Professor of Computer Science, Carnegie-Mellon University
Monday, October 15, 2018 @ 11:00am
Room 1202, CSE Building
Stochastic Resource Management in the Face of Uncertainty
Maximizing computer system performance relies on careful resource management: how to best allocate resources among jobs. Effective resource allocation is most difficult in regimes with uncertainty. This talk examines three common types of uncertainty. We consider uncertainty in job sizes and ask how to optimally schedule jobs to minimize response time in such regimes. We next turn to uncertainty in the arrival rate and ask how we should adapt capacity provisioning and power management in data centers to handle unexpected load fluctuations. Finally, we consider uncertainty in the system state and look at how job replication can help curtail unpredictability. A common thread in this talk is stochastic performance modeling and the insights it illuminates.
Mor Harchol-Balter is a Professor of Computer Science at CMU. She received her Ph.D. from U.C. Berkeley in 1996 under the direction of Manuel Blum. She joined CMU in 1999, and served as the Head of the PhD program from 2008-2011. Mor is a Fellow of the ACM and a Senior Member of IEEE. She is a recipient of the McCandless Junior Chair, the NSF CAREER award, and several teaching awards, including the Herbert A. Simon Award. She has received faculty awards from a dozen companies including Google, Microsoft, IBM, EMC, Facebook, Intel, Yahoo!, and Seagate. Mor's work focuses on designing new resource allocation policies, including load balancing policies, power management policies, and scheduling policies. Mor is heavily involved in the SIGMETRICS/PERFORMANCE research community, where she has received many best paper awards, and where she served as TPC Chair in 2007, as General Chair in 2013, and as the Keynote Speaker for 2016. She is also the author of a popular textbook, "Performance Analysis and Design of Computer Systems," published by Cambridge University Press, which bridges Operations Research and Computer Science.