Once you have verified that you have the correct version of CUDA installed, you are ready to begin the installation process for TensorFlow-GPU. If you do not have CUDA 10.2 installed, you can follow the steps outlined in this article to install it on your system. To check which version of CUDA you have currently installed, run the following command: TensorFlow-GPU requires CUDA 10.2 in order to function properly. Luckily, installing TensorFlow-GPU is a relatively simple process that can be completed in just a few steps.īefore beginning the installation process, it is important to ensure that you have the correct version of CUDA installed on your system. By default, Tensorflow will only utilize your CPU when working with data, which can severely impede performance for many tasks. Tensorflow-GPU allows you to leverage the power of your NVIDIA Graphics Processing Unit (GPU) when working with data in TensorFlow. If you see any errors, then your installation has not been successful. To test your TensorFlow installation, try running the following command: If you see “No devices found”, then your installation has not been successful. This will print out a list of your installed GPU devices and their details. The easiest way to do this is to run the “gpu info” command. Once you have completed the installation process, it is important to test your system to ensure that everything is working properly. Sudo apt-get install cuda-10-2 # You might need to restart your computer at this pointĪfter successfully completing the previous steps, you can now install TensorFlow-GPU by running the following command: The next step is to install the CUDA 10.2 toolkit, which can be done by running the following command: ![]() Once you have successfully installed the drivers, proceed to the next step. For NVIDIA graphics cards, you can find installation instructions here. The best way to install GPU drivers depends on your graphics card and operating system. If you have not already installed GPU drivers on your system, you will need to do so now. This can be done by running the following command:Ģ) Install GPU drivers (if not already installed) The first step is to update the system’s package manager index so that it is aware of the latest packages available for installation. Just follow the below steps and you should be done in no time.ġ) Update your system’s package manager index Installing TensorFlow-GPU with CUDA 10.2 is easy. Verify your installation by opening a Python shell and importing TensorFlow: import tensorflow as tf Install TensorFlow-GPU from PyPI: pip install tensorflow-gpu=2.3.0ĥ. Install the driver and then reboot your computer.Ĥ. Go to the NVidia website and download the CUDA 10.2 driver for your graphics card.ģ. Check your graphic card is CUDA 10.2 compatible.Ģ. Follow the steps below to install the correct driver for your graphics card and then install TensorFlow-GPU.ġ. ![]() Installing TensorFlow-GPU with CUDA 10.2 is simple. In addition to the GPU driver, you will need the following software: You can check which GPUs are compatible with CUDA on the NVIDIA website. ![]() ![]() TensorFlow-GPU also requires a GPU driver compatible with CUDA 10.2. TensorFlow-GPU requires a CUDA-capable graphics processing unit (GPU) and is supported on Linux, macOS, and Windows systems. In this guide, we’ll show you how to install TensorFlow-GPU with CUDA 10.2 on your Ubuntu 18.04 machine. TensorFlow is a powerful open-source software library for data analysis and machine learning.
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