July 28, 2022, 1:43 p.m. | Marcello Politi

Towards Data Science - Medium towardsdatascience.com

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Learn how to speed up compute-intensive applications with the power of modern GPUs

The most common deep learning frameworks such as Tensorflow and PyThorch often rely on kernel calls in order to use the GPU for parallel computations and accelerate the computation of neural networks. The most famous interface that allows developers to program using the GPU is CUDA, created by NVIDIA.

Parallel computing requires a completely different point of view from …

artificial intelligence cuda data science deep learning machine learning part programming

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