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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 #65322 · 04/12/2026, 11:03 PM

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🚀 AI TRENDS | MiniMax M2.7 Open Source Launches Globally with Key Partnerships On April 13, Jin10 reported that MiniMax, a domestic AI model company, announced the global open-source release of MiniMax M2.7 on April 12. According to Jin10, the launch involved collaborations with major chip manufacturers and inference platforms, including Huawei Ascend, Moore Threads, Muxi, Kunlunxin, NVIDIA, Together AI, Fireworks, and Ollama. On the first day of the open-source release, the model integration and inference adaptation were successfully completed. #AI#MiniMax#M2.7 #OpenSource#GlobalLaunch#Partnerships#HuaweiAscend#MooreThreads#Muxi#Kunlunxin#NVIDIA#TogetherAI#Fireworks#Ollama#InferencePlatforms#ChipManufacturers

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#ai #minimax #m2 #opensource #globallaunch #partnerships #huaweiascend #moorethreads #muxi #kunlunxin #nvidia #togetherai #fireworks #ollama #inferenceplatforms #chipmanufacturers