GPU programming involves utilizing the parallel processing capabilities of Graphics Processing Units (GPUs) to accelerate computationally intensive tasks. Unlike CPUs which are designed for general-purpose tasks, GPUs excel at performing the same operation on multiple data points simultaneously. This makes them well-suited for applications like machine learning, scientific simulations, image processing, and video editing, where large datasets need to be processed quickly. Frameworks like CUDA and OpenCL provide APIs and tools for developing GPU-accelerated applications.
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