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Upgrade to use CUDA 13 (#586)
* Upgrade use CUDA 13 Signed-off-by: M Q <mingmelvinq@nvidia.com> * More update to the CI workflows for CUDA 13 Signed-off-by: M Q <mingmelvinq@nvidia.com> * Addressed AI Agent comments on GenAI code Signed-off-by: M Q <mingmelvinq@nvidia.com> * Nit pick on formatting Signed-off-by: M Q <mingmelvinq@nvidia.com> * Nits in the README Signed-off-by: M Q <mingmelvinq@nvidia.com> --------- Signed-off-by: M Q <mingmelvinq@nvidia.com>
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‎.github/workflows/pr.yml‎

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pip install virtualenv
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virtualenv .venv
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source .venv/bin/activate
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python3 -m pip install nvidia-cuda-runtime-cu12
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python3 -m pip install "nvidia-cuda-runtime==13.*"
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CUDA_WHL_LIB_DIR="$(python3 -c 'import nvidia.cu13, os; print(os.path.join(nvidia.cu13.__path__[0], "lib"))')"
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export LD_LIBRARY_PATH="${CUDA_WHL_LIB_DIR}:${LD_LIBRARY_PATH}"
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echo "CUDA_WHL_LIB_DIR=${CUDA_WHL_LIB_DIR}" >> "${GITHUB_ENV}"
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echo "LD_LIBRARY_PATH=${LD_LIBRARY_PATH}" >> "${GITHUB_ENV}"
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./run setup
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- name: Check formatting
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run: |
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source .venv/bin/activate
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python3 -m pip install nvidia-cuda-runtime-cu12
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python3 -m pip install "nvidia-cuda-runtime==13.*"
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python3 -c 'import sys; print(sys.executable)'
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python3 -c 'import site; print(site.getsitepackages())'
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python3 -m pip freeze
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export CUDA_WHL_LIB_DIR=$(python3 -c 'import nvidia.cuda_runtime; print(nvidia.cuda_runtime.__path__[0])')/lib
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export LD_LIBRARY_PATH="$CUDA_WHL_LIB_DIR:$LD_LIBRARY_PATH"
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python3 -c 'from holoscan.core import *'
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./run check -f
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- name: Run Unit tests
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run: |
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source .venv/bin/activate
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python3 -m pip install nvidia-cuda-runtime-cu12
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export CUDA_WHL_LIB_DIR=$(python3 -c 'import nvidia.cuda_runtime; print(nvidia.cuda_runtime.__path__[0])')/lib
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export LD_LIBRARY_PATH="$CUDA_WHL_LIB_DIR:$LD_LIBRARY_PATH"
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python3 -m pip install "nvidia-cuda-runtime==13.*"
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./run test all unit
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- name: Coverage
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run: |
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source .venv/bin/activate
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python3 -m pip install nvidia-cuda-runtime-cu12
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export CUDA_WHL_LIB_DIR=$(python3 -c 'import nvidia.cuda_runtime; print(nvidia.cuda_runtime.__path__[0])')/lib
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export LD_LIBRARY_PATH="$CUDA_WHL_LIB_DIR:$LD_LIBRARY_PATH"
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python3 -m pip install "nvidia-cuda-runtime==13.*"
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coverage xml
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- name: Upload coverage
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uses: codecov/codecov-action@v2

‎README.md‎

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### Prerequisites
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- This SDK depends on [NVIDIA Holoscan SDK](https://pypi.org/project/holoscan/) for its core implementation as well as its CLI, hence inherits its prerequisites, e.g. Ubuntu 22.04 with glibc 2.35 on X86-64 and NVIDIA dGPU drivers version 535 or above. Important to note that `holoscan` and `holoscan-cli` up to v4.2 are compatible.
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- Key runtime dependencies also include [nvidia-nvimgcodec](https://pypi.org/project/nvidia-nvimgcodec-cu12/) and its own dependencies for GPU accecelerated DICOM image decoding.
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- [CUDA 12.2](https://developer.nvidia.com/cuda-12-2-0-download-archive) or above is required along with a supported NVIDIA GPU with at least 8GB of video RAM.
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- If inference is not used in an example application and a GPU is not installed, at least [CUDA 12 runtime](https://pypi.org/project/nvidia-cuda-runtime-cu12/) is required, as this is one of the requirements of Holoscan SDK. In addition, the `LIB_LIBRARY_PATH` must be set to include the installed shared library, e.g. in a Python 3.10 env, ```export LD_LIBRARY_PATH=`pwd`/.venv/lib/python3.10/site-packages/nvidia/cuda_runtime/lib:$LD_LIBRARY_PATH```
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- This SDK depends on [NVIDIA Holoscan SDK (CUDA 13)](https://pypi.org/project/holoscan-cu13/) for its core implementation as well as its CLI, hence inherits its prerequisites, e.g. Ubuntu 22.04 with glibc 2.35+ (see output of ldd --version) and CUDA Runtime 13.0 or above. It is important to note that `holoscan-cu13` and `holoscan-cli` up to version 4.2 are compatible.
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- Key runtime dependencies also include [nvidia-nvimgcodec](https://pypi.org/project/nvidia-nvimgcodec-cu13/) and its own dependencies for GPU-accelerated DICOM image decoding.
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- [CUDA 13.0](https://developer.nvidia.com/cuda-downloads) or above is required along with a supported NVIDIA GPU with at least 8GB of video RAM.
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- If inference is not used in an example application and a GPU is not installed, at least [CUDA 13 runtime](https://pypi.org/project/nvidia-cuda-runtime/) is required, as this is one of the requirements of Holoscan SDK. In addition, the `LD_LIBRARY_PATH` must be set to include the installed shared library, e.g. in a Python 3.10 env, ```export LD_LIBRARY_PATH=`pwd`/.venv/lib/python3.10/site-packages/nvidia/cu13/lib:$LD_LIBRARY_PATH```
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- Python: 3.10 to 3.13
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## Getting Started

‎THIRD_PARTY_NOTICES/nvidia-nvimgcodec_Apache2.0_LICENSE.txt‎

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nvidia-nvimgcodec (PyPI package: nvidia-nvimgcodec-cu12)
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nvidia-nvimgcodec (PyPI package: nvidia-nvimgcodec-cu13)
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The MONAI Deploy App SDK optionally integrates with NVIDIA nvImageCodec for
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GPU-accelerated DICOM compressed pixel data decoding.

