* Upgrade presets for LLVM 20.1.4, CUDA 12.9.0, cuDNN 9.9.0, NCCL 2.26.5, TensorRT 10.10.0.31

Author: saudet

.github/actions/deploy-ubuntu/action.yml

@@ -41,9 +41,9 @@ runs:
           export ARCH=arm64
           export ARCH_CUDA=sbsa
           export PREFIX=aarch64-linux-gnu
-          export CUDA=cuda-repo-rhel8-12-8-local-12.8.1_570.124.06-1.aarch64.rpm
-          export CUDNN=cuda-12-9.8.0.87-1.aarch64
-          export NCCL=2.26.2-1+cuda12.8.aarch64
+          export CUDA=cuda-repo-rhel8-12-9-local-12.9.0_575.51.03-1.aarch64.rpm
+          export CUDNN=cuda-12-9.9.0.52-1.aarch64
+          export NCCL=2.26.5-1+cuda12.9.aarch64
           export NVCOMP=nvcomp-linux-sbsa-4.2.0.11_cuda12-archive
           export USERLAND_BUILDME="buildme --aarch64"
         elif [[ "$CI_DEPLOY_PLATFORM" == "linux-ppc64le" ]]; then
@@ -63,9 +63,9 @@ runs:
           export ARCH=amd64
           export ARCH_CUDA=x86_64
           export PREFIX=x86_64-linux-gnu
-          export CUDA=cuda-repo-rhel8-12-8-local-12.8.1_570.124.06-1.x86_64.rpm
-          export CUDNN=cuda-12-9.8.0.87-1.x86_64
-          export NCCL=2.26.2-1+cuda12.8.x86_64
+          export CUDA=cuda-repo-rhel8-12-9-local-12.9.0_575.51.03-1.x86_64.rpm
+          export CUDNN=cuda-12-9.9.0.52-1.x86_64
+          export NCCL=2.26.5-1+cuda12.9.x86_64
           export NVCOMP=nvcomp-linux-x86_64-4.2.0.11_cuda12-archive
         fi
         echo "ARCH=$ARCH" >> $GITHUB_ENV
@@ -165,15 +165,15 @@ runs:
 
         if [[ -n ${ARCH_CUDA:-} ]] && [[ -n ${CI_DEPLOY_NEED_CUDA:-} ]]; then
           echo Installing CUDA, cuDNN, nvCOMP, etc
-          curl -LO https://developer.download.nvidia.com/compute/cuda/12.8.1/local_installers/$CUDA
+          curl -LO https://developer.download.nvidia.com/compute/cuda/12.9.0/local_installers/$CUDA
           curl -LO https://developer.download.nvidia.com/compute/cuda/repos/rhel8/$ARCH_CUDA/libcudnn9-$CUDNN.rpm
           curl -LO https://developer.download.nvidia.com/compute/cuda/repos/rhel8/$ARCH_CUDA/libcudnn9-devel-$CUDNN.rpm
           curl -LO https://developer.download.nvidia.com/compute/cuda/repos/rhel8/$ARCH_CUDA/libnccl-$NCCL.rpm
           curl -LO https://developer.download.nvidia.com/compute/cuda/repos/rhel8/$ARCH_CUDA/libnccl-devel-$NCCL.rpm
 
