ABOUT THE TALK

In his talk Ion will discuss Ray a distributed system to address demanding systems requirements in AI apps. Since the next generation of AI applications will continuously interact with the environment and learn from these interactions. These applications impose new and demanding systems requirements, both in terms of performance and flexibility. In his talk Ion will walk us through a distributed system to address them: Ray and how it implements a unified interface that can express both task-parallel and actor-based computations, supported by a single dynamic execution engine.

To meet the performance requirements, Ray employs a distributed scheduler and a distributed and fault-tolerant store to manage the system's control state. In his talk he will demonstrate scaling beyond 1.8 million tasks per second and better performance than existing specialized systems for several challenging reinforcement learning applications.

Ion Stoica

Professor | Rise Lab (UC Berkeley)

Ion Stoica is a Professor in the EECS Department at University of California at Berkeley. He does research on cloud computing and networked computer systems. Past work includes Dynamic Packet State, Chord DHT, Internet Indirection Infrastructure (i3), declarative networks, and large scale systems, including Apache Spark, Apache Mesos, and Alluxio.

He is an ACM Fellow and has received numerous awards, including the SIGOPS Hall of Fame (2015), the SIGCOMM Test of Time Award (2011), and the ACM doctoral dissertation award (2001). In 2006, he co-founded Conviva, a startup to commercialize technologies for large scale video distribution, and in 2013, he co-founded Databricks a startup to commercialize Apache Spark.

Ion Stoica
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