We recently published a technical document showing how to install NVIDIA drivers on a G4DN instance on AWS, where we covered not only how to install the NVIDIA GPU drivers but also how to make sure to get CUDA working for any ML work.
In this document we are going to run one of the most used generative AI models, Stable Diffusion, on Ubuntu on AWS for research and development purposes.
According to AWS, “G4dn instances, powered by NVIDIA T4 GPUs, are the lowest cost GPU-based instances in the cloud for machine learning inference and small scale training. (…) optimized for applications using NVIDIA libraries such as CUDA, CuDNN, and NVENC.”
G4DN instances come in different configurations:
| Instance type | vCPUs | RAM | GPUs |
| g4dn.xlarge | 4 | 16 | 1 |
| g4dn.2xlarge | 8 | 32 | 1 |
| g4dn.4xlarge | 16 | 64 | 1 |
| g4dn.8xlarge | 32 | 128 | 1 |
| g4dn.12xlarge | 48 | 192 | 4 |
| g4dn.16xlarge | 64 | 256 | 1 |
| g4dn.metal | 96 | 384 | 8 |
For this exercise, we will be using the g4dn.xlarge instance, since we need only 1 GPU, and with 4 vCPUs and 16GB of RAM, it will provide…