           $SUDO rpm -i --force --ignorearch --nodeps $CUDA libcudnn*.rpm libnccl*.rpm
           rm -f *.rpm *.tgz *.txz *.tar.*
-          pushd /var/cuda-repo-rhel8-12-8-local/; $SUDO rpm -i --force --ignorearch --nodeps cuda*.rpm libc*.rpm libn*.rpm; $SUDO rm *.rpm; popd
+          pushd /var/cuda-repo-rhel8-12-9-local/; $SUDO rpm -i --force --ignorearch --nodeps cuda*.rpm libc*.rpm libn*.rpm; $SUDO rm *.rpm; popd
           $SUDO ln -snf /usr/local/cuda/targets/*/include /usr/local/cuda/include
           $SUDO ln -snf /usr/local/cuda/targets/*/lib /usr/local/cuda/lib64
           $SUDO ln -sf /usr/local/cuda/lib64/ /usr/local/cuda/lib
@@ -215,16 +215,18 @@ runs:
         if [[ "$CI_DEPLOY_PLATFORM" == "linux-arm64" ]] && [[ "$CI_DEPLOY_MODULE" == "tensorrt" ]]; then
           echo Installing TensorRT
           # python3 -m gdown 1LZRCv4ZAGiDQAu4pvADJIGntq4cGl5tU
-          curl -LO https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.9.0/tars/TensorRT-10.9.0.34.Linux.aarch64-gnu.cuda-12.8.tar.gz
-          $SUDO tar -hxvf TensorRT-10.9.0.34.Linux.aarch64-gnu.cuda-12.8.tar.gz -C /usr/local/
+          curl -LO https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.10.0/tars/TensorRT-10.10.0.31.Linux.aarch64-gnu.cuda-12.9.tar.gz
+          $SUDO tar -hxvf TensorRT-10.10.0.31.Linux.aarch64-gnu.cuda-12.9.tar.gz -C /usr/local/
           $SUDO ln -sf /usr/local/TensorRT* /usr/local/tensorrt
+          # Remove downloaded archives and unused libraries to avoid running out of disk space
+          $SUDO rm -f *.tar.gz $(find /usr/local/tensorrt/ -name '*.a')
         fi
 
         if [[ "$CI_DEPLOY_PLATFORM" == "linux-x86_64" ]] && [[ "$CI_DEPLOY_MODULE" == "tensorrt" ]]; then
           echo Installing TensorRT
           # python3 -m gdown 1dVhD-DEYY42QbZe1GXl-vxe3k6KqWGsL
-          curl -LO https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.9.0/tars/TensorRT-10.9.0.34.Linux.x86_64-gnu.cuda-12.8.tar.gz
-          $SUDO tar -hxvf TensorRT-10.9.0.34.Linux.x86_64-gnu.cuda-12.8.tar.gz -C /usr/local/
+          curl -LO https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.10.0/tars/TensorRT-10.10.0.31.Linux.x86_64-gnu.cuda-12.9.tar.gz
+          $SUDO tar -hxvf TensorRT-10.10.0.31.Linux.x86_64-gnu.cuda-12.9.tar.gz -C /usr/local/
           $SUDO ln -sf /usr/local/TensorRT* /usr/local/tensorrt
           # Remove downloaded archives and unused libraries to avoid running out of disk space
           $SUDO rm -f *.tar.gz $(find /usr/local/tensorrt/ -name '*.a')

.github/actions/deploy-windows/action.yml

@@ -94,38 +94,33 @@ runs:
 
