Merge branch 'branch-24.12' into fetch-hll

ci/build_docs.sh

@@ -6,6 +6,10 @@ set -euo pipefail
 rapids-logger "Create test conda environment"
 . /opt/conda/etc/profile.d/conda.sh
 
+export RAPIDS_VERSION="$(rapids-version)"
+export RAPIDS_VERSION_MAJOR_MINOR="$(rapids-version-major-minor)"
+export RAPIDS_VERSION_NUMBER="$RAPIDS_VERSION_MAJOR_MINOR"
+
 rapids-dependency-file-generator \
   --output conda \
   --file-key docs \
@@ -22,35 +26,31 @@ PYTHON_CHANNEL=$(rapids-download-conda-from-s3 python)
 
 if [[ "${RAPIDS_CUDA_VERSION}" == "11.8.0" ]]; then
   CONDA_CUDA_VERSION="11.8"
-  DGL_CHANNEL="dglteam/label/cu118"
+  DGL_CHANNEL="dglteam/label/th23_cu118"
 else
   CONDA_CUDA_VERSION="12.1"
-  DGL_CHANNEL="dglteam/label/cu121"
+  DGL_CHANNEL="dglteam/label/th23_cu121"
 fi
 
 rapids-mamba-retry install \
   --channel "${CPP_CHANNEL}" \
   --channel "${PYTHON_CHANNEL}" \
   --channel conda-forge \
-  --channel pyg \
   --channel nvidia \
   --channel "${DGL_CHANNEL}" \
-  libcugraph \
-  pylibcugraph \
-  cugraph \
-  cugraph-pyg \
-  cugraph-dgl \
-  cugraph-service-server \
-  cugraph-service-client \
-  libcugraph_etl \
-  pylibcugraphops \
-  pylibwholegraph \
-  pytorch \
+  "libcugraph=${RAPIDS_VERSION_MAJOR_MINOR}.*" \
+  "pylibcugraph=${RAPIDS_VERSION_MAJOR_MINOR}.*" \
+  "cugraph=${RAPIDS_VERSION_MAJOR_MINOR}.*" \
+  "cugraph-pyg=${RAPIDS_VERSION_MAJOR_MINOR}.*" \
+  "cugraph-dgl=${RAPIDS_VERSION_MAJOR_MINOR}.*" \
+  "cugraph-service-server=${RAPIDS_VERSION_MAJOR_MINOR}.*" \
+  "cugraph-service-client=${RAPIDS_VERSION_MAJOR_MINOR}.*" \
+  "libcugraph_etl=${RAPIDS_VERSION_MAJOR_MINOR}.*" \
+  "pylibcugraphops=${RAPIDS_VERSION_MAJOR_MINOR}.*" \
+  "pylibwholegraph=${RAPIDS_VERSION_MAJOR_MINOR}.*" \
+  "pytorch>=2.3,<2.4" \
   "cuda-version=${CONDA_CUDA_VERSION}"
 
-export RAPIDS_VERSION="$(rapids-version)"
-export RAPIDS_VERSION_MAJOR_MINOR="$(rapids-version-major-minor)"
-export RAPIDS_VERSION_NUMBER="$RAPIDS_VERSION_MAJOR_MINOR"
 export RAPIDS_DOCS_DIR="$(mktemp -d)"
 
 for PROJECT in libcugraphops libwholegraph; do

ci/build_python.sh

@@ -61,7 +61,6 @@ if [[ ${RAPIDS_CUDA_MAJOR} == "11" ]]; then
     --no-test \
     --channel "${CPP_CHANNEL}" \
     --channel "${RAPIDS_CONDA_BLD_OUTPUT_DIR}" \
-    --channel pyg \
     --channel pytorch \
     --channel pytorch-nightly \
     conda/recipes/cugraph-pyg
@@ -71,7 +70,7 @@ if [[ ${RAPIDS_CUDA_MAJOR} == "11" ]]; then
     --no-test \
     --channel "${CPP_CHANNEL}" \
     --channel "${RAPIDS_CONDA_BLD_OUTPUT_DIR}" \
-    --channel dglteam \
+    --channel dglteam/label/th23_cu118 \
     --channel pytorch \
     --channel pytorch-nightly \
     conda/recipes/cugraph-dgl

ci/test_cpp.sh

@@ -8,6 +8,8 @@ cd "$(dirname "$(realpath "${BASH_SOURCE[0]}")")"/../
 
 . /opt/conda/etc/profile.d/conda.sh
 
+RAPIDS_VERSION_MAJOR_MINOR="$(rapids-version-major-minor)"
+
 rapids-logger "Generate C++ testing dependencies"
 rapids-dependency-file-generator \
   --output conda \
@@ -30,7 +32,9 @@ rapids-print-env
 
