Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Add Ubuntu 24.04 support. #554

Closed
wants to merge 1 commit into from
Closed

Add Ubuntu 24.04 support. #554

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
33 changes: 33 additions & 0 deletions _notices/rsn0041.md
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,33 @@
---
layout: notice
parent: RAPIDS Support Notices
grand_parent: RAPIDS Notices
nav_exclude: true
notice_type: rsn
# Update meta-data for notice
notice_id: 41 # should match notice number
notice_pin: false # set to true to pin to notice page
title: "Support for Ubuntu 24.04 in v24.12"
notice_author: RAPIDS Ops
notice_status: In Progress
notice_status_color: yellow
# 'notice_status' and 'notice_status_color' combinations:
# "Proposal" - "blue"
# "Completed" - "green"
# "Review" - "purple"
# "In Progress" - "yellow"
# "Closed" - "red"
notice_topic: Platform Support Change
notice_rapids_version: "v24.12"
notice_created: 2024-10-21
# 'notice_updated' should match 'notice_created' until an update is made
notice_updated: 2024-10-21
---

## Overview

RAPIDS is planning GA support for `Ubuntu 24.04` in its `v24.12` release.

## Impact

RAPIDS now tests Rocky Linux 8, Ubuntu 20.04, Ubuntu 22.04, and Ubuntu 24.04 in continuous integration.
20 changes: 10 additions & 10 deletions install/index.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -68,13 +68,13 @@ If conda has incorrectly identified the CUDA driver, you can [override by settin
### **Docker Issues**
<i class="fas fa-exclamation-triangle"></i> RAPIDS `23.08` brought significant Docker changes. <br/>
To learn more about these changes, please see the [RAPIDS Container README](https://hub.docker.com/r/rapidsai/base){: target="_blank"}. Some key notes below:
- `Development` images are no longer being published, in the coming releases RAPIDS will roll out [Dev Containers](https://code.visualstudio.com/docs/devcontainers/containers){: target="_blank"} for development
- `Development` images are no longer being published, RAPIDS now uses [Dev Containers](https://code.visualstudio.com/docs/devcontainers/containers){: target="_blank"} for development
- See cuSpatial for an example and information on [RAPIDS' usage of Dev Containers](https://github.com/rapidsai/cuspatial/tree/main/.devcontainer){: target="_blank"}
- All images are Ubuntu-based
- CUDA 11.2 images are Ubuntu `20.04`
- All other images are Ubuntu `22.04`
- CUDA 12.5+ images use Ubuntu 24.04
- All other images use Ubuntu 22.04
- All images are multiarch (x86_64 and ARM)
- The `Base` image starts in an ipython shell
- The `base` image starts in an ipython shell
- To run bash commands inside the ipython shell prefix the command with `!`
- To run the image without the ipython shell add `/bin/bash` to the end of the `docker run` command
- For a full list of changes please see this [RAPIDS Docker Issue](https://github.com/rapidsai/docker/issues/539){: target="_blank"}
Expand Down Expand Up @@ -132,9 +132,9 @@ All provisioned systems need to be RAPIDS capable. Here's what is required:
- <i class="fas fa-exclamation-triangle"></i> Pascal™ GPU support was [removed in 24.02](https://docs.rapids.ai/notices/rsn0034/). Compute capability 7.0+ is required for RAPIDS 24.02 and later.

<i class="fas fa-desktop"></i> **OS:** One of the following OS versions:
- <i class="fas fa-check-circle"></i> Ubuntu 20.04/22.04 or Rocky Linux 8 with <code>gcc/++</code> 9.0+
- <i class="fas fa-check-circle"></i> Ubuntu 20.04/22.04/24.04 or Rocky Linux 8 with <code>gcc/++</code> 9.0+
- <i class="fas fa-check-circle"></i> Windows 11 using a [WSL2 specific install](#wsl2)
- <i class="fas fa-check-circle"></i> RHEL 7/8 support is provided through Rocky Linux 8 builds/installs
- <i class="fas fa-check-circle"></i> RHEL 8 support is provided through Rocky Linux 8 builds/installs

