👁️ Overview
This article will show you the steps to take to manually enable and manage a GPU for MIG.
\uD83D\uDCD8 Instructions
Upgrade and Update
apt upgrade apt update
Get a nvidia driver version that is supported for MIG
A100 and A30 GPUs are supported starting with CUDA 11/R450 drivers.apt install nvidia-driver-525-server
525 is the tested version that is working. apt search nvidia-driver can be used to search for later versions
Enable MIG on the GPU
sudo nvidia-smi -i 0 -mig 1
Reset the gpu to complete the enabling of mig
sudo nvidia-smi --gpu-reset
You will now have to decide what size MIGs you want to use.
nvidia-smi mig -lgipwill show you the available MIG profiles and their corresponding IDs for the create step
Warning: The example below is for demonstration/illustrative purposes, make sure to decide for yourself the way you want to deploy MIG
Example:
I want two GPU instances with 10GB memory each.
nvidia-smi mig -cgi 15,15 -C
This creates 2 gpu instances of ID 15, the -C flag creates a default compute instance. (Recommended to always run -C unless you know what you need specifically)
nvidia-smi mig -lgi this will now show you the GPU instances that you’ve created.
nvidia-smi -L this will give you the MIG instance UUIDs for binding
You now have two gpu instances in which you can run CUDA applications.
To do this you can run the program with the following command:
CUDA_VISIBLE_DEVICES=MIG-d0c17ef4-4e20-5117-a3b8-5ff7e8424826 ./Application && CUDA_VISIBLE_DEVICES=MIG-221491dd-4f47-55cc-b5d6-c771c5015bd2 ./Application
It is still possible to run applications on the GPU UUID as well as the MIG UUIDs.
🔖 References
All information is taken from the NVIDIA MIG Documentation
📚 Related articles
MIG-Kubernetes - CloudKB - Confluence (atlassian.net)
Ansible for MIG - CloudKB - Confluence (atlassian.net)
Reviewer | Review period |
|---|---|
| |