Скачать или смотреть python multiprocessing gpu cuda

Download this code from https://codegive.com
In this tutorial, we will explore how to utilize Python multiprocessing in conjunction with GPU acceleration using CUDA. We will use the multiprocessing module to parallelize tasks across multiple CPU cores and the numba library to enable CUDA-accelerated computation.
Multiprocessing allows us to split a task into smaller sub-tasks and execute them concurrently on different CPU cores. Combining multiprocessing with GPU acceleration can lead to significant performance improvements, especially for computationally intensive tasks.
Let's consider a simple example of parallel matrix multiplication using CUDA. We'll use the numpy library for CPU-based operations and numba for GPU-accelerated computations.