#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
LinkWarden
Self-hosted, open-source #bookmark + archive manager to collect, and save websites for offline use.
The objective is to have a self-hosted place to keep useful links in one place, and since useful links can go away (see the inevitability of Link Rot), LinkWarden also saves a copy of the link as screenshot and PDF.
https://github.com/Daniel31x13/link-warden
📖 Inside the First Art Gallery for Blind Artists and Audiences #bookmark#raindrop
https://www.thrillist.com/travel/nation/envision-arts-gallery-wichita-kansas