- HOW TO INSTALL CUDA ON UBUNTU 16.04 EC2 AWS HOW TO
- HOW TO INSTALL CUDA ON UBUNTU 16.04 EC2 AWS DRIVERS
- HOW TO INSTALL CUDA ON UBUNTU 16.04 EC2 AWS UPDATE
HOW TO INSTALL CUDA ON UBUNTU 16.04 EC2 AWS UPDATE
Update the packages list and install the packages necessary to build Python: sudo apt update sudo apt install build-essential zlib1g-dev libncurses5-dev libgdbm-dev libnss3-dev libssl-dev libreadline-dev libffi-dev libsqlite3-dev wget libbz2-devĭownload the latest release’s source code from the Python download pageĪt the time of writing this article, the latest release is 3.8.0.
HOW TO INSTALL CUDA ON UBUNTU 16.04 EC2 AWS HOW TO
In this section, we’ll explain how to compile Python 3.8 from the source. Installing Python 3.8 on Ubuntu from Source # Verify that the installation was successful by typing: python3.8 -version Python 3.8.0Īt this point, Python 3.8 is installed on your Ubuntu system, and you can start using it. Once the repository is enabled, install Python 3.8 with: sudo apt install python3.8 When prompted press Enter to continue: Press to continue or Ctrl-c to cancel adding it. To update the packages list and install the prerequisites: sudo apt update sudo apt install software-properties-commonĪdd the deadsnakes PPA to your system’s sources list: sudo add-apt-repository ppa:deadsnakes/ppa Run the following commands as root or user with sudo access Is a relatively straightforward process and takes only a few minutes: Installing Python 3.8 on Ubuntu with Apt # The same steps apply for Ubuntu 16.04 and any Ubuntu-based distribution, including Kubuntu, Linux Mint, and Elementary OS. PPA, and the second one is by building from the source code. The first option is to install the deb package from the deadsnakes In this tutorial, we’ll cover two different ways to install Python 3.8 on Ubuntu 18.04. Python 3.8 is not available in Ubuntu’s default repositories.
It includes many new features such as assignment expressions, positional-only parameters, f-strings support, and more Python 3.8 is the latest major release of the Python language. It can be used to build all kinds of applications, from simple scrips to complex machine learning algorithms. Python is quite a versatile programming language. With its simple and easy to learn syntax, Python is a popular choice for beginners and experienced developers. Moreover, if you don’t want to run as sudo then you need to add the EC2 user to the docker group sudo usermod -a -G docker ubuntu (see the AWS guide for more details).Python is one of the most widely used programming languages in the world. Note: If you run the command for the first time, it will pull the image first. Now we can use nvidia-docker to test if everything is working as expected: $ sudo nvidia-docker run -rm nvidia/cuda nvidia-smi
Install nvidia-docker and its plugin: $ wget -P /tmp $ sudo dpkg -i /tmp/nvidia-docker_1.0.1-1_b & rm /tmp/nvidia-docker_1.0.1-1_b 3.
Install the Docker Community Edition (check out the official guide for more information about the installation): $ curl -fsSL | sudo apt-key add - # Verify that the key fingerprint is 9DC8 5822 9FC7 DD38 854A E2D8 8D81 803C 0EBF CD88 $ sudo apt-key fingerprint 0EBFCD88 $ sudo add-apt-repository \ "deb \ $(lsb_release -cs) \ stable" $ sudo apt-get update $ sudo apt-get install -y docker-ce NVIDIA-Docker Update the graphic driver: $ sudo add-apt-repository ppa:graphics-drivers/ppa -y $ sudo apt-get update $ sudo apt-get install -y nvidia-375 nvidia-settings nvidia-modprobe Docker
HOW TO INSTALL CUDA ON UBUNTU 16.04 EC2 AWS DRIVERS
Update the NVIDIA drivers and install docker+nvidia-docker NVIDIA Driver Launch the cluster and assign an EC2 key pair.