         if "%CI_DEPLOY_PLATFORM%"=="windows-x86_64" if not "%CI_DEPLOY_NEED_CUDA%"=="" (
           echo Installing CUDA, cuDNN, nvCOMP, etc
-          curl -LO https://developer.download.nvidia.com/compute/cuda/11.8.0/local_installers/cuda_11.8.0_522.06_windows.exe
-          curl -LO https://developer.download.nvidia.com/compute/cuda/12.8.1/local_installers/cuda_12.8.1_572.61_windows.exe
-          curl -LO https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/windows-x86_64/cudnn-windows-x86_64-9.8.0.87_cuda12-archive.zip
+          curl -LO https://developer.download.nvidia.com/compute/cuda/12.9.0/local_installers/cuda_12.9.0_576.02_windows.exe
+          curl -LO https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/windows-x86_64/cudnn-windows-x86_64-9.9.0.52_cuda12-archive.zip
           curl -LO http://www.winimage.com/zLibDll/zlib123dllx64.zip
           curl -LO https://developer.download.nvidia.com/compute/nvcomp/redist/nvcomp/windows-x86_64/nvcomp-windows-x86_64-4.2.0.11_cuda12-archive.zip
-          cuda_11.8.0_522.06_windows.exe -s
-          bash -c "rm -Rf 'C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v11.8'"
-          bash -c "mv 'C:/Program Files/NVIDIA Corporation/NvToolsExt' 'C:/Program Files/NVIDIA Corporation/NvToolsExt_old'"
-          cuda_12.8.1_572.61_windows.exe -s
-          bash -c "mv 'C:/Program Files/NVIDIA Corporation/NvToolsExt_old' 'C:/Program Files/NVIDIA Corporation/NvToolsExt'"
-          bash -c "ls 'C:/Program Files/NVIDIA Corporation/NvToolsExt'"
-          unzip cudnn-windows-x86_64-9.8.0.87_cuda12-archive.zip
+          cuda_12.9.0_576.02_windows.exe -s
+          unzip cudnn-windows-x86_64-9.9.0.52_cuda12-archive.zip
           unzip zlib123dllx64.zip
           unzip nvcomp-windows-x86_64-4.2.0.11_cuda12-archive.zip
-          move cudnn-windows-x86_64-9.8.0.87_cuda12-archive\bin\*.dll "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.8\bin"
-          move cudnn-windows-x86_64-9.8.0.87_cuda12-archive\include\*.h "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.8\include"
-          move cudnn-windows-x86_64-9.8.0.87_cuda12-archive\lib\x64\*.lib "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.8\lib\x64"
-          move dll_x64\zlibwapi.dll "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.8\bin"
-          move nvcomp-windows-x86_64-4.2.0.11_cuda12-archive\include\* "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.8\include"
-          move nvcomp-windows-x86_64-4.2.0.11_cuda12-archive\include\nvcomp "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.8\include"
-          move nvcomp-windows-x86_64-4.2.0.11_cuda12-archive\bin\nvcomp*.dll "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.8\bin"
-          move nvcomp-windows-x86_64-4.2.0.11_cuda12-archive\lib\nvcomp*.lib "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.8\lib\x64"
+          move cudnn-windows-x86_64-9.9.0.52_cuda12-archive\bin\*.dll "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.9\bin"
+          move cudnn-windows-x86_64-9.9.0.52_cuda12-archive\include\*.h "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.9\include"
+          move cudnn-windows-x86_64-9.9.0.52_cuda12-archive\lib\x64\*.lib "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.9\lib\x64"
+          move dll_x64\zlibwapi.dll "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.9\bin"
+          move nvcomp-windows-x86_64-4.2.0.11_cuda12-archive\include\* "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.9\include"
+          move nvcomp-windows-x86_64-4.2.0.11_cuda12-archive\include\nvcomp "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.9\include"
+          move nvcomp-windows-x86_64-4.2.0.11_cuda12-archive\bin\nvcomp*.dll "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.9\bin"
+          move nvcomp-windows-x86_64-4.2.0.11_cuda12-archive\lib\nvcomp*.lib "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.9\lib\x64"
 
