Paper Title: Analyzing the Effects of Storage on AI Workloads

Paper Abstract: The past decade has seen explosive growth in AI hardware, frameworks, and algorithms. This has led to some unique challenges for architecting storage systems for AI workloads. In this session I describe some of these challenges and methods for overcoming them.

Paper Author: Wes Vaske, Principal Solutions Engineer, Micron Technology

Author Bio: Wes Vaske is a Principal Solutions Engineer on the Storage Solutions Engineering team at Micron Technology in Austin, TX. He analyzes application performance for various workloads on enterprise systems such as databases and software defined storage solutions. His current focus of work is analyzing the performance of data science systems--primarily model training and inference systems. Before Micron, Wes was a Oracle Systems Engineer at Dell in the Global Solutions Engineering group analyzing the performance and design of Oracle Database systems.