How to install TensorFlow version with CUDA, cudNN and GPU support - Step by step tutorial 2023

How to install TensorFlow version with CUDA, cudNN and GPU support - Step by step tutorial 2023

Welcome to our step-by-step tutorial on how to install TensorFlow version with CUDA, cudNN and GPU support in 2023.

TensorFlow is one of the most popular open-source machine learning libraries in the world. It is widely used in various fields such as computer vision, natural language processing, and robotics. TensorFlow has many advantages, one of which is the ability to use the power of GPUs to speed up computations. In order to utilize GPUs, we need to install additional software such as CUDA and cudNN. In this tutorial, we will guide you through the process of installing these software packages along with TensorFlow.

Before we get started, you need to ensure that your computer meets the minimum system requirements. You should have a compatible GPU that supports CUDA, as well as the necessary drivers installed. You can check the compatibility of your GPU with CUDA by visiting the NVIDIA website. here link for more details, please check it:

Once you have confirmed that your computer meets the requirements, let's move on to the installation process. The first step is to download and install CUDA, which is a parallel computing platform and programming model developed by NVIDIA. CUDA enables developers to accelerate applications by offloading compute-intensive tasks to the GPU.

After installing CUDA, we need to install cudNN, which is a library for deep neural networks. cudNN is designed to take advantage of the CUDA architecture, providing high-performance primitives for deep learning frameworks such as TensorFlow.

Once we have installed CUDA and cudNN, we can move on to installing TensorFlow with GPU support. This version of TensorFlow is optimized to run on GPUs, providing faster training and inference times for deep learning models.

In this tutorial, we will guide you through each step of the installation process, from downloading and installing CUDA and cudNN to installing TensorFlow with GPU support. We will also provide troubleshooting tips for common installation issues.

By the end of this tutorial, you will have a fully functioning installation of TensorFlow with CUDA, cudNN, and GPU support. You will be able to utilize the power of your GPU to accelerate your deep learning computations, making your models run faster and more efficiently.

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Thank you for joining us for this tutorial. Let's get started!

[mohananant]

Struggling from last seven days to find a workable solution in oct 2023. Anyone looking to install this is the perfect step by step solution.
Great Work!!

[hzhox]

Hi, I wonder what is the use of downloading GPU drivers but not installing it.
I am currently using win11, anaconda with python 3.10.9, tensorflow 2.13.0.
and I install CUDA toolkit 11.8, and CuDNN 8.6, by following the instructions given in the video.
I followed the same steps as your video, but my gpu was not detected by tensorflow.

[AndresCamiloPaez]

Thank you so much, I lost too much time trying to make this work and yours is the only video who has it right

[elifoksuzali]

Hello sir I have multigpu card geforce rtx 1080 ti and geforce geforce 2060 and other gpu amd how can I get used to these and I want to learn this field in depth but my anaconda navigator works in this code " import tensorflow as tf tf.configf (GPU) anaconda I was wondering if it sees the GPU of my laptop but anaconda does not see the GPUs in my computer at all can you please help me

[donfeto]

WTF all of those steps why it is so hard to work with tensorflow

[aryanraina]

Which cuda version is suitable for tensorflow 2.12.0

[RymDAKHLI]

Thanx for the video, do you have any idea how to install cuda toolkit 11.2 for windows 11. On the NVIDIA website there isn’t an installer for Windows 11, just Windows 10 and some server versions.

[jenilsaliya]

you should provide reference link so that user can easily access the sources

[arkanayudha]

So it doesn't need the visual studio community?

[drancerd]

Can yo make More videos teaching TF+ CUDA + Tensor Core?

[patolinoD]

I did everything exactly like your video and it didn't work, the GPU doesn't appear.

I installed the exact same CUDA Toolkit and the same for CuDNN.

Remembering that I have the same video card GTX 1050 TI 4GB.

[SandeepSingh-ocrr]

The Cudnn archive website pages are not working now, clicking on any version is showing that "Even Ai cant find that page", how to resolve this ?

[khenpahilanga]

hello, does the python version have to be 3.8? I have python 3.10 in my system at the moment thru anaconda installation, im scared of removing it as it may cause errors after changing. I am currently new and just freshly learning machine and deep learning and im afraid changing the python version may affect my training of algorithm, which I have been able to do with my current setup and system.

[davidwilliam.g]

which version of tensorflow i want to install

[Luckypantera]

Hi, how can I test it? I don't have Jupyter, thanks for your help. Your video was amazing!

[falahakmalismail]

I'm still having issues after following all the steps but with different version of mine (tf version 2.14, CUDA version 11.8, CuDNN version 8.7, python version 3.9). Do you have any idea with this? because it seems like when I tried to run still got error GPU device not found. Thank you...

[jasonkadayat]

How can check it whether is it working or not? Could you provide the code. And where to run the code?

[gurudasshinde]

I have tensorflow version 2.5 and tf detects my gpu rtx 3050. But in jupyter notebook kernel becomes dead frequently while building model

[rvrhnuy]

Hey not working. I have cuda tollkit 11.8 and CuDnn 8.6 and followed the exact steps. Python 3.11. Tensorflow 2.13.0

[aryans]

Hi brother...I have ssame 1050 ti card...In the video you have shown cudaa version 10.1 and Cudnn version 10.1 to download....but you have installed version 10.0 on your system....Please help which version to install...It's very urgent. Thankyou.