           rem echo Applying hotfix to Visual Studio 2019 for CUDA
           rem curl -LO https://raw.githubusercontent.com/microsoft/STL/main/stl/inc/cmath
           rem bash -c "find 'C:/Program Files (x86)/Microsoft Visual Studio/2019/Enterprise/VC/' -name cmath -exec cp -v cmath {} \;"
-          bash -c "sed -i 's/cublas_v2.h/cublas_api.h/g' 'C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.8/include/cublasXt.h' 'C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.8/include/cusolverDn.h' 'C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.8/include/cusolverSp.h'"
-          bash -c "sed -i 's/#if !defined(__cplusplus) || __cplusplus >= 201103L/#if 1/g' 'C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.8/include/driver_types.h'"
-          bash -c "sed -i '/block_merge_sort.cuh/d' 'C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.8/include/cub/cub.cuh'"
-          bash -c "sed -i '/device_merge_sort.cuh/d' 'C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.8/include/cub/cub.cuh'"
-          bash -c "sed -i '/device_segmented_sort.cuh/d' 'C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.8/include/cub/cub.cuh'"
-          bash -c "sed -i '/warp_merge_sort.cuh/d' 'C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.8/include/cub/cub.cuh'"
+          bash -c "sed -i 's/cublas_v2.h/cublas_api.h/g' 'C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.9/include/cublasXt.h' 'C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.9/include/cusolverDn.h' 'C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.9/include/cusolverSp.h'"
+          bash -c "sed -i 's/#if !defined(__cplusplus) || __cplusplus >= 201103L/#if 1/g' 'C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.9/include/driver_types.h'"
+          bash -c "sed -i '/block_merge_sort.cuh/d' 'C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.9/include/cub/cub.cuh'"
+          bash -c "sed -i '/device_merge_sort.cuh/d' 'C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.9/include/cub/cub.cuh'"
+          bash -c "sed -i '/device_segmented_sort.cuh/d' 'C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.9/include/cub/cub.cuh'"
+          bash -c "sed -i '/warp_merge_sort.cuh/d' 'C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.9/include/cub/cub.cuh'"
+          bash -c "find 'C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.9/'"
         )
 
         if "%CI_DEPLOY_MODULE%"=="nvcodec" (
@@ -138,9 +133,9 @@ runs:
         if "%CI_DEPLOY_MODULE%"=="tensorrt" (
           echo Installing TensorRT
           rem python -m gdown 1GfmJ1BKbacLpUU-0i_mGu0sjrAS0Xzzi
-          curl -LO https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.9.0/zip/TensorRT-10.9.0.34.Windows.win10.cuda-12.8.zip
-          unzip TensorRT-10.9.0.34.Windows.win10.cuda-12.8.zip
-          move TensorRT-10.9.0.34 "%ProgramFiles%\NVIDIA GPU Computing Toolkit\TensorRT"
+          curl -LO https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.10.0/zip/TensorRT-10.10.0.31.Windows.win10.cuda-12.9.zip
+          unzip TensorRT-10.10.0.31.Windows.win10.cuda-12.9.zip
+          move TensorRT-10.10.0.31 "%ProgramFiles%\NVIDIA GPU Computing Toolkit\TensorRT"
         )
 
         if "%CI_DEPLOY_MODULE%"=="mkl" (
@@ -214,10 +209,10 @@ runs:
           C:/msys64/usr/bin/bazel.exe version
         )
         if exist "%ProgramFiles%\NVIDIA GPU Computing Toolkit" (
-          set "CUDA_PATH=%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.8"
-          set "CUDA_PATH_V12_8=%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.8"
-          set "PATH=%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.8\bin;%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.8\libnvvp;%PATH%"
-          echo CUDA Version 12.8.1>"%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.8\version.txt"
+          set "CUDA_PATH=%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.9"
+          set "CUDA_PATH_V12_9=%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.9"
+          set "PATH=%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.9\bin;%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.9\libnvvp;%PATH%"
+          echo CUDA Version 12.9.0>"%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.9\version.txt"
         )
         set "CCACHE_DIR=%USERPROFILE%\ccache"
         set "PATH=C:\hostedtoolcache\windows\Python\3.10.11\x64;C:\msys64\%MSYSTEM%\bin;C:\msys64\usr\bin;%ProgramFiles%\apache-maven-3.6.3\bin;%PATH%"

