NVIDIA
NVIDIA
CUDA Deep Learning
Container
NVIDIA
NVIDIA
CUDA Deep Learning

CUDA is a parallel computing platform and programming model that enhances computing performance using NVIDIA GPUs. CUDA Deep Learning integrates networking and GPU-accelerated libraries like cuDNN, cuTensor, NCCL, HPC-x, and the CUDA Toolkit.

LayerLabelCreated
8aa721bfc4389c7dbb56483ff45cffebdf8305e14b3a022e522535b8631a9373CONFIG
Entrypoint /opt/nvidia/nvidia_entrypoint.sh
01/09/2026 11:37 PM UTC
550269931fbfd888865b62840e83914c0995d960e9a3f96185052703f73d6754RUN
RUN |2 ENABLE_MITMPROXY=0 VERSION_LIST=CURAND_VERSION CUBLAS_VERSION CUFILE_VERSION /bin/sh -c set -exo pipefail export DEVEL=1 BASE=0 if [ ! -f /etc/ld.so.conf.d/nvidia-tegra.conf ]; then COMPONENT_LIST="nvrtc-dev" /nvidia/build-scripts/installCUDA.sh else # Don't use COMPONENT_LIST in iGPU environment
    /nvidia/build-scripts/installCUDA.sh
fi

VERSION_LIST="${VERSION_LIST}" /nvidia/build-scripts/installLIBS.sh
if [ ! -f /etc/ld.so.conf.d/nvidia-tegra.conf ]; then 
  /nvidia/build-scripts/installNCCL.sh
fi
NOBUILDER=1 /nvidia/build-scripts/installTRT.sh
/nvidia/build-scripts/installCUDNN.sh
/nvidia/build-scripts/installCUSPARSELT.sh

# Clean up libcudnn_engines_precompiled
rm -rf /usr/lib/*-linux-gnu/libcudnn_engines_precompiled.so*
 # buildkit
01/09/2026 11:37 PM UTC
c8da9527bd762a891ef6030de975bd5aa817d2e8b43049d7588e98f0047d0bd5ARG
VERSION_LIST=CURAND_VERSION CUBLAS_VERSION CUFILE_VERSION
01/09/2026 11:26 PM UTC
1b876b19ef5acd1292daf1615f33384cc0e949b6e0eda45c003b88cf0c6f3097RUN
ENABLE_MITMPROXY=0 /tmp/manage_cert.sh install
01/09/2026 11:26 PM UTC
088357379b5ff09243b7d7a686d081d1674ec2f15aaec1874b5a1c0e6e78d9daARG
ENABLE_MITMPROXY=0
01/09/2026 11:26 PM UTC
787ecd71c2eabe5b5dd8c1d9b4de898822a96ff815b684db451d418dc0afc977LABEL
com.nvidia.nccl.version=2.29.stable.20260109 com.nvidia.cublas.version=13.2.1.1 com.nvidia.cufft.version=12.1.0.78 com.nvidia.curand.version=10.4.1.81 com.nvidia.cusparse.version=12.7.3.1 com.nvidia.cusparselt.version=0.8.1.1 com.nvidia.cusolver.version=12.0.9.81 com.nvidia.npp.version=13.0.3.3 com.nvidia.nvjpeg.version=13.0.3.75 com.nvidia.cudnn.version=9.17.1.4
01/09/2026 11:24 PM UTC
c3c9ba9e8503edeb2a331b45d778b952764bc865778879fc47ab2da6d05b5c32RUN
ENABLE_MITMPROXY=0 CUDA_COMPONENT_LIST=cccl crt nvrtc driver-dev culibos-dev cudart cudart-dev nvcc tileiras VERSION_LIST=CURAND_VERSION CUBLAS_VERSION CUFILE_VERSION /tmp/manage_cert.sh uninstall
01/09/2026 11:24 PM UTC
533e7b8cbef5139501652dd8e5f7686202f2b686bc09a7991cd7f159372d6e4cENV
LIBRARY_PATH=/usr/local/cuda/lib64/stubs:
01/09/2026 11:24 PM UTC
e5f37157f575d653112b465201e776725167be333229d1c9847cfcd41ec55661RUN
RUN |3 ENABLE_MITMPROXY=0 CUDA_COMPONENT_LIST=cccl crt nvrtc driver-dev culibos-dev cudart cudart-dev nvcc tileiras VERSION_LIST=CURAND_VERSION CUBLAS_VERSION CUFILE_VERSION /bin/sh -c set -exo pipefail VERSION_LIST="${VERSION_LIST}" /nvidia/build-scripts/installLIBS.sh # Hack to grab stubs from the libs stage and put them under /usr/local/cuda/lib64 without actually installing the libs HACK_LIST="cusparse cusolver cufft nvJitLink" for lib in ${HACK_LIST}; do _LIB_VERSION_ENV_VAR="${lib^^}_VERSION" _LIB_MAJOR_VERSION=$(echo "${!_LIB_VERSION_ENV_VAR}" | cut -d. -f1) if [[ -z "${_LIB_MAJOR_VERSION}" ]]; then echo "[ERROR] ${_LIB_VERSION_ENV_VAR} is not set" exit 1 fi for _stub in $(ls /tmp/stubs/*${lib}*); do cp ${_stub} /usr/local/cuda/lib64/$(basename ${_stub}).${_LIB_MAJOR_VERSION} # Create a symlink to the file with .0 extension ln -sf $(basename ${_stub}).${_LIB_MAJOR_VERSION} /usr/local/cuda/lib64/$(basename ${_stub}).0 done done ( set +x; echo "[INFO] /usr/local/cuda/lib64 after hack:"; ls -larth /usr/local/cuda/lib64/ ) /nvidia/build-scripts/installCUDNN.sh /nvidia/build-scripts/installCUSPARSELT.sh NOBUILDER=1 /nvidia/build-scripts/installTRT.sh if [ ! -f /etc/ld.so.conf.d/nvidia-tegra.conf ]; then /nvidia/build-scripts/installNCCL.sh /nvidia/build-scripts/installNVSHMEM.sh # Manually create symlinks nvshmem so we don't need to use dpkg-divert
  # nvshmem default installation is under /usr/lib/x86_64-linux-gnu/nvshmem/${CUDA_VERSION_MAJOR}
  # We need to libs to be available under /usr/local/cuda/lib64
  export CUDA_VERSION_MAJOR=$(echo "${CUDA_VERSION}" | cut -d. -f1)
  find /usr/lib/*-linux-gnu/nvshmem/${CUDA_VERSION_MAJOR}/ -maxdepth 1 -type f -exec ln -sf {} /usr/local/cuda/lib64/ \;
  # For symlinks under /usr/lib/*-linux-gnu/nvshmem/${CUDA_VERSION_MAJOR}/, we want to create it under /usr/local/cuda/lib64/ and link it to the same target
  find /usr/lib/*-linux-gnu/nvshmem/${CUDA_VERSION_MAJOR}/ -maxdepth 1 -type l -exec ln -sf {} /usr/local/cuda/lib64/ \;
  # Ensure libnvshmem_host.so* files exist under /usr/local/cuda/lib64
  ls /usr/local/cuda/lib64/libnvshmem_host.so* || { echo "[ERROR] libnvshmem_host.so* not found under /usr/local/cuda/lib64"; exit 1; }
fi
 # buildkit
01/09/2026 11:24 PM UTC
6d4f2437a913e5cd169feff2841a18d51c3755096b05ca2ddbb80ff154df26a2ARG
VERSION_LIST=CURAND_VERSION CUBLAS_VERSION CUFILE_VERSION
01/09/2026 11:23 PM UTC