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.