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* Upgrade presets for cuDNN 9.25.0.15, nvCOMP 5.3.0.16, TensorRT 11.2.1.2, Triton Inference Server 2.71.0
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Lines changed: 2560 additions & 1978 deletions

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

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@@ -51,9 +51,9 @@ runs:
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export PREFIX=aarch64-linux-gnu
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export CUDA=cuda-repo-rhel8-13-3-local-13.3.1_610.43.02-1.aarch64.rpm
5353
export CCCL=13-3-13.3.3.4.1-1.aarch64
54-
export CUDNN=cuda-13-9.24.0.43-1.aarch64
54+
export CUDNN=cuda-13-9.25.0.15-1.aarch64
5555
export NCCL=2.30.7-1+cuda13.3.aarch64
56-
export NVCOMP=nvcomp-linux-sbsa-5.2.0.10_cuda13-archive
56+
export NVCOMP=nvcomp-linux-sbsa-5.3.0.16_cuda13-archive
5757
export USERLAND_BUILDME="buildme --aarch64"
5858
elif [[ "$CI_DEPLOY_PLATFORM" == "linux-ppc64le" ]]; then
5959
export ARCH=ppc64el
@@ -74,9 +74,9 @@ runs:
7474
export PREFIX=x86_64-linux-gnu
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export CUDA=cuda-repo-rhel8-13-3-local-13.3.1_610.43.02-1.x86_64.rpm
7676
export CCCL=13-3-13.3.3.4.1-1.x86_64
77-
export CUDNN=cuda-13-9.24.0.43-1.x86_64
77+
export CUDNN=cuda-13-9.25.0.15-1.x86_64
7878
export NCCL=2.30.7-1+cuda13.3.x86_64
79-
export NVCOMP=nvcomp-linux-x86_64-5.2.0.10_cuda13-archive
79+
export NVCOMP=nvcomp-linux-x86_64-5.3.0.16_cuda13-archive
8080
fi
8181
echo "ARCH=$ARCH" >> $GITHUB_ENV
8282
echo "PREFIX=$PREFIX" >> $GITHUB_ENV
@@ -235,8 +235,8 @@ runs:
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if [[ "$CI_DEPLOY_PLATFORM" == "linux-arm64" ]] && [[ "$CI_DEPLOY_MODULE" == "tensorrt" ]]; then
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echo Installing TensorRT
237237
# python3 -m gdown 1LZRCv4ZAGiDQAu4pvADJIGntq4cGl5tU
238-
curl -LO https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/11.1.0/tars/TensorRT-Enterprise-11.1.0.106-Linux-aarch64-cuda-13.3-Release-external.tar.zst
239-
$SUDO tar -hxvf TensorRT-Enterprise-11.1.0.106-Linux-aarch64-cuda-13.3-Release-external.tar.zst -C /usr/local/
238+
curl -LO https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/11.2.1/tars/TensorRT-Enterprise-11.2.1.2-Linux-aarch64-cuda-13.3-Release-external.tar.zst
239+
$SUDO tar -hxvf TensorRT-Enterprise-11.2.1.2-Linux-aarch64-cuda-13.3-Release-external.tar.zst -C /usr/local/
240240
$SUDO ln -sf /usr/local/TensorRT* /usr/local/tensorrt
241241
$SUDO patchelf --set-rpath '$ORIGIN' /usr/local/tensorrt/lib/libnvinfer.so
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# Remove downloaded archives and unused libraries to avoid running out of disk space
@@ -246,8 +246,8 @@ runs:
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if [[ "$CI_DEPLOY_PLATFORM" == "linux-x86_64" ]] && [[ "$CI_DEPLOY_MODULE" == "tensorrt" ]]; then
247247
echo Installing TensorRT
248248
# python3 -m gdown 1dVhD-DEYY42QbZe1GXl-vxe3k6KqWGsL
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curl -LO https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/11.1.0/tars/TensorRT-Enterprise-11.1.0.106-Linux-x86_64-cuda-13.3-Release-external.tar.zst
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$SUDO tar -hxvf TensorRT-Enterprise-11.1.0.106-Linux-x86_64-cuda-13.3-Release-external.tar.zst -C /usr/local/
249+
curl -LO https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/11.2.1/tars/TensorRT-Enterprise-11.2.1.2-Linux-x86_64-cuda-13.3-Release-external.tar.zst
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$SUDO tar -hxvf TensorRT-Enterprise-11.2.1.2-Linux-x86_64-cuda-13.3-Release-external.tar.zst -C /usr/local/
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$SUDO ln -sf /usr/local/TensorRT* /usr/local/tensorrt
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$SUDO patchelf --set-rpath '$ORIGIN' /usr/local/tensorrt/lib/libnvinfer.so
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# Remove downloaded archives and unused libraries to avoid running out of disk space

