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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 #14969 · 07/17/2025, 11:30 AM

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#cplusplus#artificial_intelligence#cloud#cloud_native#cncf#container#docker#edge_computing#ewasm#hacktoberfest#hacktoberfest2023#kubernetes#rust_lang#serverless#wasm#webassembly WasmEdge is a fast, lightweight, and secure WebAssembly runtime that lets you run programs safely on your devices, servers, or the cloud. It supports many programming languages like C++, Rust, and JavaScript, and can run AI models, microservices, and smart contracts efficiently. WasmEdge offers strong security by isolating programs, making it great for extending software safely. It works well on edge devices, smart devices, and cloud environments, and supports easy integration with tools like Kubernetes and Docker. Using WasmEdge helps you run powerful applications faster, safer, and more flexibly on various platforms[1][2][3][4][5]. https://github.com/WasmEdge/WasmEdge

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#cplusplus #artificial_intelligence #cloud #cloud_native #cncf #container #docker #edge_computing #ewasm #hacktoberfest #hacktoberfest2023 #kubernetes #rust_lang #serverless #wasm #webassembly