Comments (7)
When running inside the Docker you need to ensure that nvidia driver module is loaded in the host. We normally run deviceQuery to load the nVidia Kernel
- Launched the instance with AMI ami-d6f2e6bc
- Build DeviceQuery and run it with the following instructions in the AMI
cd NVIDIA_CUDA-7.0_Samples/1_Utilities/deviceQuery
make
./deviceQuery
3 . sudo docker run -it --privileged amazon/dsstne /bin/bash
from amazon-dsstne.
Because of the confusion I have also updated the setup documentation for further referrence.
Please do let us know if you are still blocker
from amazon-dsstne.
Thank you for a very quick reply.
3 . sudo docker run -it --privileged amazon/dsstne /bin/bash
I found the reason. It was because I didn't say "sudo" before the "docker".
Now everything is working.
I think it should be explained in the setup document. It is not clear for people who are not familiar with docker or cuda.
from amazon-dsstne.
I am having a similar problem (and hamukazu's solution doesnt work for me)
I am following the instructions in the setup file for running dsstne through docker.
In my aws ami ./deviceQuery works (it returns Detected 4 CUDA Capable device(s) and then lists them and finally says that it passed)
i can look at my device and driver with the command nvidia-smi and everything appears to be correct.
I then build the docker image and start it using:
sudo docker run -it --privileged amazon/dsstne /bin/bash
however when I try to run the sample code in the docker container all lines run up until the train step which returns the error:
GpuContext::Startup: Process 0 out of 1 initialized.
cudaGetDeviceCount failed no CUDA-capable device is detected
If I try to list nvidia devices using the command nvidia-smi it returns the errors:
Failed to initialize NVML: GPU access blocked by the operating system
Do you have any advice about how I might fix this?
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Did you install the same driver version as it is inside the docker?
from amazon-dsstne.
@Claire-Kelley Are you still Blocked with this
from amazon-dsstne.
Sorry to respond slowly! Yes I had installed the same driver version as in the docker.
I never did figure out what was causing my particular issue- I think I must have installed something improperly and not been able to uninstall it. I ended up wiping the instance and starting again with a new one (which worked as expected). Thanks for your help!
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Related Issues (20)
- Predict with k=30 result on all item with score=0.000 HOT 1
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