 rapids-mamba-retry install \
     --channel "${CPP_CHANNEL}" \
-    libcugraph libcugraph_etl libcugraph-tests
+    "libcugraph=${RAPIDS_VERSION_MAJOR_MINOR}.*" \
+    "libcugraph_etl=${RAPIDS_VERSION_MAJOR_MINOR}.*" \
+    "libcugraph-tests=${RAPIDS_VERSION_MAJOR_MINOR}.*"
 
 rapids-logger "Check GPU usage"
 nvidia-smi

ci/test_notebooks.sh

@@ -5,6 +5,8 @@ set -Eeuo pipefail
 
 . /opt/conda/etc/profile.d/conda.sh
 
+RAPIDS_VERSION_MAJOR_MINOR="$(rapids-version-major-minor)"
+
 rapids-logger "Generate notebook testing dependencies"
 rapids-dependency-file-generator \
   --output conda \
@@ -27,7 +29,9 @@ PYTHON_CHANNEL=$(rapids-download-conda-from-s3 python)
 rapids-mamba-retry install \
   --channel "${CPP_CHANNEL}" \
   --channel "${PYTHON_CHANNEL}" \
-  libcugraph pylibcugraph cugraph
+  "libcugraph=${RAPIDS_VERSION_MAJOR_MINOR}.*" \
+  "pylibcugraph=${RAPIDS_VERSION_MAJOR_MINOR}.*" \
+  "cugraph=${RAPIDS_VERSION_MAJOR_MINOR}.*"
 
 NBTEST="$(realpath "$(dirname "$0")/utils/nbtest.sh")"
 NOTEBOOK_LIST="$(realpath "$(dirname "$0")/notebook_list.py")"

ci/test_python.sh

@@ -8,6 +8,8 @@ cd "$(dirname "$(realpath "${BASH_SOURCE[0]}")")"/../
 
 . /opt/conda/etc/profile.d/conda.sh
 
+RAPIDS_VERSION_MAJOR_MINOR="$(rapids-version-major-minor)"
+
 rapids-logger "Generate Python testing dependencies"
 rapids-dependency-file-generator \
   --output conda \
@@ -34,12 +36,12 @@ rapids-print-env
 rapids-mamba-retry install \
   --channel "${CPP_CHANNEL}" \
   --channel "${PYTHON_CHANNEL}" \
-  libcugraph \
-  pylibcugraph \
-  cugraph \
-  nx-cugraph \
-  cugraph-service-server \
-  cugraph-service-client
+  "libcugraph=${RAPIDS_VERSION_MAJOR_MINOR}.*" \
+  "pylibcugraph=${RAPIDS_VERSION_MAJOR_MINOR}.*" \
+  "cugraph=${RAPIDS_VERSION_MAJOR_MINOR}.*" \
+  "nx-cugraph=${RAPIDS_VERSION_MAJOR_MINOR}.*" \
+  "cugraph-service-server=${RAPIDS_VERSION_MAJOR_MINOR}.*" \
+  "cugraph-service-client=${RAPIDS_VERSION_MAJOR_MINOR}.*"
 
 rapids-logger "Check GPU usage"
 nvidia-smi
@@ -151,14 +153,13 @@ if [[ "${RAPIDS_CUDA_VERSION}" == "11.8.0" ]]; then
       --channel "${CPP_CHANNEL}" \
       --channel "${PYTHON_CHANNEL}" \
       --channel conda-forge \
-      --channel dglteam/label/cu118 \
+      --channel dglteam/label/th23_cu118 \
       --channel nvidia \
-      libcugraph \
-      pylibcugraph \
-      pylibcugraphops \
-      cugraph \
-      cugraph-dgl \
-      'dgl>=1.1.0.cu*,<=2.0.0.cu*' \
+      "libcugraph=${RAPIDS_VERSION_MAJOR_MINOR}.*" \
+      "pylibcugraph=${RAPIDS_VERSION_MAJOR_MINOR}.*" \
+      "pylibcugraphops=${RAPIDS_VERSION_MAJOR_MINOR}.*" \
+      "cugraph=${RAPIDS_VERSION_MAJOR_MINOR}.*" \
+      "cugraph-dgl=${RAPIDS_VERSION_MAJOR_MINOR}.*" \
       'pytorch>=2.3,<2.4' \
       'cuda-version=11.8'
 
@@ -208,16 +209,10 @@ if [[ "${RAPIDS_CUDA_VERSION}" == "11.8.0" ]]; then
     rapids-mamba-retry install \
       --channel "${CPP_CHANNEL}" \
       --channel "${PYTHON_CHANNEL}" \
-      --channel pyg \
-      "cugraph-pyg" \
+      "cugraph-pyg=${RAPIDS_VERSION_MAJOR_MINOR}.*" \
+      "pytorch>=2.3,<2.4" \
       "ogb"
 