CHANGELOG.md

@@ -5,7 +5,7 @@
  * Allow setting "org.bytedeco.openblas.load" system property to "none" ([issue #1203](https://github.com/bytedeco/javacpp-presets/issues/1203))
  * Fix presets for the CUPTI module of CUDA on Windows ([pull #1576](https://github.com/bytedeco/javacpp-presets/pull/1576))
  * Introduce `macosx-arm64` builds for ARPACK-NG, CMINPACK, FFTW, GSL, TensorFlow Lite, ONNX, ONNX Runtime ([issue #1069](https://github.com/bytedeco/javacpp-presets/issues/1069))
- * Upgrade presets for OpenCV 4.11.0, FFmpeg 7.1.1, DNNL 3.8.1 ([pull #1633](https://github.com/bytedeco/javacpp-presets/pull/1633)), OpenBLAS 0.3.29, CPython 3.13.3, NumPy 2.2.5, SciPy 1.15.2, LLVM 20.1.3, libffi 3.4.8, CUDA 12.8.1, cuDNN 9.8.0, NCCL 2.26.2, nvCOMP 4.2.0.11, NVIDIA Video Codec SDK 13.0.19, PyTorch 2.7.0, TensorFlow Lite 2.19.0, TensorRT 10.9.0.34, Triton Inference Server 2.56.0, ONNX Runtime 1.21.1, and their dependencies
+ * Upgrade presets for OpenCV 4.11.0, FFmpeg 7.1.1, DNNL 3.8.1 ([pull #1633](https://github.com/bytedeco/javacpp-presets/pull/1633)), OpenBLAS 0.3.29, CPython 3.13.3, NumPy 2.2.5, SciPy 1.15.2, LLVM 20.1.4, libffi 3.4.8, CUDA 12.9.0, cuDNN 9.9.0, NCCL 2.26.5, nvCOMP 4.2.0.11, NVIDIA Video Codec SDK 13.0.19, PyTorch 2.7.0, TensorFlow Lite 2.19.0, TensorRT 10.10.0.31, Triton Inference Server 2.56.0, ONNX Runtime 1.21.1, and their dependencies
 
 ### November 16, 2024 version 1.5.11
  * Enable distributed package using Gloo in presets for PyTorch ([pull #1510](https://github.com/bytedeco/javacpp-presets/pull/1510))

README.md

@@ -216,8 +216,8 @@ Each child module in turn relies by default on the included [`cppbuild.sh` scrip
  * Tesseract 5.5.x  https://github.com/tesseract-ocr/tesseract
  * Caffe 1.0  https://github.com/BVLC/caffe
  * OpenPose 1.7.0  https://github.com/CMU-Perceptual-Computing-Lab/openpose
- * CUDA 12.8.x  https://developer.nvidia.com/cuda-downloads
-   * cuDNN 9.8.x  https://developer.nvidia.com/cudnn
+ * CUDA 12.9.x  https://developer.nvidia.com/cuda-downloads
+   * cuDNN 9.9.x  https://developer.nvidia.com/cudnn
    * NCCL 2.26.x  https://developer.nvidia.com/nccl
    * nvCOMP 4.2.x https://developer.nvidia.com/nvcomp
  * NVIDIA Video Codec SDK 13.0.x  https://developer.nvidia.com/nvidia-video-codec-sdk
@@ -227,7 +227,7 @@ Each child module in turn relies by default on the included [`cppbuild.sh` scrip
  * SentencePiece 0.2.0  https://github.com/google/sentencepiece
  * TensorFlow 1.15.x  https://github.com/tensorflow/tensorflow
  * TensorFlow Lite 2.19.x  https://github.com/tensorflow/tensorflow
- * TensorRT 10.9.x  https://developer.nvidia.com/tensorrt
+ * TensorRT 10.10.x  https://developer.nvidia.com/tensorrt
  * Triton Inference Server 2.56.x  https://developer.nvidia.com/nvidia-triton-inference-server
  * The Arcade Learning Environment 0.8.x  https://github.com/mgbellemare/Arcade-Learning-Environment
  * DepthAI 2.24.x  https://github.com/luxonis/depthai-core

cuda/README.md

@@ -25,9 +25,9 @@ Introduction
 ------------
 This directory contains the JavaCPP Presets module for:
 
- * CUDA 12.8.1  https://developer.nvidia.com/cuda-zone
- * cuDNN 9.8.0  https://developer.nvidia.com/cudnn
- * NCCL 2.26.2  https://developer.nvidia.com/nccl
+ * CUDA 12.9.0  https://developer.nvidia.com/cuda-zone
+ * cuDNN 9.9.0  https://developer.nvidia.com/cudnn
+ * NCCL 2.26.5  https://developer.nvidia.com/nccl
  * nvCOMP 4.2.0.11  https://developer.nvidia.com/nvcomp
 
