Tutorials/Accelerated Python: Rebase to NVIDIA CUDA 13.1 base container.#132
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… Brev to ensure Nsight tools can run as non-root.
…rofiling instead of reloading NVIDIA modules.
…hon which lacks Nsight tools.
…and relax profiling permissions at container startup.
…fully-qualified paths in ncu and nsys wrappers.
…version variables are resolved.
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Rebase the accelerated-python tutorial to use the same NVIDIA CUDA 13.1 base container as the cuda-tile tutorial (
ghcr.io/nvidia/mirrors/nvidia-cuda-13.1.0-devel-ubuntu22.04).Changes
Dockerfile
rapidsai-devcontainers-25.08-cpp-cuda12.8tonvidia-cuda-13.1.0-devel-ubuntu22.04.cu128tocu130withtorch==2.10.0.cudf-cu12/cuml-cu12tocudf-cu13/cuml-cu13.PYTHON_VERSION,PATH, Nsight version vars; removePYTHONSTARTUP.libglib2.0-0(matching cuda-tile).requirements.txt
nvidia-cublas-cu12,nvidia-nvshmem-cu12,nvidia-cuda-nvcc-cu12,nvidia-cuda-nvrtc-cu12(provided by the devel base container).