Closed akielaries closed 1 year ago
Updating the kernel is very risk full. You can easily end up with conflicting dependencies. See https://github.com/Qengineering/Jetson-Nano-image/issues/32 Perhaps in the end, you may succeed. However I would strongly recommend not to do so. Besides, the CUDA tool chain is already installed as you can see below.
Ah interesting, I had done a fresh install of the base image but noticed none of the CUDA toolkit was included in image. Is the base CUDA toolchain (not TensorFlow or OpenCV related libs) not included in the base installation?
Let me try a fresh installation once more and list what dpkg is aware of
When I was trying to do my own installation of a more recent version of CUDA and its driver it had bricked the initial installation from the image. Reinstall worked and was able to have the toolchain all present
jetson@nano:~$ dpkg -l | grep cuda
ii cuda-command-line-tools-10-2 10.2.460-1 arm64 CUDA command-line tools
ii cuda-compiler-10-2 10.2.460-1 arm64 CUDA compiler
ii cuda-cudart-10-2 10.2.300-1 arm64 CUDA Runtime native Libraries
ii cuda-cudart-dev-10-2 10.2.300-1 arm64 CUDA Runtime native dev links, headers
ii cuda-cuobjdump-10-2 10.2.300-1 arm64 CUDA cuobjdump
ii cuda-cupti-10-2 10.2.300-1 arm64 CUDA profiling tools runtime libs.
ii cuda-cupti-dev-10-2 10.2.300-1 arm64 CUDA profiling tools interface.
ii cuda-documentation-10-2 10.2.300-1 arm64 CUDA documentation
ii cuda-driver-dev-10-2 10.2.300-1 arm64 CUDA Driver native dev stub library
ii cuda-gdb-10-2 10.2.300-1 arm64 CUDA-GDB
ii cuda-libraries-10-2 10.2.460-1 arm64 CUDA Libraries 10.2 meta-package
ii cuda-libraries-dev-10-2 10.2.460-1 arm64 CUDA Libraries 10.2 development meta-package
ii cuda-memcheck-10-2 10.2.300-1 arm64 CUDA-MEMCHECK
ii cuda-nvcc-10-2 10.2.300-1 arm64 CUDA nvcc
ii cuda-nvdisasm-10-2 10.2.300-1 arm64 CUDA disassembler
ii cuda-nvgraph-10-2 10.2.300-1 arm64 NVGRAPH native runtime libraries
ii cuda-nvgraph-dev-10-2 10.2.300-1 arm64 NVGRAPH native dev links, headers
ii cuda-nvml-dev-10-2 10.2.300-1 arm64 NVML native dev links, headers
ii cuda-nvprof-10-2 10.2.300-1 arm64 CUDA Profiler tools
ii cuda-nvprune-10-2 10.2.300-1 arm64 CUDA nvprune
ii cuda-nvrtc-10-2 10.2.300-1 arm64 NVRTC native runtime libraries
ii cuda-nvrtc-dev-10-2 10.2.300-1 arm64 NVRTC native dev links, headers
ii cuda-nvtx-10-2 10.2.300-1 arm64 NVIDIA Tools Extension
ii cuda-repo-l4t-10-2-local 10.2.460-1 arm64 cuda repository configuration files
ii cuda-samples-10-2 10.2.300-1 arm64 CUDA example applications
ii cuda-toolkit-10-2 10.2.460-1 arm64 CUDA Toolkit 10.2 meta-package
ii cuda-tools-10-2 10.2.460-1 arm64 CUDA Tools meta-package
ii cuda-visual-tools-10-2 10.2.460-1 arm64 CUDA visual tools
ii graphsurgeon-tf 8.2.1-1+cuda10.2 arm64 GraphSurgeon for TensorRT package
ii libcudnn8 8.2.1.32-1+cuda10.2 arm64 cuDNN runtime libraries
ii libcudnn8-dev 8.2.1.32-1+cuda10.2 arm64 cuDNN development libraries and headers
ii libcudnn8-samples 8.2.1.32-1+cuda10.2 arm64 cuDNN documents and samples
ii libnvinfer-bin 8.2.1-1+cuda10.2 arm64 TensorRT binaries
ii libnvinfer-dev 8.2.1-1+cuda10.2 arm64 TensorRT development libraries and headers
ii libnvinfer-doc 8.2.1-1+cuda10.2 all TensorRT documentation
ii libnvinfer-plugin-dev 8.2.1-1+cuda10.2 arm64 TensorRT plugin libraries
ii libnvinfer-plugin8 8.2.1-1+cuda10.2 arm64 TensorRT plugin libraries
ii libnvinfer-samples 8.2.1-1+cuda10.2 all TensorRT samples
ii libnvinfer8 8.2.1-1+cuda10.2 arm64 TensorRT runtime libraries
ii libnvonnxparsers-dev 8.2.1-1+cuda10.2 arm64 TensorRT ONNX libraries
ii libnvonnxparsers8 8.2.1-1+cuda10.2 arm64 TensorRT ONNX libraries
ii libnvparsers-dev 8.2.1-1+cuda10.2 arm64 TensorRT parsers libraries
ii libnvparsers8 8.2.1-1+cuda10.2 arm64 TensorRT parsers libraries
ii nvidia-container-csv-cuda 10.2.460-1 arm64 Jetpack CUDA CSV file
ii nvidia-container-csv-cudnn 8.2.1.32-1+cuda10.2 arm64 Jetpack CUDNN CSV file
ii nvidia-container-csv-tensorrt 8.2.1.8-1+cuda10.2 arm64 Jetpack TensorRT CSV file
ii nvidia-l4t-cuda 32.7.2-20220420143418 arm64 NVIDIA CUDA Package
ii tensorrt 8.2.1.8-1+cuda10.2 arm64 Meta package of TensorRT
ii uff-converter-tf 8.2.1-1+cuda10.2 arm64 UFF converter for TensorRT package
I am using your base 20.04 image and notice the kernel was on an old version still. Is it possible to upgrade the kernel on your image or will this break some existing compatibility?
I am trying to install the CUDA toolchain but had seen the warning in the
README
that v11 and beyond are not compatible with the Jetson's hardware, what version and kernel driver should we target for this image?