.1-dev (svn r280) (C) 2008-2010 Lukas Lueg 
http://pyrit.googlecode.com This code is distributed under the GNU General 
Public License v3+

Traceback (most recent call last):
    File "/usr/bin/pyrit", line 6, in <module>
        pyrit_cli.Pyrit_CLI().initFromArgv() 
    File "/usr/lib/python2.5/site-packages/pyrit_cli.py", line 116, in initFromArgv
        func(self, options) 
    File "/usr/lib/python2.5/site-packages/pyrit_cli.py", line 292, in list_cores
        with cpyrit.cpyrit.CPyrit() as cp: 
    File "/usr/lib/python2.5/site-packages/cpyrit/cpyrit.py", line 450, in init
        self.cores.append(CUDACore(queue=self, dev_idx=dev_idx)) 
    File "/usr/lib/python2.5/site-packages/cpyrit/cpyrit.py", line 243, in init
        cpyrit_cuda.CUDADevice.init(self, dev_idx) 
SystemError?: CUDA_ERROR_UNKNOWN

What version of the product are you using? On what operating system?

Pyrit 0.3.1-dev (svn r280)
Backtrack 4 R2, nVidia 295GTX, driver 256.xx

Please provide any additional information below.

Now, with BT installed on a physical partition, I get this message 90% of the 
time.
The situation is better with liveUSB.
The hard drive with the DB is Windows7 NTFS partition.

Original issue reported on code.google.com by Peter.Fi...@gmail.com on 19 Jun 2011 at 12:29

GoogleCodeExporter commented 8 years ago
This is not something Pyrit can do anything about; the error CUDA_ERROR_UNKNOWN 
comes directly from the driver (defined and raised by the API). It literally 
means that the driver encountered an error condition it does not know anything 
about.

You may try updating your drivers to a more recent version. It is also possible 
that - e.g. in case you overclocked your gpu - your hardware simply fails to 
act properly.

Original comment by lukas.l...@gmail.com on 19 Jun 2011 at 7:36