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

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@@ -147,21 +147,21 @@ runs:
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if "%CI_DEPLOY_PLATFORM%"=="windows-x86_64" if not "%CI_DEPLOY_NEED_CUDA%"=="" (
148148
echo Installing CUDA, cuDNN, nvCOMP, etc
149149
curl -LO https://developer.download.nvidia.com/compute/cuda/13.3.1/local_installers/cuda_13.3.1_windows.exe
150-
curl -LO https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/windows-x86_64/cudnn-windows-x86_64-9.24.0.43_cuda13-archive.zip
150+
curl -LO https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/windows-x86_64/cudnn-windows-x86_64-9.25.0.15_cuda13-archive.zip
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curl -LO http://www.winimage.com/zLibDll/zlib123dllx64.zip
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curl -LO https://developer.download.nvidia.com/compute/nvcomp/redist/nvcomp/windows-x86_64/nvcomp-windows-x86_64-5.2.0.10_cuda13-archive.zip
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curl -LO https://developer.download.nvidia.com/compute/nvcomp/redist/nvcomp/windows-x86_64/nvcomp-windows-x86_64-5.3.0.16_cuda13-archive.zip
153153
cuda_13.3.1_windows.exe -s
154-
unzip cudnn-windows-x86_64-9.24.0.43_cuda13-archive.zip
154+
unzip cudnn-windows-x86_64-9.25.0.15_cuda13-archive.zip
155155
unzip zlib123dllx64.zip
156-
unzip nvcomp-windows-x86_64-5.2.0.10_cuda13-archive.zip
157-
move cudnn-windows-x86_64-9.24.0.43_cuda13-archive\bin\x64\*.dll "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v13.3\bin\x64"
158-
move cudnn-windows-x86_64-9.24.0.43_cuda13-archive\include\*.h "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v13.3\include"
159-
move cudnn-windows-x86_64-9.24.0.43_cuda13-archive\lib\x64\*.lib "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v13.3\lib\x64"
156+
unzip nvcomp-windows-x86_64-5.3.0.16_cuda13-archive.zip
157+
move cudnn-windows-x86_64-9.25.0.15_cuda13-archive\bin\x64\*.dll "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v13.3\bin\x64"
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move cudnn-windows-x86_64-9.25.0.15_cuda13-archive\include\*.h "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v13.3\include"
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move cudnn-windows-x86_64-9.25.0.15_cuda13-archive\lib\x64\*.lib "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v13.3\lib\x64"
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move dll_x64\zlibwapi.dll "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v13.3\bin\x64"
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move nvcomp-windows-x86_64-5.2.0.10_cuda13-archive\include\* "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v13.3\include"
162-
move nvcomp-windows-x86_64-5.2.0.10_cuda13-archive\include\nvcomp "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v13.3\include"
163-
move nvcomp-windows-x86_64-5.2.0.10_cuda13-archive\bin\nvcomp*.dll "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v13.3\bin\x64"
164-
move nvcomp-windows-x86_64-5.2.0.10_cuda13-archive\lib\nvcomp*.lib "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v13.3\lib\x64"
161+
move nvcomp-windows-x86_64-5.3.0.16_cuda13-archive\include\* "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v13.3\include"
162+
move nvcomp-windows-x86_64-5.3.0.16_cuda13-archive\include\nvcomp "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v13.3\include"
163+
move nvcomp-windows-x86_64-5.3.0.16_cuda13-archive\bin\nvcomp*.dll "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v13.3\bin\x64"
164+
move nvcomp-windows-x86_64-5.3.0.16_cuda13-archive\lib\nvcomp*.lib "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v13.3\lib\x64"
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rem echo Applying hotfix to Visual Studio 2019 for CUDA
167167
rem curl -LO https://raw.githubusercontent.com/microsoft/STL/main/stl/inc/cmath
@@ -187,9 +187,9 @@ runs:
187187
if "%CI_DEPLOY_MODULE%"=="tensorrt" (
188188
echo Installing TensorRT
189189
rem python -m gdown 1GfmJ1BKbacLpUU-0i_mGu0sjrAS0Xzzi
190-
curl -LO https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/11.1.0/zip/TensorRT-Enterprise-11.1.0.106-Windows-amd64-cuda-13.3-Release-external.zip
191-
unzip TensorRT-Enterprise-11.1.0.106-Windows-amd64-cuda-13.3-Release-external.zip
192-
move TensorRT-11.1.0.106 "%ProgramFiles%\NVIDIA GPU Computing Toolkit\TensorRT"
190+
curl -LO https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/11.2.1/zip/TensorRT-Enterprise-11.2.1.2-Windows-amd64-cuda-13.3-Release-external.zip
191+
unzip TensorRT-Enterprise-11.2.1.2-Windows-amd64-cuda-13.3-Release-external.zip
192+
move TensorRT-11.2.1.2 "%ProgramFiles%\NVIDIA GPU Computing Toolkit\TensorRT"
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)
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if "%CI_DEPLOY_MODULE%"=="mkl" (