 Please refer to the parent README.md file for more detailed information about the JavaCPP Presets.
@@ -67,14 +67,14 @@ We can use [Maven 3](http://maven.apache.org/) to download and install automatic
         <dependency>
             <groupId>org.bytedeco</groupId>
             <artifactId>cuda-platform</artifactId>
-            <version>12.8-9.8-1.5.12-SNAPSHOT</version>
+            <version>12.9-9.9-1.5.12-SNAPSHOT</version>
         </dependency>
 
         <!-- Additional dependencies to use bundled CUDA, cuDNN, and NCCL -->
         <dependency>
             <groupId>org.bytedeco</groupId>
             <artifactId>cuda-platform-redist</artifactId>
-            <version>12.8-9.8-1.5.12-SNAPSHOT</version>
+            <version>12.9-9.9-1.5.12-SNAPSHOT</version>
         </dependency>
 
     </dependencies>

cuda/platform/pom.xml

@@ -12,7 +12,7 @@
 
   <groupId>org.bytedeco</groupId>
   <artifactId>cuda-platform</artifactId>
-  <version>12.8-9.8-${project.parent.version}</version>
+  <version>12.9-9.9-${project.parent.version}</version>
   <name>JavaCPP Presets Platform for CUDA</name>
 
   <properties>

cuda/platform/redist/pom.xml

@@ -12,7 +12,7 @@
 
   <groupId>org.bytedeco</groupId>
   <artifactId>cuda-platform-redist</artifactId>
-  <version>12.8-9.8-${project.parent.version}</version>
+  <version>12.9-9.9-${project.parent.version}</version>
   <name>JavaCPP Presets Platform Redist for CUDA</name>
 
   <properties>

cuda/pom.xml

@@ -11,7 +11,7 @@
 
   <groupId>org.bytedeco</groupId>
   <artifactId>cuda</artifactId>
-  <version>12.8-9.8-${project.parent.version}</version>
+  <version>12.9-9.9-${project.parent.version}</version>
   <name>JavaCPP Presets for CUDA</name>
 
   <dependencies>

cuda/samples/pom.xml

@@ -12,14 +12,14 @@
         <dependency>
             <groupId>org.bytedeco</groupId>
             <artifactId>cuda-platform</artifactId>
-            <version>12.8-9.8-1.5.12-SNAPSHOT</version>
+            <version>12.9-9.9-1.5.12-SNAPSHOT</version>
         </dependency>
 
         <!-- Additional dependencies to use bundled CUDA, cuDNN, and NCCL -->
         <dependency>
             <groupId>org.bytedeco</groupId>
             <artifactId>cuda-platform-redist</artifactId>
-            <version>12.8-9.8-1.5.12-SNAPSHOT</version>
+            <version>12.9-9.9-1.5.12-SNAPSHOT</version>
         </dependency>
 
     </dependencies>

cuda/src/gen/java/org/bytedeco/cuda/cudart/CUDA_CHILD_GRAPH_NODE_PARAMS.java

@@ -33,6 +33,12 @@ public class CUDA_CHILD_GRAPH_NODE_PARAMS extends Pointer {
     }
 
     /** The child graph to clone into the node for node creation, or
-                            a handle to the graph owned by the node for node query */
+                        *   a handle to the graph owned by the node for node query.
+                        *   The graph must not contain conditional nodes. Graphs
+                        *   containing memory allocation or memory free nodes must
+                        *   set the ownership to be moved to the parent.
+                        */
     public native CUgraph_st graph(); public native CUDA_CHILD_GRAPH_NODE_PARAMS graph(CUgraph_st setter);
+    /** The ownership relationship of the child graph node. */
+    public native @Cast("CUgraphChildGraphNodeOwnership") int ownership(); public native CUDA_CHILD_GRAPH_NODE_PARAMS ownership(int setter);
 }