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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 #14862 · 06/24/2025, 01:00 PM

#typescript#codemirror#graphiql#graphql#lsp_mode#lsp_server#monaco_editor#vscode GraphiQL is a powerful, open-source GraphQL IDE that helps you write, test, and explore GraphQL queries easily in your browser or desktop. It offers features like syntax highlighting, live error checking, and schema exploration, making it simpler to work with GraphQL APIs. The project is part of a monorepo that includes tools for different editors like CodeMirror and Monaco, providing a consistent and extensible development experience. Using this monorepo setup improves collaboration, code sharing, and maintenance across related tools, saving you time and effort when building or extending GraphQL IDEs. This means you get a reliable, efficient environment to develop GraphQL applications faster and with fewer errors. https://github.com/graphql/graphiql