‎.github/workflows/tritonserver.yml‎

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jobs:
2020
linux-x86_64:
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runs-on: ubuntu-22.04
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container: nvcr.io/nvidia/tritonserver:26.06-pyt-python-py3
22+
container: nvcr.io/nvidia/tritonserver:26.07-pyt-python-py3
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steps:
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- uses: bytedeco/javacpp-presets/.github/actions/deploy-ubuntu@actions
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platform:

‎CHANGELOG.md‎

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* Add new `SampleOnnxMNIST` in samples for TensorRT ([pull #1742](https://github.com/bytedeco/javacpp-presets/pull/1742))
1111
* Fix loading issues with `libomp.dylib` and `libiomp5.dylib` for DNNL and PyTorch on Mac
1212
* Include `model_package_loader.h` header file in presets for PyTorch ([issue #1729](https://github.com/bytedeco/javacpp-presets/issues/1729))
13-
* Upgrade presets for OpenCV 4.14.0, FFmpeg 8.1.2, MKL 2026.1.0, DNNL 3.13, OpenBLAS 0.3.34, CMINPACK 1.3.14, CUDA 13.3.1, cuDNN 9.24.0.43, NCCL 2.30.7, nvCOMP 5.2.0.10, NVIDIA Video Codec SDK 13.1.15, OpenCL 3.1.1, FFTW 3.3.11, CPython 3.14.6, NumPy 2.5.1, SciPy 1.18.0, LLVM 22.1.8, libffi 3.7.1, Tesseract 5.5.3, PyTorch 2.13.0, TensorFlow Lite 2.21.0, TensorRT 11.1.0.106, Triton Inference Server 2.70.0, ONNX 1.22.0, ONNX Runtime 1.28.0 ([pull #1791](https://github.com/bytedeco/javacpp-presets/pull/1791)), and their dependencies
13+
* Upgrade presets for OpenCV 4.14.0, FFmpeg 8.1.2, MKL 2026.1.0, DNNL 3.13, OpenBLAS 0.3.34, CMINPACK 1.3.14, CUDA 13.3.1, cuDNN 9.25.0.15, NCCL 2.30.7, nvCOMP 5.3.0.16, NVIDIA Video Codec SDK 13.1.15, OpenCL 3.1.1, FFTW 3.3.11, CPython 3.14.6, NumPy 2.5.1, SciPy 1.18.0, LLVM 22.1.8, libffi 3.7.1, Tesseract 5.5.3, PyTorch 2.13.0, TensorFlow Lite 2.21.0, TensorRT 11.2.1.2, Triton Inference Server 2.71.0, ONNX 1.22.0, ONNX Runtime 1.28.0 ([pull #1791](https://github.com/bytedeco/javacpp-presets/pull/1791)), and their dependencies
1414
* Compile classes with `parameters` bumping minimum requirements to Java SE 8 and Android 7.0 ([issue #1739](https://github.com/bytedeco/javacpp-presets/issues/1739))
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### February 22, 2026 version 1.5.13

