Christina Delimitrou, Assistant Professor in the School of Electrical and Computer Engineering at Cornell University recently received a U.S. National Science Foundation Early Career Development (NSF CAREER) Award from the Division of Computing and Communication Foundations (CCF). The award supports her research proposal, “Learning-Based Hardware and Software Techniques for Quality-of-Service-Aware Cloud Microservices” for a five-year period from 2019 through 2024 with a total amount of $500,000.
According to the award’s abstract, datacenters support a large and ever-increasing fraction of the world's digital computation power, including search engines, social networks, and machine learning analytics. As modern cloud services grow in popularity, their design shifts from supporting complex monolithic applications, to supporting collections of specialized, loosely-coupled microservices. Such microservices impact resource requirements by requiring fast network processing and low-latency memory accesses to achieve their quality-of-service (QoS) constraints. Dependencies among microservices also complicate compute cluster management, and can cause cascading QoS violations, hurting availability and service reliability. Guaranteeing the responsiveness expected from cloud services while using datacenters efficiently requires instead a joint hardware-software approach.
This project takes a holistic view towards designing a system stack for interactive cloud microservices running on large-scale datacenters that is QoS-aware, and resource-efficient. By pursuing automated, learning-based techniques, this project highlights the value of leveraging practical machine learning techniques to better navigate the increasing complexity of the cloud, as more datacenter services switch to this new application model.
Delimitrou is a member of the Computer Systems Laboratory where she works on improving the design and management of large-scale datacenters. In 2015-2016 she was a postdoctoral researcher and lecturer at Stanford University. Christina graduated from Stanford with a Ph.D. in Electrical Engineering in 2015. As part of her Ph.D. work, she built practical systems for cluster management and scheduling in warehouse-scale computers. She is the recipient of a Google Faculty Research Award, a Facebook Faculty Award, a VMWare Research Award, and previously, a Facebook Research Fellowship, and a Stanford Graduate Fellowship. She has also received three IEEE Micro Top Picks awards, two ASPLOS best paper runner-up awards, and an IISWC 2012 best paper nomination. Christina previously also earned an M.S. from Stanford in 2011 and a diploma in Electrical and Computer Engineering from the National Technical University of Athens in 2009.
Delimitrou’s primary interests are in computer architecture and distributed systems, including the design and management of large-scale datacenters, hardware acceleration, applied data mining, performance monitoring and debugging, and cloud security.
According to the NSF, “The Faculty Early Career Development (CAREER) Program is a Foundation-wide activity that offers the National Science Foundation's most prestigious awards in support of early-career faculty who have the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization. Activities pursued by early-career faculty should build a firm foundation for a lifetime of leadership in integrating education and research.”