install pytorch with cuda linux

January 6, 2024

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Title: Installing PyTorch with CUDA on Linux: A Step-by-Step Tutorial
Introduction:
PyTorch, a popular deep learning library, can be significantly accelerated by using CUDA, which allows you to leverage the power of NVIDIA GPUs. This tutorial will guide you through the process of installing PyTorch with CUDA on a Linux system. We’ll use Ubuntu as the example distribution, but the general steps should be similar for other Linux distributions.
Prerequisites:
Step 1: Update and Upgrade your System
Ensure that your system is up-to-date by running the following commands in the terminal:
Step 2: Install NVIDIA GPU Drivers
Install the appropriate NVIDIA GPU drivers for your GPU. You can use the following command, replacing version with the desired driver version:
Reboot your system after installing the drivers:
Step 3: Install CUDA Toolkit
Download and install the CUDA Toolkit. Visit the NVIDIA CUDA Toolkit download page (https://developer.nvidia.com/cuda-downloads) and follow the instructions for your distribution. Make sure to select the correct version of CUDA compatible with your GPU.
Once downloaded, install CUDA Toolkit using the following commands (replace version with the downloaded version):
Step 4: Install cuDNN
Download cuDNN from the NVIDIA cuDNN download page (https://developer.nvidia.com/cudnn) and follow the instructions to install it. You may need to create a free NVIDIA developer account to access the cuDNN downloads.
After downloading, extract the contents and copy the files to the CUDA Toolkit directory:
Step 5: Install Anaconda (Optional)
It’s recommended to use a virtual environment for managing Python packages. Anaconda provides a convenient way to set up and manage environments.
Download and install Anaconda from the official website (https://www.anaconda.com/products/distribution):
Follow the on-screen instructions to complete the installation.
Step 6: Create a Virtual Environment (Optional)
Create a virtual environment using conda:
Step 7: Install PyTorch with CUDA
Install PyTorch with CUDA support using the following conda command:
Replace version with the version of CUDA installed on your system (e.g., 11.1).
That’s it! You’ve successfully installed PyTorch with CUDA on your Linux system. You can now start building and training deep learning models with accelerated GPU computations.
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