austinarmbruster / gpu-install-on-ec2

instructions for installing a gpu on an ec2 instance

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Install NVIDIA GPU on an EC2 instance with Ubuntu Server 22.04

Update and Upgrade the System:

sudo apt update && sudo apt upgrade -y
Ensure the Latest CUDA is Installed:

This will automatically install the compatible NVIDIA driver:

wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
sudo dpkg -i cuda-keyring_1.1-1_all.deb
sudo apt-get update
sudo apt-get -y install cuda

Install Docker:

Add Docker's official GPG key and set up the Docker stable repository:

sudo apt install -y apt-transport-https ca-certificates curl software-properties-common
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
sudo add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable"
sudo apt update

Install Docker CE:

sudo apt install -y docker-ce

Add your user to the Docker group to allow non-root access (you'll need to log out and back in or start a new session for this to take effect):

sudo usermod -aG docker $USER

Install NVIDIA Container Toolkit:

Set up the NVIDIA Docker repository and GPG key:

distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -
curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
sudo apt update

Install the NVIDIA Container Toolkit:

sudo apt install -y nvidia-container-toolkit

Restart Docker to apply changes:

sudo systemctl restart docker

To run text generation using Docker

model=Trelis/Llama-2-7b-chat-hf-function-calling
volume=$PWD/data # share a volume with the Docker container to avoid downloading weights every run

docker run --gpus all --shm-size 1g -p 8080:80 -v $volume:/data ghcr.io/huggingface/text-generation-inference:1.0.1 --model-id $model --quantize gptq

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instructions for installing a gpu on an ec2 instance