How Do I Deploy the NVIDIA/CUDA Docker Image on AWS EC2 With TypeScript?

Introduction

This guide provides a step-by-step process for deploying an NVIDIA/CUDA Docker image on an AWS EC2 instance using Pulumi and TypeScript. The guide aims to help you set up an EC2 instance, configure it to run Docker, and pull the NVIDIA/CUDA Docker image. This setup is particularly useful for utilizing GPU capabilities on AWS for computational tasks.

import * as pulumi from "@pulumi/pulumi";
import * as aws from "@pulumi/aws";

// Create a new security group for the EC2 instance
const securityGroup = new aws.ec2.SecurityGroup("cuda-security-group", {
    description: "Allow SSH and HTTP access",
    ingress: [
        { protocol: "tcp", fromPort: 22, toPort: 22, cidrBlocks: ["0.0.0.0/0"] }, // SSH
        { protocol: "tcp", fromPort: 80, toPort: 80, cidrBlocks: ["0.0.0.0/0"] }, // HTTP
    ],
});

// Create a new EC2 instance
const instance = new aws.ec2.Instance("cuda-instance", {
    instanceType: "p2.xlarge", // Instance type with GPU support
    ami: "ami-0c55b159cbfafe1f0", // Amazon Linux 2 AMI (HVM), SSD Volume Type
    securityGroups: [securityGroup.name],
    userData: `#!/bin/bash
sudo yum update -y
sudo amazon-linux-extras install docker
sudo service docker start
sudo usermod -a -G docker ec2-user
sudo docker run --gpus all nvidia/cuda:11.0-base nvidia-smi
`,
    tags: {
        Name: "cuda-instance",
    },
});

// Export the public IP of the instance
export const publicIp = instance.publicIp;
export const publicDns = instance.publicDns;

Key Points:

Security Group: We created a security group to allow SSH and HTTP access to the EC2 instance.
EC2 Instance: We launched an EC2 instance of type p2.xlarge which has GPU support.
User Data Script: The script installs Docker, starts the Docker service, adds the ec2-user to the Docker group, and runs the NVIDIA/CUDA Docker image.

Summary:

In this guide, we successfully deployed an NVIDIA/CUDA Docker image on an AWS EC2 instance using Pulumi and TypeScript. The process involved setting up an EC2 instance with GPU support, configuring Docker, and running the NVIDIA/CUDA Docker image. This setup enables you to leverage AWS’s GPU capabilities for enhanced computational tasks.

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