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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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@djangoproject · Post #516 · 12/07/2017, 07:12 AM
https://pyvisa.readthedocs.io/en/stable/ PyVISA: #Control your instruments with Python #PyVISA is a Python package that enables you to control all kinds of measurement devices independently of the interface (e.g. #GPIB, #RS232, #USB, #Ethernet). As an example, reading self-identification from a Keithley Multimeter with GPIB number 12 is as easy as three lines of Python code:
@GetMoeCats · Post #563 · 02/13/2024, 01:18 PM
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