The new book "Ray Tracing Gems" (http://raytracinggems.com, free electronically) is a collection of 32 articles by experts in the field. Authors of selected articles will discuss their papers and present recent updates to their work.
Meeting the latency requirements of 5G networks requires massive parallelization. We'll discuss how to parallelize and map certain radio access network (RAN) functions to GPU architectures to achieve orders-of-magnitude acceleration. We'll describe how to realize selected RAN functions using online machine learning methods. We'll also explore the possibility of a machine learning function orchestrator (MLFO) in the context of end-to-end network slicing where deep neural networks are an interesting option. Our talk will use findings of the ITU-T focus group on machine learning for 5G to explore the challenge of implementing MLFO, leading to new mobile network architectures.