José Quenum
José Quenum is a Researcher at the Namibia University of Science and Technology (NUST). His interests include Distributed Systems, Artificial Intelligence and Big Data.
Session
This talk discusses our efforts to implement artificial intelligence (AI) workloads on a Ray commodity cluster using the Julia programming language. Similar to Apache Spark, Ray is a cluster computing environment for data analytics and AI workloads, mainly in Python. First, we present the configurations and setup steps for a Ray cluster. Next, we discuss the implementation of three distributed clustering algorithms in Ray: partition-based (a variant of distributed KMeans), hierarchical (the PACk algorithm), and graph (filtered graphs with a distributed hierarchical bubble tree). Specifically, we emphasise the integration of Julia and Python within Ray. Finally, we contrast the Ray environment to Apache Spark and highlight the lessons learned (limitations and advantages) throughout this experiment.