more docs changes

docs/cugraph/source/installation/getting_cugraph.md

@@ -45,7 +45,7 @@ conda install -c rapidsai -c conda-forge -c nvidia cugraph cuda-version=12.0
 
 Alternatively, use `cuda-version=11.8` for packages supporting CUDA 11.
 
-Note: This conda installation only applies to Linux and Python versions 3.9/3.10/3.11.
+Note: This conda installation only applies to Linux and Python versions 3.10/3.11.
 
 <br>
 

docs/cugraph/source/tutorials/basic_cugraph.md

@@ -5,7 +5,7 @@
 CuGraph is part of [Rapids](https://docs.rapids.ai/user-guide) and has the following system requirements:
  * NVIDIA GPU, Volta architecture or later, with [compute capability](https://developer.nvidia.com/cuda-gpus) 7.0+
  * CUDA 11.2, 11.4, 11.5, 11.8, 12.0 or 12.2
- * Python version 3.9, 3.10, or 3.11
+ * Python version 3.10 or 3.11
  * NetworkX >= version 3.3 or newer in order to use use [NetworkX Configs](https://networkx.org/documentation/stable/reference/backends.html#module-networkx.utils.configs) **This is required for use of nx-cuGraph, [see below](#cugraph-using-networkx-code).**
 
 ## Installation

notebooks/README.md

@@ -67,13 +67,13 @@ The easiest way to run the notebooks is to get the latest [rapidsai/notebooks](h
 
 For example, get the latest (as of writing the document) nightly image (`a` after the version number indicates that an image is nightly) with cuda 12.0 using
 ```sh
-docker pull rapidsai/notebooks:24.10a-cuda12.0-py3.9
+docker pull rapidsai/notebooks:24.10a-cuda12.0-py3.10
 ```
 
 And, then run a container based on the image using
 
 ```sh
-docker run --rm  -it --pull always --gpus all --shm-size=1g --ulimit memlock=-1 --ulimit stack=67108864   -p 8888:8888 rapidsai/notebooks:24.10a-cuda12.0-py3.9
+docker run --rm  -it --pull always --gpus all --shm-size=1g --ulimit memlock=-1 --ulimit stack=67108864   -p 8888:8888 rapidsai/notebooks:24.10a-cuda12.0-py3.10
 ```
 You are all set. Run and edit cugraph notebooks from a browser at url
 http://127.0.0.1:8888/lab/tree/cugraph/cugraph_benchmarks
@@ -89,8 +89,8 @@ ssh -L  127.0.0.1:8888:127.0.0.1:8888 [USER_NAME@][REMOTE_HOST_NAME or REMOTE_HO
 and then run the container in your remote machine.
 
 ```sh
-docker pull rapidsai/notebooks:24.10a-cuda12.0-py3.9
-docker run --rm  -it --pull always --gpus all --shm-size=1g --ulimit memlock=-1 --ulimit stack=67108864 -p 8888:8888 rapidsai/notebooks:24.10a-cuda12.0-py3.9
+docker pull rapidsai/notebooks:24.10a-cuda12.0-py3.10
+docker run --rm  -it --pull always --gpus all --shm-size=1g --ulimit memlock=-1 --ulimit stack=67108864 -p 8888:8888 rapidsai/notebooks:24.10a-cuda12.0-py3.10
 ```
 
 You can run and edit cugraph notebooks at url http://127.0.0.1:8888/lab/tree/cugraph/cugraph_benchmarks as if they are running locally.

notebooks/demo/nx_cugraph_demo.ipynb

@@ -20,7 +20,7 @@
     "Using `nx-cugraph` with this notebook requires the following: \n",
     "- NVIDIA GPU, Pascal architecture or later\n",
     "- CUDA 11.2, 11.4, 11.5, 11.8, or 12.0\n",
-    "- Python versions 3.9, 3.10, or 3.11\n",
+    "- Python versions 3.10 or 3.11\n",
     "- NetworkX >= version 3.2\n",
     "  - _NetworkX 3.0 supports dispatching and is compatible with `nx-cugraph`, but this notebook will demonstrate features added in 3.2_\n",
     "  - At the time of this writing, NetworkX 3.2 is only available from source and can be installed by following the [development version install instructions](https://github.com/networkx/networkx/blob/main/INSTALL.rst#install-the-development-version).\n",

python/nx-cugraph/README.md

@@ -9,7 +9,7 @@ to run supported algorithms with GPU acceleration.
 nx-cugraph requires the following:
  * NVIDIA GPU, Volta architecture or later, with [compute capability](https://developer.nvidia.com/cuda-gpus) 7.0+
  * CUDA 11.2, 11.4, 11.5, 11.8, or 12.0
- * Python version 3.9, 3.10, or 3.11
+ * Python version 3.10 or 3.11
  * NetworkX >= version 3.0 (version 3.2 or higher recommended)
 
 More details about system requirements can be found in the [RAPIDS System Requirements documentation](https://docs.rapids.ai/install#system-req).