CS Colloquium Series @ UCY
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Colloquium Coordinator: Demetris Zeinalipour
Colloquium: Multi-Engine Data Analytics, Dr. Dimitrios Tsoumakos (Department of Informatics of the Ionian University, Greece), Monday, October 3, 2016, 15:00-16:00 EET.
The Department of Computer Science at the University of Cyprus cordially invites you to the Colloquium entitled:
Multi-Engine Data Analytics
Speaker: Dr. Dimitrios Tsoumakos
The complexity of Big Data analytics has long outreached the capabilities of current platforms, which fail to efficiently cope with the data and task heterogeneity of modern workflows due to their adhesion to a single data and/or compute model. In this talk I present IReS, the Intelligent Resource Scheduler for complex analytics workflows executed over multi-engine environments. IReS is able to optimize a workflow with respect to a user-defined policy relying on cost and performance models of the required tasks over the available platforms. This optimization consists of allocating distinct workflow parts to the most advantageous execution and/or storage engine among the available ones and deciding on the exact amount of resources provisioned. Moreover, IReS can efficiently adapt to the current cluster/engine conditions and recover from failures by effectively monitoring the workflow execution in real-time. The current prototype supports 5 compute and 3 data engines, yet new ones can effortlessly be added to IReS by virtue of its engine-agnostic mechanisms.
Dimitrios Tsoumakos is an Assistant Professor in the Department of Informatics of the Ionian University. He is also a collaborating researcher with the Computing Systems Laboratory of the National Technical University of Athens (NTUA). He received his Diploma in Electrical and Computer Engineering from NTUA in 1999, then joined the graduate program in Computer Sciences at the University of Maryland in 2000, where he received his M.Sc. (2002) and Ph.D. (2006). His research interests relate to both systemic and data management aspects of Distributed, Large-Scale Systems: Algorithms for big-data management over distributed platforms as well as optimization aspects of Cloud Computing.
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