Update installation docs for CUDA 12. (#4207)

Closes #3909.

Authors:
  - Bradley Dice (https://github.com/bdice)

Approvers:
  - Brad Rees (https://github.com/BradReesWork)

URL: #4207

docs/cugraph/source/installation/getting_cugraph.md

@@ -15,7 +15,7 @@ There are 4 ways to get cuGraph packages:
 <br>
 
 ## Docker
-The RAPIDS Docker containers contain all RAPIDS packages, including all from cuGraph, as well as all required supporting packages.   To download a container, please see the [Docker Repository](https://hub.docker.com/r/rapidsai/rapidsai/), choosing a tag based on the NVIDIA CUDA version you’re running.  This provides a ready to run Docker container with example notebooks and data, showcasing how you can utilize all of the RAPIDS libraries: cuDF, cuML, and cuGraph.
+The RAPIDS Docker containers contain all RAPIDS packages, including all from cuGraph, as well as all required supporting packages. To download a RAPIDS container, please see the [Docker Hub page for rapidsai/base](https://hub.docker.com/r/rapidsai/base), choosing a tag based on the NVIDIA CUDA version you're running. Also, the [rapidsai/notebooks](https://hub.docker.com/r/rapidsai/notebooks) container provides a ready to run Docker container with example notebooks and data, showcasing how you can utilize all of the RAPIDS libraries: cuDF, cuML, and cuGraph.
 
 <br>
 
@@ -31,28 +31,38 @@ cuGraph Conda packages
  * cugraph-service-server
  * cugraph-dgl
  * cugraph-pyg
+ * cugraph-equivariant
+ * nx-cugraph
 
 Replace the package name in the example below to the one you want to install.
 
 
 Install and update cuGraph using the conda command:
 
 ```bash
-conda install -c rapidsai -c conda-forge -c nvidia cugraph cudatoolkit=11.8
+conda install -c rapidsai -c conda-forge -c nvidia cugraph cuda-version=12.0
 ```
 
-Note: This conda installation only applies to Linux and Python versions 3.8/3.10.
+Alternatively, use `cuda-version=11.8` for packages supporting CUDA 11.
+
+Note: This conda installation only applies to Linux and Python versions 3.9/3.10.
 
 <br>
 
 ## PIP
 cuGraph, and all of RAPIDS, is available via pip.
 
 ```
-pip install cugraph-cu11 --extra-index-url=https://pypi.ngc.nvidia.com
+pip install cugraph-cu12 --extra-index-url=https://pypi.ngc.nvidia.com
 ```
 
-pip packages for other packages are being worked and should be available in early 2023
+Replace `-cu12` with `-cu11` for packages supporting CUDA 11.
+
+Also available:
+ * cugraph-dgl-cu12
+ * cugraph-pyg-cu12
+ * cugraph-equivariant-cu12
+ * nx-cugraph-cu12
 
 <br>