Speed Cubing for Machine Learning - Episode 2

N. Morizet, Towards Data Science, November 20th, 2020.

Abstract: In Episode 1, we described how to generate 3D data as fast as possible to feed some Generative Adversarial Networks, using CPUs, multithreading and Cloud resources. We reached a rate of 2 billion data points per second !

In this Episode 2, we are going to benefit from GPUs through a dedicated framework called RAPIDS. Also, we will see how to visualize the generated data, thanks to a GPU accelerated library named VisPy.

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