Development System
The table below lists the system requirements for UCS Tools for development:
Platform |
x86_64 |
OS |
Ubuntu 22.04 |
GPU |
CUDA-capable GPU, iGPU 1,2 |
Helm |
3.11 |
1 (Alpha) With remote access only
2 (Alpha) Need Vulkan support (Intel Iris Graphics 540 or later)
These instructions require having Ubuntu Server LTS 22.04 on your system.
Install the Ubuntu Operating System
The Ubuntu Server can be downloaded from http://cdimage.ubuntu.com/releases/22.04/release/.
For more information on installing Ubuntu server refer to the Ubuntu Server Installation Guide.
Install CUDA Drivers
CUDA installation instructions are available from https://developer.nvidia.com/cuda-downloads?target_os=Linux&target_arch=x86_64&Distribution=Ubuntu&target_version=22.04&target_type=deb_local.
Once the NVIDIA Drivers installed, please reboot the system and run the below command to validate NVIDIA drivers are loaded:
nvidia-smiExpected Output:
+---------------------------------------------------------------------------------------+ | NVIDIA-SMI 535.104.05 Driver Version: 535.104.05 CUDA Version: 12.2 | |-----------------------------------------+----------------------+----------------------+ | GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |=========================================+======================+======================| | 0 NVIDIA GeForce RTX 4090 On | 00000000:65:00.0 Off | Off | | 0% 30C P8 5W / 450W | 133MiB / 24564MiB | 0% Default | | | | N/A | +-----------------------------------------+----------------------+----------------------+ +---------------------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=======================================================================================| | 0 N/A N/A 1119 G /usr/lib/xorg/Xorg 107MiB | | 0 N/A N/A 1239 G /usr/bin/gnome-shell 13MiB | +---------------------------------------------------------------------------------------+
Install Docker CE
Set up the repository and update the apt package index:
$ sudo apt-get update
Install packages to allow apt to use a repository over HTTPS:
$ sudo apt-get install -y \ apt-transport-https \ ca-certificates \ curl \ gnupg-agent \ software-properties-common
Add Docker’s official GPG key:
$ curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
Verify that you now have the key with the fingerprint 9DC8 5822 9FC7 DD38 854A E2D8 8D81 803C 0EBF CD88 by searching for the last 8 characters of the fingerprint:
$ sudo apt-key fingerprint 0EBFCD88 pub rsa4096 2017-02-22 [SCEA] 9DC8 5822 9FC7 DD38 854A E2D8 8D81 803C 0EBF CD88 uid [ unknown] Docker Release (CE deb) <docker@docker.com> sub rsa4096 2017-02-22 [S]
Use the following command to set up the stable repository:
$ sudo add-apt-repository \ "deb [arch=amd64] https://download.docker.com/linux/ubuntu \ $(lsb_release -cs) \ stable"
Install Docker Engine - Community Update the apt package index:
$ sudo apt-get update
Install Docker Engine:
$ sudo apt-get install -y docker-ce docker-ce-cli containerd.io
Verify that Docker Engine - Community is installed correctly by running the hello-world image:
$ sudo docker run hello-world
More information on how to install Docker can be found at https://docs.docker.com/install/linux/docker-ce/ubuntu/.
Install NVIDIA Container Toolkit
Setup the package repository:
distribution=$(. /etc/os-release;echo $ID$VERSION_ID) \ && curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg \ && curl -s -L https://nvidia.github.io/libnvidia-container/$distribution/libnvidia-container.list | \ sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | \ sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
Update the package index:
sudo apt update
Install NVIDIA Container Toolkit:
sudo apt-get install -y nvidia-docker2
Update the Docker Default Runtime.
Edit the docker daemon configuration to add the following line and save the file:
"default-runtime" : "nvidia"Example:
$ sudo nano /etc/docker/daemon.json { "runtimes": { "nvidia": { "path": "nvidia-container-runtime", "runtimeArgs": [] } }, "default-runtime" : "nvidia" }
Now execute the below commands to restart the docker daemon:
sudo systemctl daemon-reload && sudo systemctl restart docker
Validate docker default runtime.
Execute the below command to validate docker default runtime as NVIDIA:
$ sudo docker info | grep -i runtimeOutput:
Runtimes: nvidia runc Default Runtime: nvidia
Install Helm
Execute the following command to download and install Helm 3.11.0:
wget https://get.helm.sh/helm-v3.11.0-linux-amd64.tar.gz && \
tar -zxvf helm-v3.11.0-linux-amd64.tar.gz && \
sudo mv linux-amd64/helm /usr/local/bin/helm && \
rm -rf helm-v3.11.0-linux-amd64.tar.gz linux-amd64/
Refer to the Helm 3.11.0 release notes and the Installing Helm guide for more information.