python cuda list devices смотреть онлайн

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CUDA (Compute Unified Device Architecture) is a parallel computing platform and application programming interface model created by Nvidia. It allows developers to use Nvidia GPUs for general-purpose processing, particularly in high-performance computing tasks. In this tutorial, we'll explore how to list CUDA devices using Python with the help of the pycuda library.
Let's create a simple Python script to list the available CUDA devices using pycuda.
Import Libraries: Import the pycuda.driver module, which provides access to the CUDA driver API.
Initialize CUDA: Use cuda.init() to initialize the CUDA driver.
Get Device Count: Use cuda.Device.count() to obtain the number of available CUDA devices.
Iterate Through Devices: Loop through each CUDA device, create a cuda.Device object, and print relevant information such as device name, compute capability, total memory, multiprocessors, and CUDA cores.
Handle Errors: Use a try-except block to catch any potential CUDA errors and print an error message.
Run the Script: Finally, execute the script by calling list_cuda_devices() in the __main__ block.
This tutorial covered the basics of listing CUDA devices using Python and the pycuda library. You can further extend this script to perform GPU-accelerated computations or integrate it into larger projects that leverage GPU capabilities for enhanced performance.
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