Adapt cuGraph examples to new API (#9541)

Updates the cuGraph examples to use the new non-dask API. Adds a new
multinode cuGraph example.

---------

Co-authored-by: rusty1s <matthias.fey@tu-dortmund.de>

CHANGELOG.md

@@ -38,6 +38,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Changed
 
+- Adapt `cugraph` examples to its new API ([#9541](https://github.com/pyg-team/pytorch_geometric/pull/9541))
 - Allow optional but untyped tensors in `MessagePassing` ([#9494](https://github.com/pyg-team/pytorch_geometric/pull/9494))
 - Added support for modifying `filename` of the stored partitioned file in `ClusterLoader` ([#9448](https://github.com/pyg-team/pytorch_geometric/pull/9448))
 - Support other than two-dimensional inputs in `AttentionalAggregation` ([#9433](https://github.com/pyg-team/pytorch_geometric/pull/9433))

examples/multi_gpu/README.md

@@ -9,8 +9,9 @@
 | [`distributed_sampling_multinode.py`](./distributed_sampling_multinode.py)         | multi-node  | Example for training GNNs on a homogeneous graph with neighbor sampling on multiple nodes.                                                                                                                                                                                                      |
 | [`distributed_sampling_multinode.sbatch`](./distributed_sampling_multinode.sbatch) | multi-node  | Example for submitting a training job to a Slurm cluster using [`distributed_sampling_multi_node.py`](./distributed_sampling_multinode.py).                                                                                                                                                     |
 | [`papers100m_gcn.py`](./papers100m_gcn.py)                                         | single-node | Example for training GNNs on the `ogbn-papers100M` homogeneous graph w/ ~1.6B edges.                                                                                                                                                                                                            |
-| [`papers100m_gcn_cugraph.py`](./papers100m_gcn_cugraph.py%60)                      | single-node | Example for accelerating GNN training on `ogbn-papers100M` using [CuGraph](...).                                                                                                                                                                                                                |
+| [`papers100m_gcn_cugraph.py`](./papers100m_gcn_cugraph.py)                         | single-node | Example for training GNNs on `ogbn-papers100M` using [CuGraph](...).                                                                                                                                                                                                                            |
 | [`papers100m_gcn_multinode.py`](./papers100m_gcn_multinode.py)                     | multi-node  | Example for training GNNs on a homogeneous graph on multiple nodes.                                                                                                                                                                                                                             |
+| [`papers100m_gcn_cugraph_multinode.py`](./papers100m_gcn_cugraph_multinode.py)     | multi-node  | Example for training GNNs on a homogeneous graph on multiple nodes using [CuGraph](...).                                                                                                                                                                                                        |
 | [`pcqm4m_ogb.py`](./pcqm4m_ogb.py)                                                 | single-node | Example for training GNNs for a graph-level regression task.                                                                                                                                                                                                                                    |
 | [`mag240m_graphsage.py`](./mag240m_graphsage.py)                                   | single-node | Example for training GNNs on a large heterogeneous graph.                                                                                                                                                                                                                                       |
 | [`taobao.py`](./taobao.py)                                                         | single-node | Example for training link prediction GNNs on a heterogeneous graph.                                                                                                                                                                                                                             |