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Scratch the surface of the enormous technical challenge that’s confronting the backend of clouds and datacenters

Prof. Ningfang Mi gave us an excited academic talk about “Scratch the surface of the enormous technical challenge that’s confronting the backend of clouds and datacenters”, invited by School of Computer Science and Technology. Prof. Ningfang Mi is a head of the Computer System Research Laboratory of Northeastern University (NUCSRL). She is now a chair professor in our university. The talk took place at Room 109, Building S2, Xianlin Campus. The dean, Prof. Genlin Ji hosted the talk. Most of our faculties and students were present.

 Ningfang Mi is an Associate Professor in Department of Electrical and Computer Engineering (ECE) at Northeastern University since 2009. Dr. Mi graduated with a B.S. in Computer Science from Nanjing University, China in 2000 and a M.S. in Computer Science from the University of Texas at Dallas in 2004. She received her Ph.D in Computer Science from the College of William and Mary in 2009. Her research interests include cloud computing, big data processing, resource management, capacity planning, MapReduce/Hadoop scheduling, performance evaluation, simulation and virtualization. Dr. Mi was a recipient of the 2015 National Science Foundation (NSF) CAREER Award, the 2014 Air Force’s Young Investigator Research (YIP) Award and the 2010 IBM Faculty Award. She is the director of the Northeastern University Computer Systems Research Laboratory (NUCSRL) at Northeastern University.

“Amazon’s website is taking too long to load.” “The most popular YouTube video won’t stop buffering.” “Twitter is over capacity.” While these may not seem like a big deal to end users, they merely scratch the surface of the enormous technical challenge that’s confronting the backend of data centers and cloud computing. Nowadays, these large-scaled cluster systems have become an important part of contemporary computing environments. Everybody is moving their computing and data from desktops to large cluster systems, spanning from scientific computing clusters to commercial and military data centers. However, maintaining such large systems with high efficiency and high dependability at low cost is an inherently difficult problem as the complexity of these systems increases and the workflows to these systems are becoming dynamic and diverse. This requires new designs that are able to manage unplanned increases or bursts in user demands. Co-scheduling a large number of applications can further incur severe resource contention; different performance management solutions are needed to meet their varying resource and performance requirements. Therefore, in this talk, we will present our recent research work that focuses on how to leverage the knowledge of workload patterns to develop new techniques and tools for modeling, prediction, and resource management.

This rich talk gave us forward thinking. Prof. Mi communicated with us effectively and clearly. She answered all the questions from the audiences patiently. Finally, this talk ended in deafening applauses.