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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
Search: #xmlrpc
@djangoproject · Post #408 · 08/10/2017, 10:42 AM
https://docs.python.org/3/library/xmlrpc.html #XML-#RPC is a #Remote_Procedure_Call method that uses XML passed via #HTTP as a transport. With it, a #client can call methods with parameters on a remote server (the #server is named by a URI) and get back structured data. #xmlrpc is a package that collects server and client modules implementing XML-RPC. The modules are: xmlrpc.client xmlrpc.server