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Source channel @githubtrending · Post #14985 · Jul 22

#c_lang#cuda#cuda_driver_api#cuda_kernels#cuda_opengl You can use the CUDA Samples from NVIDIA to learn and test CUDA Toolkit 12.9 features by downloading them from GitHub or as a ZIP file. These samples show how to use CUDA for GPU programming, including utilities, concepts, libraries, and performance optimization. You build them with CMake on Linux, Windows, or Tegra devices, and can run tests automatically with a provided Python script. This helps you understand CUDA programming, debug GPU code, and optimize your applications for better performance on NVIDIA GPUs. It’s a practical way to develop and improve GPU-accelerated software efficiently. https://github.com/NVIDIA/cuda-samples

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@githubtrending · Post #15419 · 01/17/2026, 09:30 AM

#python#agent#ai#aippt#editable_pptx#langgraph#paper2slides#ppt_generator Paper2Any turns paper PDFs, images, or text into editable diagrams, technical roadmaps, experiment plots, PPT slides, and more with one click. Key tools include Paper2Figure for scientific visuals, Paper2PPT for custom decks with table extraction, PDF2PPT for layout-perfect conversions, and AI beautification. Install via GitHub on Python 3.11+, Linux preferred; try online demo or scripts. You save hours recreating figures or slides for research, talks, or reports, getting pro-quality, customizable outputs fast. https://github.com/OpenDCAI/Paper2Any