"no CUDA-capable device is detected" with CUDA-capable GPU installed Win7

Question

I have installed cuda.7.0.28 into my laptop. I tried to run one of the sample file. I ran deviceQuery project and got this message:

cudaGetDeviceCount returned 38
-> no CUDA-capable device is detected
Result = FAIL

Then, I ran nvidia-smi.exe file and got this message:

As you see, it is written that "Not Supported". What should I do?

Solution

nvidia-smi returning 'not supported' does not necessarily mean that your GPU does not have the ability to run CUDA code. It means that you don't have the ability to see the active CUDA process name using nvidia-smi.

Cuda-z might be of help here. Take a look at what it is here: http://cuda-z.sourceforge.net/

Also, I have to say I had quite a few problems getting CUDA running on Windows. If you really need to run it on Windows, make sure you go through this first: http://docs.nvidia.com/cuda/cuda-getting-started-guide-for-microsoft-windows/#axzz3cNkYKZDP

Have you tried to run it on linux on the same machine? It was much easier to get it workinge.

Comments

[michael scolfield]

I tried to install CUDA in ubuntu using virtual machine. In the beginning of the installation, it said that This might cause some serious problems on your computer . Do you recommend keep going installation?

[Dennis C Furlaneto]

I've seen people installing CUDA in Virtual machines without problems. This guide actually teaches you how to install Cuda and use caffe (python package) on a virtual machine: github.com/BVLC/caffe/wiki/Ubuntu-14.04-VirtualBox-VM. I would recommend creating a small partition in your disk and installing Linux for your work - I think it will pay off over time as I've found most open source code I encountered works better in Linux.

[michael scolfield]

I accomplished installing cuda in ubuntu using virtual machine. I took a snaphot before restarting the machine. After restarting the machine, it cannot open ubuntu. It gets stuck in that status.

[Robert Crovella]

Unless you take special steps (e.g. PCI Passthrough), and have the proper setup, you can't use a GPU in a VM. Note the instruction in the the linked guide: "Do NOT install the graphics card drivers (since we are in a virtual machine)" and "(In a virtual machine we do not have access to the the GPU)" So this isn't really a sensible suggestion if the goal is to actually be able to use the GPU in that laptop (or any GPU) for CUDA.