123 lines
4.4 KiB
Markdown
123 lines
4.4 KiB
Markdown
<h1> GPU Support </h1>
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<h2> Table of Contents </h2>
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- [Introduction](#introduction)
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- [Filter and Reserve a GPU Node](#filter-and-reserve-a-gpu-node)
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- [Filter Nodes](#filter-nodes)
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- [Reserve a Node](#reserve-a-node)
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- [Deploy a VM with GPU](#deploy-a-vm-with-gpu)
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- [Install the GPU Driver](#install-the-gpu-driver)
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- [AMD Driver](#amd-driver)
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- [Nvidia Driver](#nvidia-driver)
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- [With an AI Model](#with-an-ai-model)
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- [Troubleshooting](#troubleshooting)
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- [GPU Support Links](#gpu-support-links)
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***
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## Introduction
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This section covers the essential information to deploy a node with a GPU. We also provide links to other parts of the manual covering GPU support.
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To use a GPU on the TFGrid, users need to rent a dedicated node. Once they have rented a dedicated node equipped with a GPU, users can deploy workloads on their dedicated GPU node.
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## Filter and Reserve a GPU Node
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You can filter and reserve a GPU node using the [Dedicated Nodes section](dashboard@@node_finder) of the **ThreeFold Dashboard**.
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### Filter Nodes
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* Filter nodes using the vendor name
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* In **Filters**, select **GPU's vendor name**
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* A new window will appear below named **GPU'S VENDOR NAME**
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* Write the name of the vendor desired (e.g. **nvidia**, **amd**)
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* Filter nodes using the device name
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* In **Filters**, select **GPU's device name**
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* A new window will appear below named **GPU'S DEVICE NAME**
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* Write the name of the device desired (e.g. **GT218**)
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### Reserve a Node
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When you have decided which node to reserve, click on **Reserve** under the column **Actions**. Once you've rented a dedicated node that has a GPU, you can deploy GPU workloads.
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## Deploy a VM with GPU
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Now that you've reserverd a dedicated GPU node, it's time to deploy a VM to make use of the GPU! There are many ways to proceed. You can use the [Dashboard](fullvm.md), [Go](developers@@grid3_go_gpu), [Terraform](terraform_gpu_support.md), etc.
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For example, deploying a VM with GPU on the Dashboard is easy. Simply set the GPU option and make sure to select your dedicated node, as show here:
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## Install the GPU Driver
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Once you've deployed a VM with GPU, you want to SSH into the VM and install the GPU driver.
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- SSH to the VM and get your system updated
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```bash
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dpkg --add-architecture i386
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apt-get update
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apt-get dist-upgrade
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reboot
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```
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- Find your Driver installer
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- [AMD driver](https://www.amd.com/en/support/linux-drivers)
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- [Nvidia driver](https://www.nvidia.com/download/index.aspx)
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- You can see the node card details on the ThreeFold Dashboard or by using the following command lines:
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```bash
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lspci | grep VGA
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lshw -c video
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```
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### AMD Driver
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- Download the GPU driver using `wget`
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- For example: `wget https://repo.radeon.com/amdgpu-install/23.30.2/ubuntu/focal/amdgpu-install_5.7.50702-1_all.deb`
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- Install the GPU driver using `apt-get`. Make sure to update `<VERSION>`.
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```bash
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apt-get install ./amdgpu-install_<VERSION>.deb
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amdgpu-install --usecase="dkms,graphics,opencl,hip,rocm,rocmdev,opencl,hiplibsdk,mllib,mlsdk" --opencl=rocr --vulkan=pro --opengl=mesa
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```
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- To verify that the GPU is properly installed, use the following command lines:
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```bash
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rocm-smi
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rocminfo
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```
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- You should something like this:
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### Nvidia Driver
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For Nvidia, you can follow [those steps](https://linuxize.com/post/how-to-nvidia-drivers-on-ubuntu-20-04/#installing-the-nvidia-drivers-using-the-command-line).
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- To verify that the GPU is properly installed, you can use `nvidia-smi`. You should something like this:
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### With an AI Model
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You can also try this [AI model](https://github.com/invoke-ai/InvokeAI#getting-started-with-invokeai) to install your driver.
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## Troubleshooting
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Here are some useful links to troubleshoot your GPU installation.
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- [Steps to install the driver](https://amdgpu-install.readthedocs.io/en/latest/index.html)
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- Changing kernel version
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- [Link 1](https://linux.how2shout.com/how-to-change-default-kernel-in-ubuntu-22-04-20-04-lts/)
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- [Link 2](https://gist.github.com/chaiyujin/c08e59752c3e238ff3b1a5098322b363)
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> Note: It is recommended to use Ubuntu 22.04.2 LTS (GNU/Linux 5.18.13-051813-generic x86_64)
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## GPU Support Links
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You can consult the [GPU Table of Contents](gpu_toc.md) to see all available GPU support links on the ThreeFold Manual. |