Through a series of 4 blog posts, we’ll discuss and provide working examples of how one can use the open-source library Ray to (a) scale computing locally (single machine), (b) distribute scaling remotely (multiple-machines), and (c) serve deep learning models across a cluster (basic/advanced). Please note that the blog posts in this series increasingly raise in difficulty!
I am personally very excited by the opportunities afforded by Ray, its been a long time desire to have such an easy-to-use library!
Okay, lets start off by talking about scaling local computation with Ray!
Continue reading Ray: An Open-Source Api For Easy, Scalable Distributed Computing In Python – Part 1 Local Scaling