‎README.md‎

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* Caffe 1.0 https://github.com/BVLC/caffe
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* OpenPose 1.7.0 https://github.com/CMU-Perceptual-Computing-Lab/openpose
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* CUDA 13.3.x https://developer.nvidia.com/cuda-downloads
222-
* cuDNN 9.24.x https://developer.nvidia.com/cudnn
222+
* cuDNN 9.25.x https://developer.nvidia.com/cudnn
223223
* NCCL 2.30.x https://developer.nvidia.com/nccl
224-
* nvCOMP 5.2.x https://developer.nvidia.com/nvcomp
224+
* nvCOMP 5.3.x https://developer.nvidia.com/nvcomp
225225
* NVIDIA Video Codec SDK 13.1.x https://developer.nvidia.com/nvidia-video-codec-sdk
226226
* OpenCL 3.1.x https://github.com/KhronosGroup/OpenCL-ICD-Loader
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* MXNet 1.9.x https://github.com/apache/incubator-mxnet
228228
* PyTorch 2.13.x https://github.com/pytorch/pytorch
229229
* SentencePiece 0.2.x https://github.com/google/sentencepiece
230230
* TensorFlow 1.15.x https://github.com/tensorflow/tensorflow
231231
* TensorFlow Lite 2.21.x https://github.com/tensorflow/tensorflow
232-
* TensorRT 11.1.x https://developer.nvidia.com/tensorrt
233-
* Triton Inference Server 2.70.x https://developer.nvidia.com/nvidia-triton-inference-server
232+
* TensorRT 11.2.x https://developer.nvidia.com/tensorrt
233+
* Triton Inference Server 2.71.x https://developer.nvidia.com/nvidia-triton-inference-server
234234
* The Arcade Learning Environment 0.8.x https://github.com/mgbellemare/Arcade-Learning-Environment
235235
* DepthAI 2.24.x https://github.com/luxonis/depthai-core
236236
* ONNX 1.22.x https://github.com/onnx/onnx

