Fwd: TODAY- CS Colloquium on Monday, March 2 - Christina Delimitrou
Jason Hennessey
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| Subject: | [Colloquium] TODAY: CS Colloquium on Monday, March 2 - Christina Delimitrou |
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| Date: | Mon, 2 Mar 2015 16:56:47 +0000 |
| From: | Sweetland, Gioia <gi...@seas.harvard.edu> |
| To: | colloquium <collo...@seas.harvard.edu>, cs-researchers <cs-rese...@seas.harvard.edu>, cs-visitors <cs-vi...@seas.harvard.edu>, cs-gradstudents <cs-grad...@seas.harvard.edu>, cs-undergrads <cs-und...@seas.harvard.edu>, cs-faculty <cs-fa...@seas.harvard.edu> |
Christina Delimitrou will give a talk entitled “Improving Resource Efficiency in Cloud Computing”
Monday, March 2, 2015
4:00 p.m.
Maxwell Dworkin G115
Refreshments at 3:30 p.m. – Maxwell Dworkin 2nd floor lounge
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“Improving Resource Efficiency in Cloud Computing”
Abstract: Cloud computing promises flexibility, high performance and low cost. Despite its prevalence, most datacenters hosting cloud computing services still operate at very low utilization, posing serious scalability concerns.
The goal of my work is to improve the efficiency of these systems, while guaranteeing high performance for each submitted application. A crucial system component to achieve this goal is the cluster manager; the system that orchestrates where applications are placed and how many resources they receive. In this talk, I will describe a new approach in cluster management that relies on two main insights. First, it automates resource management by leveraging practical data mining techniques. Second, it provides the user with a high-level, declarative interface that centers around performance, not raw resources. Using these insights, I designed and built a datacenter scheduler (Paragon), a cluster manager (Quasar), and scalable provisioning systems for public clouds. In settings with several hundred servers, I demonstrated that this approach achieves high application performance and improves system utilization by over 2x. Several production systems, including Twitter and AT&T, have since adopted similar cluster management approaches.
Bio: Christina Delimitrou is a PhD candidate in the EE Department at Stanford University, working in computer architecture and systems. As part of her PhD work, she built practical systems for cluster management and scheduling in large-scale datacenters. She is the recipient of a Facebook Research Fellowship and a Stanford Graduate Fellowship. She has earned an MS from Stanford and a diploma in Electrical and Computer Engineering from the National Technical University of Athens.