gpuDevice Crashing Matlab
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I'm try to get up and running with GPU computing through the Parallel Computing Toolbox, but I'm having trouble getting the toolbox to work. When I run "gpuDevice", "gpuDeviceCount", or "gpuArray", Matlab instantaneously crashes, leaving only a "6573 Floating point exception" error in my shell window (the number changes every time). The crash leaves behind a "matlab_crash_dump" file, but the file is empty. Has anyone had this problem before and been able to discover what the problem was?
I'm on a Linux machine with a Quadro 4000 GPU and NVidia's 295.20 drivers. I've had this problem since I got the toolbox a few months ago, but at the time assumed it was because I was using an old and unsupported set of drivers. Those have been updated now, but I still get the same problem.
Jason Ross on 13 Apr 2012
What distro? What version of MATLAB? 64 or 32 bit?
If you run "nvidia-smi --query", do you get usable output? How does the device show up in the nvidia-settings application?
Is the Quadro being used for display and compute, or is it compute only?
FWIW when I've seen odd problems like this, the cause has come down to a defective card. Typical setup is to install the driver and start MATLAB, then it works.
Yair Carmon on 13 Aug 2015
I had a similar issue on a remote server that ran Ubuntu 12.04, Matlab 2015a, CUDA 7.0, and a GeForce GTX 960. During a routine run of my application, the nvidia-smi utility (which was open using watch nvidia-smi, to monitor GPU utilization) suddenly printed "Error" instead of things like temperature and available memory. A complete system crash followed immediately, and it was necessary to power cycle the machine before it started responding to ping again.
When the system came back online I had the problems reported above: any attempt to run nvidia-smi or gpuDevice/gpuArray would result in a crash. It was not a problem with the card - we swapped GPU's and the issue persisted. Uninstalling and reinstalling the CUDA toolkit using apt-get did not help either. The problem was finally resolved by reinstalling the entire OS, Matlab and CUDA 7.0 in that order. I suspect that using the CUDA 7.0 .run installation might have solved the problem without having to go through OS installation. I hope to never have a chance to check that :).