-    pip install \
-        pyg_lib \
-        torch_scatter \
-        torch_sparse \
-      -f ${PYG_URL}
-
     rapids-print-env
 
     rapids-logger "pytest cugraph_pyg (single GPU)"
@@ -253,7 +248,7 @@ if [[ "${RAPIDS_CUDA_VERSION}" == "11.8.0" ]]; then
       --channel "${PYTHON_CHANNEL}" \
       --channel conda-forge \
       --channel nvidia \
-      cugraph-equivariant
+      "cugraph-equivariant=${RAPIDS_VERSION_MAJOR_MINOR}.*"
     pip install e3nn==0.5.1
 
     rapids-print-env

ci/test_wheel_cugraph-dgl.sh

@@ -30,10 +30,10 @@ else
   PYTORCH_CUDA_VER=$PKG_CUDA_VER
 fi
 PYTORCH_URL="https://download.pytorch.org/whl/cu${PYTORCH_CUDA_VER}"
-DGL_URL="https://data.dgl.ai/wheels/cu${PYTORCH_CUDA_VER}/repo.html"
+DGL_URL="https://data.dgl.ai/wheels/torch-2.3/cu${PYTORCH_CUDA_VER}/repo.html"
 
 rapids-logger "Installing PyTorch and DGL"
 rapids-retry python -m pip install torch==2.3.0 --index-url ${PYTORCH_URL}
-rapids-retry python -m pip install dgl==2.0.0 --find-links ${DGL_URL}
+rapids-retry python -m pip install dgl==2.4.0 --find-links ${DGL_URL}
 
 python -m pytest python/cugraph-dgl/tests

conda/environments/all_cuda-118_arch-x86_64.yaml

@@ -4,8 +4,7 @@ channels:
 - rapidsai
 - rapidsai-nightly
 - dask/label/dev
-- pyg
-- dglteam/label/cu118
+- dglteam/label/th23_cu118
 - conda-forge
 - nvidia
 dependencies:

conda/environments/all_cuda-125_arch-x86_64.yaml

@@ -4,8 +4,7 @@ channels:
 - rapidsai
 - rapidsai-nightly
 - dask/label/dev
-- pyg
-- dglteam/label/cu118
+- dglteam/label/th23_cu118
 - conda-forge
 - nvidia
 dependencies:

conda/recipes/cugraph-dgl/meta.yaml

@@ -25,7 +25,7 @@ requirements:
     - setuptools>=61.0.0
   run:
     - cugraph ={{ version }}
-    - dgl >=1.1.0.cu*
+    - dgl >=2.4.0.th23.cu*
     - numba >=0.57
     - numpy >=1.23,<3.0a0
     - pylibcugraphops ={{ minor_version }}

conda/recipes/cugraph-pyg/meta.yaml

@@ -36,7 +36,7 @@ requirements:
     - cugraph ={{ version }}
     - pylibcugraphops ={{ minor_version }}
     - tensordict >=0.1.2
-    - pyg >=2.5,<2.6
+    - pytorch_geometric >=2.5,<2.6
 
 tests:
   imports:

dependencies.yaml

@@ -323,8 +323,7 @@ channels:
   - rapidsai
   - rapidsai-nightly
   - dask/label/dev
-  - pyg
-  - dglteam/label/cu118
+  - dglteam/label/th23_cu118
   - conda-forge
   - nvidia
 dependencies:
@@ -700,7 +699,7 @@ dependencies:
           - &pytorch_conda pytorch>=2.3,<2.4.0a0
           - pytorch-cuda==11.8
           - &tensordict tensordict>=0.1.2
-          - dgl>=1.1.0.cu*
+          - dgl>=2.4.0.cu*
   cugraph_pyg_dev:
     common:
       - output_types: [conda]
@@ -709,7 +708,7 @@ dependencies:
           - *pytorch_conda
           - pytorch-cuda==11.8
           - *tensordict
-          - pyg>=2.5,<2.6
+          - pytorch_geometric>=2.5,<2.6
 
   depends_on_pytorch:
     common:

docs/cugraph/source/basics/cugraph_intro.md → docs/cugraph/source/basics/index.md

@@ -1,5 +1,5 @@
-
 # cuGraph Introduction
+
 The Data Scientist has a collection of techniques within their
 proverbial toolbox. Data engineering, statistical analysis, and
 machine learning are among the most commonly known. However, there
@@ -20,8 +20,8 @@ into the RAPIDS data science ecosystem and allows the data scientist to easily
 call graph algorithms using data stored in a GPU DataFrame, NetworkX Graphs, or even
 CuPy or SciPy sparse Matrix.
 
-
 ## Vision
+
 The vision of RAPIDS cuGraph is to ___make graph analysis ubiquitous to the
 point that users just think in terms of analysis and not technologies or
 frameworks___. This is a goal that many of us on the cuGraph team have been
@@ -48,7 +48,6 @@ high-speed ETL, statistics, and machine learning. To make things even better,
 RAPIDS and DASK allows cuGraph to scale to multiple GPUs to support
 multi-billion edge graphs.
 
-
 ## Terminology
 
 cuGraph is a collection of GPU accelerated graph algorithms and graph utility