‎cuda/README.md‎

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This directory contains the JavaCPP Presets module for:
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* CUDA 13.3.1 https://developer.nvidia.com/cuda-zone
29-
* cuDNN 9.24.0.43 https://developer.nvidia.com/cudnn
29+
* cuDNN 9.25.0.15 https://developer.nvidia.com/cudnn
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* NCCL 2.30.7 https://developer.nvidia.com/nccl
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* nvCOMP 5.2.0.10 https://developer.nvidia.com/nvcomp
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* nvCOMP 5.3.0.16 https://developer.nvidia.com/nvcomp
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3333
Please refer to the parent README.md file for more detailed information about the JavaCPP Presets.
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@@ -67,49 +67,49 @@ We can use [Maven 3](http://maven.apache.org/) to download and install automatic
6767
<dependency>
6868
<groupId>org.bytedeco</groupId>
6969
<artifactId>cuda-platform</artifactId>
70-
<version>13.3-9.24-1.5.14-SNAPSHOT</version>
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<version>13.3-9.25-1.5.14-SNAPSHOT</version>
7171
</dependency>
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7373
<!-- Additional dependencies to use bundled CUDA, cuDNN, and NCCL -->
7474
<dependency>
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<groupId>org.bytedeco</groupId>
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<artifactId>cuda-platform-redist</artifactId>
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<version>13.3-9.24-1.5.14-SNAPSHOT</version>
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<version>13.3-9.25-1.5.14-SNAPSHOT</version>
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</dependency>
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<dependency>
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<groupId>org.bytedeco</groupId>
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<artifactId>cuda-platform-redist-cublas</artifactId>
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<version>13.3-9.24-1.5.14-SNAPSHOT</version>
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<version>13.3-9.25-1.5.14-SNAPSHOT</version>
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</dependency>
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<dependency>
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<groupId>org.bytedeco</groupId>
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<artifactId>cuda-platform-redist-cudnn</artifactId>
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<version>13.3-9.24-1.5.14-SNAPSHOT</version>
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<version>13.3-9.25-1.5.14-SNAPSHOT</version>
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</dependency>
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<dependency>
9090
<groupId>org.bytedeco</groupId>
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<artifactId>cuda-platform-redist-cusolver</artifactId>
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<version>13.3-9.24-1.5.14-SNAPSHOT</version>
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<version>13.3-9.25-1.5.14-SNAPSHOT</version>
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</dependency>
9494
<dependency>
9595
<groupId>org.bytedeco</groupId>
9696
<artifactId>cuda-platform-redist-cusparse</artifactId>
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<version>13.3-9.24-1.5.14-SNAPSHOT</version>
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<version>13.3-9.25-1.5.14-SNAPSHOT</version>
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</dependency>
9999
<dependency>
100100
<groupId>org.bytedeco</groupId>
101101
<artifactId>cuda-platform-redist-npp</artifactId>
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<version>13.3-9.24-1.5.14-SNAPSHOT</version>
102+
<version>13.3-9.25-1.5.14-SNAPSHOT</version>
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</dependency>
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<dependency>
105105
<groupId>org.bytedeco</groupId>
106106
<artifactId>cuda-platform-redist-nccl</artifactId>
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<version>13.3-9.24-1.5.14-SNAPSHOT</version>
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<version>13.3-9.25-1.5.14-SNAPSHOT</version>
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</dependency>
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<dependency>
110110
<groupId>org.bytedeco</groupId>
111111
<artifactId>cuda-platform-redist-nvcomp</artifactId>
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<version>13.3-9.24-1.5.14-SNAPSHOT</version>
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<version>13.3-9.25-1.5.14-SNAPSHOT</version>
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</dependency>
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</dependencies>

‎cuda/platform/pom.xml‎

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<groupId>org.bytedeco</groupId>
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<artifactId>cuda-platform</artifactId>
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<version>13.3-9.24-${project.parent.version}</version>
15+
<version>13.3-9.25-${project.parent.version}</version>
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<name>JavaCPP Presets Platform for CUDA</name>
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<properties>

‎cuda/platform/redist-cublas/pom.xml‎

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<groupId>org.bytedeco</groupId>
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<artifactId>cuda-platform-redist-cublas</artifactId>
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<version>13.3-9.24-${project.parent.version}</version>
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<version>13.3-9.25-${project.parent.version}</version>
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<name>JavaCPP Presets Platform Redist for CUDA</name>
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<properties>

‎cuda/platform/redist-cudnn/pom.xml‎

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<groupId>org.bytedeco</groupId>
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<artifactId>cuda-platform-redist-cudnn</artifactId>
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<version>13.3-9.24-${project.parent.version}</version>
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<version>13.3-9.25-${project.parent.version}</version>
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<name>JavaCPP Presets Platform Redist for CUDA</name>
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<properties>

‎cuda/platform/redist-cusolver/pom.xml‎

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<groupId>org.bytedeco</groupId>
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<artifactId>cuda-platform-redist-cusolver</artifactId>
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<version>13.3-9.24-${project.parent.version}</version>
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<version>13.3-9.25-${project.parent.version}</version>
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<name>JavaCPP Presets Platform Redist for CUDA</name>
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<properties>

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