‎monai/deploy/operators/decoder_nvimgcodec.py‎

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nvimgcodec = None
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# nvimgcodec pypi package name, minimum version required and the label for this decoder plugin.
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NVIMGCODEC_MODULE_NAME = "nvidia.nvimgcodec" # from nvidia-nvimgcodec-cu12 or other variants
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NVIMGCODEC_MODULE_NAME = "nvidia.nvimgcodec" # from nvidia-nvimgcodec-cu13 or other variants
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NVIMGCODEC_MIN_VERSION = "0.6"
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NVIMGCODEC_MIN_VERSION_TUPLE = tuple(int(x) for x in NVIMGCODEC_MIN_VERSION.split("."))
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NVIMGCODEC_PLUGIN_LABEL = "0.6+nvimgcodec" # to be sorted to first in ascending order of plugins
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# Required for decoder plugin
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DECODER_DEPENDENCIES = {
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x: ("numpy", "cupy", f"{NVIMGCODEC_MODULE_NAME}>={NVIMGCODEC_MIN_VERSION}, nvidia-nvjpeg2k-cu12>=0.9.1,")
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x: (
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"numpy",
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"cupy",
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f"{NVIMGCODEC_MODULE_NAME}>={NVIMGCODEC_MIN_VERSION}",
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"nvidia-nvjpeg2k-cu13>=0.9.1",
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)
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for x in SUPPORTED_TRANSFER_SYNTAXES
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}
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‎monai/deploy/operators/dicom_series_to_volume_operator.py‎

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based decoder plugins are available at runtime.
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Registering the decoder plugin is all automatic and does not require any additional change in user's application
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except for adding a dependency on the `nvimgcodec-cu12` and `nvidia-nvjpeg2k-cu12` packages (suffix of cu12 means
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CUDA 12.0 though cu13 is also supported).
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except for adding a dependency on the `nvidia-nvimgcodec-cu13` and `all` of its optional dependencies.
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Named Input:
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study_selected_series_list: List of StudySelectedSeries.

‎notebooks/tutorials/01_simple_app.ipynb‎

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"source": [
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"tag_prefix = \"simple_imaging_app\"\n",
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"\n",
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"!monai-deploy package simple_imaging_app -c simple_imaging_app/app.yaml -t {tag_prefix}:1.0 --platform x86_64 --cuda 12 -l DEBUG"
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"!monai-deploy package simple_imaging_app -c simple_imaging_app/app.yaml -t {tag_prefix}:1.0 --platform x86_64 -l DEBUG"
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]
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},
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{

‎notebooks/tutorials/02_mednist_app-prebuilt.ipynb‎

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"source": [
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"tag_prefix = \"mednist_app\"\n",
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"\n",
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"!monai-deploy package \"source/examples/apps/mednist_classifier_monaideploy/mednist_classifier_monaideploy.py\" -m {models_folder} -c \"source/examples/apps/mednist_classifier_monaideploy/app.yaml\" -t {tag_prefix}:1.0 --platform x86_64 -l DEBUG --cuda 12"
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"!monai-deploy package \"source/examples/apps/mednist_classifier_monaideploy/mednist_classifier_monaideploy.py\" -m {models_folder} -c \"source/examples/apps/mednist_classifier_monaideploy/app.yaml\" -t {tag_prefix}:1.0 --platform x86_64 -l DEBUG"
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]
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},
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{

‎notebooks/tutorials/02_mednist_app.ipynb‎

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"source": [
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"tag_prefix = \"mednist_app\"\n",
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"\n",
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"!monai-deploy package \"mednist_app/mednist_classifier_monaideploy.py\" -m {models_folder} -c \"mednist_app/app.yaml\" -t {tag_prefix}:1.0 --platform x86_64 -l DEBUG --cuda 12"
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"!monai-deploy package \"mednist_app/mednist_classifier_monaideploy.py\" -m {models_folder} -c \"mednist_app/app.yaml\" -t {tag_prefix}:1.0 --platform x86_64 -l DEBUG"
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},
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{

‎notebooks/tutorials/03_segmentation_app.ipynb‎

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"source": [
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"tag_prefix = \"my_app\"\n",
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"\n",
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"!monai-deploy package my_app -m {models_folder} -c my_app/app.yaml -t {tag_prefix}:1.0 --platform x86_64 -l DEBUG --cuda 12"
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"!monai-deploy package my_app -m {models_folder} -c my_app/app.yaml -t {tag_prefix}:1.0 --platform x86_64 -l DEBUG"
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]
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},
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{

‎notebooks/tutorials/04_monai_bundle_app.ipynb‎

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"tag_prefix = \"my_app\"\n",
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"\n",
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"!monai-deploy package my_app -m {models_folder} -c my_app/app.yaml -t {tag_prefix}:1.0 --platform x86_64 -l DEBUG --cuda 12 "
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"!monai-deploy package my_app -m {models_folder} -c my_app/app.yaml -t {tag_prefix}:1.0 --platform x86_64 -l DEBUG"
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]
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},
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{

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