Add SDK Manager and updated CUDA install options (#547)

Co-authored-by: Bradley Dice <bdice@bradleydice.com>
Co-authored-by: James Lamb <jlamb@nvidia.com>
Co-authored-by: jakirkham <jakirkham@gmail.com>

install/index.md

@@ -24,7 +24,9 @@ RAPIDS has several methods for installation, depending on the preferred environm
 - [Conda](#conda)
 - [Docker](#docker)
 - [pip](#pip)
+- [SDK Manager](#sdkm)
 - [Windows WSL2](#wsl2)
+  - [SDK Manager](#wsl2-sdkm)
   - [Conda](#wsl2-conda)
   - [Docker](#wsl2-docker)
   - [pip](#wsl2-pip)
@@ -154,7 +156,7 @@ All provisioned systems need to be RAPIDS capable. Here's what is required:
 
  **Note**: RAPIDS is tested with and officially supports the versions listed above. Newer CUDA and driver versions may also work with RAPIDS. See [CUDA compatibility](https://docs.nvidia.com/deploy/cuda-compatibility/index.html) for details.
 
-## **CUDA 12 Support**
+## **CUDA Support**
 
 ### **Docker and Conda**
 
@@ -185,8 +187,7 @@ If you do not have access to GPU hardware, there are several cloud service provi
 
 Several services also offer **free and limited** trials with GPU resources:
 - [Amazon SageMaker Studio Lab](https://studiolab.sagemaker.aws/)
-- [Google CoLab w/ pip](https://colab.research.google.com/drive/13sspqiEZwso4NYTbsflpPyNFaVAAxUgr)
-- [Google CoLab w/ Conda](https://colab.research.google.com/drive/1TAAi_szMfWqRfHVfjGSqnGVLr_ztzUM9)
+- [Google Colab w/ pip](https://nvda.ws/3XEO6hK)
 - [PaperSpace](https://www.paperspace.com/gpu-cloud)
 
 <hr/>
@@ -280,6 +281,19 @@ RAPIDS pip packages are available for CUDA 11 and CUDA 12 on the NVIDIA Python P
 <i class="fas fa-info-circle"></i> **glibc version:** x86_64 wheels require glibc >= 2.17. <br/>
 <i class="fas fa-info-circle"></i> **glibc version:** ARM architecture (aarch64) wheels require glibc >= 2.32 (only ARM Server Base System Architecture is supported).
 
+<br/>
+<div id="sdkm"></div>
+
+## **SDK Manager (Ubuntu Only)**
+[NVIDIA SDK Manager](https://developer.nvidia.com/sdk-manager) gives a users a Graphical User Interface (GUI) option to install RAPIDS.  It also attempts to fix any environment issues before installing RAPIDS or updating RAPIDS, making it ideal for new Linux users.
+1. Download [SDK Manager's Ubuntu version from their website](https://developer.nvidia.com/sdk-manager){: target="_blank"} (requires sign up or login to NVIDIA's Developer community).  Do not install yet.  It is assumed that your home directory's `Downloads` folder is where the `.deb` file will be stored.  If not, please move `sdkmanager_[version]-[build#]_amd64.deb` file to your current Download folder.
+2. Install and run SDK Manager [using the installation guide here](https://docs.nvidia.com/sdk-manager/download-run-sdkm/index.html){: target="_blank"}. For Ubuntu, use the following commands:
+```bash
+sudo apt install ./sdkmanager_[version]-[build#]_amd64.deb
+sdkmanager
+```
+3. Sign in when asked, and follow SDK Manager's [RAPIDS installation instructions](https://docs.nvidia.com/sdk-manager/install-with-sdkm-rapids/index.html){: target="_blank"}.
+
 
 <br/>
 <div id="wsl2"></div>
@@ -310,10 +324,31 @@ Windows users can now tap into GPU accelerated data science on their local machi
 
 <i class="fas fa-info-circle text-white"></i> When installing with Docker Desktop, if the container pull command is successful, but the run command hangs indefinitely, [ensure you're on Docker Desktop >= 4.18](https://docs.docker.com/desktop/release-notes/){: target="_blank"}.
 
+<br/>
+<div id="wsl2-sdkm"></div>
+
+### **WSL2 SDK Manager Install**
+[NVIDIA's SDK Manager](https://developer.nvidia.com/sdk-manager){: target="_blank"} gives Windows users a Graphical User Interface (GUI) option to install RAPIDS. It also attempts to fix any environment issues before installing RAPIDS or updating RAPIDS, making it ideal for new WSL users.
+1. Install the [latest NVIDIA Drivers](https://www.nvidia.com/en-us/drivers/){: target="_blank"} on the Windows host.
+2. Download [SDK Manager's Ubuntu version from their website](https://developer.nvidia.com/sdk-manager){: target="_blank"} (requires sign up or login to NVIDIA's Developer community).  Do not install yet.  The rest of the instructions assume that your home directory's `Downloads` folder is where the `.deb` file will be stored.  If this is not the case, please change the directory, as needed, for your system.
+3. Install or update WSL2 and the Ubuntu 22.04 or Ubuntu 24.04 package [using Microsoft's instructions](https://docs.microsoft.com/en-us/windows/wsl/install){: target="_blank"}. To install Ubuntu 24.04 from the command line, use this command:
+```bash
+wsl --install -d Ubuntu-24.04
+```
+This will install and start Ubuntu in your Windows host system using WSL2.  Make your **sudo** password memorable as you will need it in the next two steps.
+4. Install and run SDK Manager inside Ubuntu by pasting this into your command line.  This command will navigate to your Windows users's `Downloads` folder, from your WSL2 instance, and install the latest SDK Manager `.deb` file that you had downloaded. You will have to enter the sudo password you created when you installed Ubuntu.
+```bash
+sudo apt update && sudo apt install wslu -y
+cd "$(wslpath -au "$(cmd.exe /c 'echo %USERPROFILE%' | tr -d '\r')")/Downloads"
+sudo apt install "$(ls -t ./sdkmanager_*_amd64.deb | head -n 1)" -y
+sdkmanager
+```
+5. Sign in when asked, and [follow SDK Manager's RAPIDS installation instructions here](https://docs.nvidia.com/sdk-manager/install-with-sdkm-rapids/index.html){: target="_blank"}.
+
 <br/>
 <div id="wsl2-conda"></div>
 
-### **WSL2 Conda Install (Preferred Method)**
+### **WSL2 Conda Install**
 
 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.