Tutorials/CUDA C++: Rebase on to CUDA 13.1 container

[brycelelbach]

Rebase the CUDA C++ tutorial from rapidsai-devcontainers-25.10-cpp-cuda12.9 to the nvidia-cuda-13.1.0-devel-ubuntu22.04 base image (CUDA 13.1), and modernize the setup to match the accelerated-python tutorial.

Changes

tutorials/cuda-cpp/brev/dockerfile

• Base image: rapidsai-devcontainers-25.10-cpp-cuda12.9 → nvidia-cuda-13.1.0-devel-ubuntu22.04
• Install Python 3.12 from deadsnakes PPA (base image no longer bundles Python)
• Structured ENV block with PIP_DISABLE_PIP_VERSION_CHECK, VIRTUAL_ENV_DISABLE_PROMPT, updated PATH
• System packages installed with DEBIAN_FRONTEND=noninteractive and comprehensive package list
• Passwordless sudo setup matching accelerated-python
• Docker installation cleaned up
• Use Nsight tools from the CUDA toolkit (/usr/local/cuda/bin/nsys, /usr/local/cuda/bin/ncu)
• Jupyter announcements disabled
• Clean layer ordering: system packages → sudo → Python → Docker → pip → Jupyter config → COPY

tutorials/cuda-cpp/brev/docker-compose.yml

• No functional changes (kept existing configuration)

tutorials/cuda-cpp/brev/requirements.txt

• Added explicit jupyterlab dependency

tutorials/cuda-cpp/brev/test.bash

• Added elapsed time reporting

[nv-kriehl]

@gevtushenko Can you please review this pull request for the C++ tutorial?

[github-actions]

❌ Link Check Failed

Broken links were detected in this PR.

Please check the workflow run logs for details on which links are broken.

Common fixes:

1. Typo in URL - Check for spelling mistakes in the link
2. Outdated link - The page may have moved or been deleted
3. Relative path issue - Ensure relative links use the correct path
4. External site down - If the external site is temporarily down, you can add it to brev/.lycheeignore

To test links locally:

./brev/test-links.bash .

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