<i class="fas fa-download text-purple"></i> **CUDA & NVIDIA Drivers:** One of the following supported versions:
{: .no-tb-margins }
Expand Down Expand Up @@ -283,7 +283,7 @@ Windows users can now tap into GPU accelerated data science on their local machi

### **WSL2 Additional Prerequisites**

<i class="fas fa-desktop text-white"></i> **OS:** Windows 11 with Ubuntu 22.04 instance for WSL2. <br/>
<i class="fas fa-desktop text-white"></i> **OS:** Windows 11 with Ubuntu instance for WSL2 (minimum version 20.04). <br/>
<i class="fas fa-info-circle text-white"></i> **WSL Version:** WSL2 (WSL1 not supported). <br/>
<i class="fas fa-microchip text-white"></i> **GPU:** GPUs with [Compute Capability](https://developer.nvidia.com/cuda-gpus){: target="_blank"} 7.0 or higher (16GB+ GPU RAM is recommended).

Expand All @@ -309,7 +309,7 @@ Windows users can now tap into GPU accelerated data science on their local machi

### **WSL2 Conda Install (Preferred Method)**

1. Install WSL2 and the Ubuntu 22.04 package [using Microsoft's instructions](https://docs.microsoft.com/en-us/windows/wsl/install){: target="_blank"}.
1. Install WSL2 and the Ubuntu distribution [using Microsoft's instructions](https://docs.microsoft.com/en-us/windows/wsl/install){: target="_blank"}.
2. Install the [latest NVIDIA Drivers](https://www.nvidia.com/download/index.aspx){: target="_blank"} on the Windows host.
3. Log in to the WSL2 Linux instance.
4. Install Conda in the WSL2 Linux Instance using our [Conda instructions](#conda).
Expand All @@ -325,7 +325,7 @@ print(cudf.Series([1, 2, 3]))

### **WSL2 Docker Desktop Install**

1. Install WSL2 and the Ubuntu 22.04 package [using Microsoft's instructions](https://docs.microsoft.com/en-us/windows/wsl/install){: target="_blank"}.
1. Install WSL2 and the Ubuntu distribution [using Microsoft's instructions](https://docs.microsoft.com/en-us/windows/wsl/install){: target="_blank"}.
2. Install the [latest NVIDIA Drivers](https://www.nvidia.com/download/index.aspx){: target="_blank"} on the Windows host.
3. Install latest Docker Desktop for Windows
4. Log in to the WSL2 Linux instance.
Expand All @@ -341,7 +341,7 @@ print(cudf.Series([1, 2, 3]))

### **WSL2 pip Install**

1. Install WSL2 and the Ubuntu 22.04 package [using Microsoft's instructions](https://docs.microsoft.com/en-us/windows/wsl/install){: target="_blank"}.
1. Install WSL2 and the Ubuntu distribution [using Microsoft's instructions](https://docs.microsoft.com/en-us/windows/wsl/install){: target="_blank"}.
2. Install the [latest NVIDIA Drivers](https://www.nvidia.com/download/index.aspx){: target="_blank"} on the Windows host.
3. Log in to the WSL2 Linux instance.
4. Follow [this helpful developer guide](https://docs.nvidia.com/cuda/wsl-user-guide/index.html#cuda-support-for-wsl2){: target="_blank"} and then install the WSL-specific [CUDA 11](https://developer.nvidia.com/cuda-11-8-0-download-archive?target_os=Linux&target_arch=x86_64&Distribution=WSL-Ubuntu&target_version=2.0&target_type=deb_local){: target="_blank"} or [CUDA 12](https://developer.nvidia.com/cuda-downloads?target_os=Linux&target_arch=x86_64&Distribution=WSL-Ubuntu&target_version=2.0&target_type=deb_local){: target="_blank"} Toolkit without drivers into the WSL2 instance.
Expand Down