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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 #14996 · 07/25/2025, 12:00 PM

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#ocaml#c#go#java#javascript#python#r2c#ruby#sast#semgrep#static_analysis#static_code_analysis#typescript Semgrep is a fast, open-source tool that scans your code to find bugs and security issues in over 30 programming languages. It works locally on your computer or in your build system, so your code stays private. Semgrep’s rules are easy to write and understand, helping you catch problems early in development, whether in your IDE, pre-commit checks, or CI/CD pipelines. For stronger security, the Semgrep AppSec Platform offers advanced analysis, AI-powered triage, and detailed fix guidance, reducing false alarms and helping developers fix issues quickly without slowing down. This improves code quality and security efficiently. https://github.com/semgrep/semgrep

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