Nvidia Cuda, cuDNN, Conda, PyTorch and TensorFlow Installation with Ubuntu 22.04

This video is all you need to get your Ubuntu 22.04 Deep Learning machine ready with the following:
1. Ubuntu Kernel 5.18 Update
2. Latest Nvidia Display Driver 515.57
3. Cuda Toolkit 11.7
4. cuDNN 8.0 Installation
5. Conda Toolkit 11.7
6. Python 3.9
7. Torch with GPU Support
8. TensorFlow with GPU support

GitHub Resources:

▬▬▬▬▬▬ ⏰ TUTORIAL TIME STAMPS ⏰ ▬▬▬▬▬▬
- (00:00) Quick Intro
- (01:32) Ubuntu Kernel 5.18 Update
- (02:30) Nvidia Driver update 515.57
- (03:05) Driver install in Recovery Mode
- (04:40) Cuda Toolkit 11.7 Installation
- (05:24) Tools nvcc, gcc, g++, cmake check
- (06:06) cudNN 8.x instalation
- (09:32) Conda Cuda Toolkit 11.7 Installation
- (10:22) Python 3.9 and Torch test with GPU
- (10:45) TensorFlow Installation with GPU
- (11:15) Final installation validation

Connect
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Tags:
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[linuxbrad]

Thank you! I wouldn't have even known what questions to ask, but you have enumerated the process quite clearly. Keep up the good work!

[SpaceExplorer]

thank you. I have hated how difficult this process has been I hope this video works!

[gpligor]

Sorry but at the end of the video near ~12:00 the output seems that no GPUs are found! why is that ?

[themysteriousindian]

manual installation for cuda is a bit hard for maintaining i recommend using cuda containers by nvidia using docker once that's configured there is no issue as the gcc issues happens with other packages docker can tackle this problem

[MK-izgc]

When I check whether GPU is acessable i have 10 answer that is not and last that GPU is fine. But it works and my network is learning using GPU.

[periyasamyshyamsundar]

Hi Prodramp, thanks for the wonderful tutorial.

[manfredkremer]

I have problems with this procedure. Already at the very beginning at updating the kernel there is a mistake: instead of .deb it must be *.deb This I finally figured out. When I try to install the NVIDIA driver in the recovery mode, the installation is terminated, because it needs cc, but in my system (i specially prepared a virgin system to do the procedure) cc is not found. This makes it difficult to follow your instructions.

[danielwulf]

for MX Linux users installing cuda as deb package:

sudo add-apt-repository contrib

doesn't work out of the box, use instead:

sudo apt-get install software-properties-common

[shubhamkulkarni]

I followed your setps, installed drive in reboot successfully but still getting this error:
NVIDIA-SMI has failed because it couldn't communicate with the NVIDIA driver. Make sure that the latest NVIDIA driver is installed and running.

Please help

[AnvABmai]

CUDA version in nvidia-smi output does not shows actually installed CUDA toolkit version, but show the latest suitable CUDA version for current driver. To check actual installed CUDA version please use nvcc --version command

[kasichennupati]

Hey

its a great video able to follow through the whole video and explained very well

small correction in the Ubuntu kernel Update 5.18 section

code to install all the .deb packages is

sudo dpkg -i *.deb

Also after installing the cuda
need to add the path to .bashrc

cd /home/$user/
nano .bashrc
add below
export
export

now nvcc --version will show up

[dmaxdsbabo]

I thought the CUDA toolkit downloads the Driver automatically?

[IanWoolf]

Every time I reboot after nvidia driver installation I get a "oh no something went wrong" screen. I tried to follow your directions, but dpkg of linux-modules won't install because the kernel isn't installed, and the kernel won't install because the linux-modules aren't installed.

[doublesami]

I have few questions becuase i want to install cuda tool kit 11.7 and pytorch 1.3.x with cuda 11.7:
1 : can I installed cuda tool kit 11.7 with latest version of nvidia drivers 535 in ubuntu 20?
2: for cuda too kit installation, you have installed cuda toolkit twice, one by downloading from nvidia website and one by running command for conda, is it compulsory to install conda based toolkit as well?

[nettyyyys]

Hello, at the beggining all installed all but nothin shown. After restart the terminal nvidia-smi showed cuda but nvcc not. I solved that with:

check if it is in your PATH by “whereis nvcc”, if it returns “nvcc:” then you need to add below two lines in “.bashrc”
usually “.bashrc” file path is like “/home/username/.bashrc” then add below two lines (change cuda version with installed version)
export
export
then save and close the file
check “nvcc --version”

Hope that it helps someone. I used it because NVIDIA-SMI sowed CUDA but NVCC --version not.

[Nomolosos]

Hi thank you for the tutorial. I have a question, during the driver install, I had a request for “install sign kernel” and things didn’t work out. I tried to install it but got an error because secure boot is enabled. Should I disable it? And how should I do that?

[skumarreddymallidi]

I am trying to setup a small station with 2 rtx 3060 GPUs, but not able to. Can you pls guide me.

[Himakarbavikaty]

Hi Prodramp,
Thanks for your tutorial.
I did as you thought but tensorflow and pytorch are not recognizing GPU. i am able to get GPU with nvidia-smi. Can you please advise?

[shitongmao]

Thank you, Prodramp for this helpful tutorial. However, from 3:05 to 4:39, I have no idea what you are talking about. I am a machine learning Ph.D. and just bought a PC for my own projects. I just installed ubuntu 22.04, and I am trying to set up the environment. Sorry that I have learned nothing about the 'start mode', 'recovery mode', or 'user prompt', would you please explain more about the procedures? really appreciate!!

[tamizhelakkiya]

hi, it is very useful..is it mandatory to install anaconda in the base and cuda toolkit in the new environment(in your video it is in dl39).