CUDA driver version is insufficient for CUDA runtime version

Hi all,

I have recently installed both tensorflow-gpu, nvidia drivers and cuda toolkit. After some research I determined I had to install CUDA 9.1 in order to be compatible with my nvidia driver which is 390.77 (I have a GTX 1070) [source: https://devtalk.nvidia.com/default/topic/1038069/cuda-setup-and-installation/which-cuda-version-will-work-with-driver-390-77-/]. However I still get the following error message:

CUDA driver version is insufficient for CUDA runtime version

  • Output from nvidia-smi:
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 390.77                 Driver Version: 390.77                    |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  GeForce GTX 1070    Off  | 00000000:01:00.0  On |                  N/A |
|  0%   46C    P8    13W / 200W |    473MiB /  8105MiB |      1%      Default |
+-------------------------------+----------------------+----------------------+
                                                                               
+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID   Type   Process name                             Usage      |
|=============================================================================|
|    0      1115      G   /usr/lib/xorg/Xorg                            24MiB |
|    0      1150      G   /usr/bin/gnome-shell                          51MiB |
|    0      1401      G   /usr/lib/xorg/Xorg                           209MiB |
|    0      1533      G   /usr/bin/gnome-shell                         139MiB |
|    0      1986      G   ...uest-channel-token=16350887306611312583    44MiB |
+-----------------------------------------------------------------------------+
  • Output from nvcc -V:
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2017 NVIDIA Corporation
Built on Fri_Nov__3_21:07:56_CDT_2017
Cuda compilation tools, release 9.1, V9.1.85
  • Output from lspci
01:00.0 VGA compatible controller: NVIDIA Corporation GP104 [GeForce GTX 1070] (rev a1)
01:00.1 Audio device: NVIDIA Corporation GP104 High Definition Audio Controller (rev a1)

What am I doing wrong? Any help is much appreciated!

Kind regards

EDIT
I did some more digging and found that the cudatoolkit specified in conda was 9.2. The installation of 9.1 didn’t seem to work so I settled on 9.0 (did the complete reinstall using

conda install tensorflow-gpu==1.11 cudatoolkit==9.0 cudnn==7.1.2 h5py

).

So now it is working but i would still like soma advice that says if this is a good solution or that I am now running things sub-optimally because of the lower cuda version.
Thanks in advance!