CODEWITHSUNDEEP
tensorflowcudacudnn
smg9450
smg9450

Reputation: 86

What is the correct version of CUDNN for CUDA 11.0

I want to start using tensorflow-gpu, and I looked some stuff up, and found out that I need to ensure that I have both CUDA and CUDNN. So, I opened up the command prompt and ran the command nvidia-smi to check my CUDA version:

C:\Program Files\NVIDIA Corporation\NVSMI>nvidia-smi
Tue Jun 02 14:13:03 2020
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 445.87       Driver Version: 445.87       CUDA Version: 11.0     |
|-------------------------------+----------------------+----------------------+
| GPU  Name            TCC/WDDM | Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  GeForce GTX 1050   WDDM  | 00000000:01:00.0 Off |                  N/A |
| N/A   40C    P8    N/A /  N/A |     77MiB /  4096MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU                  PID   Type   Process name                  GPU Memory |
|                                                                  Usage      |
|=============================================================================|
|    0                10488    C+G   ...n64\EpicGamesLauncher.exe    N/A      |
|    0                12636    C+G   ...4\UnrealCEFSubProcess.exe    N/A      |
+-----------------------------------------------------------------------------+

Now that I see my CUDA version is 11.0, I went to the NVidia's website to select a version of CUDNN that can work with CUDA 11.0, but the latest ones support up to CUDA 10.2 currently. What should I do? Can I use the one for CUDA 10.2?

Upvotes: 4

Views: 12348

Answers (2)

Dr. Snoopy
Dr. Snoopy

Reputation: 56407

What nvidia-smi shows is not the CUDA version that you have installed, but the maximum CUDA version that your driver supports.

CUDA 11.0 has been announced but not released yet (as of June 2nd 2020), so you should use CUDA 10.2 as it's the latest available version.

Upvotes: 6

Amelmal
Amelmal

Reputation: 11

A couple of weeks ago, I have upgraded three of them to the new cuda_11.0.2, Driver 450.51.06 and cuDNN _8.0. My environment:

  1. 86-64
  2. Centos 7 with gcc 4.8.5 ( sudo doesn't work in Centos. Login as root)
  3. I downloaded cuda_11.0.2-450.51.05_linux.run I took a risk but it went fine. On Nvidia cudnn matrix it said: Compute > 3.5, toolkit =11.0 , and driver r450 So the driver and toolkit minors doesn't matter.
  4. Installed, and went through pre-, post- and recommended. Everything went fine. *This is very important My cudnn installed but couldn't run the examples. If you are an Engineer, you have went through such dilemma because you bypass some small details. Gcc 4.8.5 if for installing toolkit and driver.

Cudnn 8.0 needs gcc 5 and above for c++ 11 or 14 for tool chain. So what I have done is that( I have a lot of. devtoolset versions in my environment). I choose 6.0 version instead of 5 to make not be on the border line. Re-install it, you will be cool. ***Regarding tensor-flow×××: It has nothing to do with cudnn other than kera for python if I get this right.

Upvotes: 1

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