install cuda ubuntu pytorch
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CUDA is a parallel computing platform and application programming interface model created by Nvidia. PyTorch, a popular deep learning library, can leverage CUDA to accelerate computations on Nvidia GPUs. This tutorial will guide you through the process of installing CUDA on Ubuntu and setting up PyTorch to use it.
Nvidia GPU: Ensure that your system has a compatible Nvidia GPU. You can check the official Nvidia website for a list of supported GPUs.
Ubuntu OS: This tutorial assumes you are using Ubuntu. Make sure your system is running a supported version.
Nvidia Driver: Install the latest Nvidia driver for your GPU. You can use the following commands to install it:
CMake: Install CMake, which is required for building PyTorch from source.
Download CUDA Toolkit: Visit the Nvidia CUDA Toolkit download page and download the appropriate version for your GPU and Ubuntu version.
Install CUDA Toolkit:
Set Environment Variables: Add CUDA to your system’s environment variables by appending the following lines to your ~/.bashrc or ~/.zshrc file:
Then, run:
Replace cuda_version with your installed CUDA version.
CuDNN is a GPU-accelerated library for deep neural networks. PyTorch requires cuDNN for optimal performance.
Download cuDNN: Visit the Nvidia cuDNN download page and download the appropriate version for your CUDA version.
Install cuDNN:
Replace cudnn_version and cuda_version with the versions you downloaded.
Install Dependencies:
Install PyTorch:
Replace cuda_version with the version of CUDA you installed.
You can verify the installation by running a simple PyTorch script:
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