Sibyl: A system for large scale machine learning at Google
Note: This address is now available on YouTube at Tushar Chandra DSN 2014 Keynote.
Large scale machine learning is playing an increasingly important role in improving the quality and monetization of Internet properties. A small number of techniques, such as regression, have proven to be widely applicable across Internet properties and applications. Sibyl is a research project that implements these primitives at scale and is widely used within Google. In this talk I will outline Sibyl and the requirements that it places on Google's computing infrastructure.
Tushar Chandra is a Principal Engineer at Google Research and a co-lead for the Sibyl project. He received his Ph.D. in Computer Science from Cornell University in 1993, worked at IBM Research thereafter until he joined Google in 2004. He has worked on a number of distributed systems projects: Reliable Scalable Cluster Technology, Gryphon, and Oceano at IBM and Bigtable and a Paxos-based platform for fault-tolerance at Google. He was a joint winner of the 2010 Edsger W. Dijkstra Prize in Distributed Computing.
