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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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Crypto M - Crypto News

@CryptoM · Post #65388 · 04/13/2026, 04:14 AM

🚀 AINFT Platform Surpasses 700,000 Users, Advances in Web3 AI The AINFT platform has officially exceeded 700,000 users, according to official data. According to Odaily, the growing user base and the continuous enhancement of AI model capabilities are propelling it to become a leading AI platform in the Web3 sector. AINFT currently offers users AI models ready for production and fully supports the execution of on-chain automated workflows, facilitating a rapid transition from creative ideas to on-chain implementation. Leveraging its expanding community and open technical architecture, AINFT aims to lower the barriers to using Web3 AI, enabling more efficient deployment of innovative applications. #AINFT#700000Users#Web3#AIPlatform#AI#Blockchain#OnChain#AutomatedWorkflows#Web3AI#Innovation#Technology#Community