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学术讲座:Scalable Big Data Management on clouds and HPC systems

阅读数:231    发布:2017-11-03 15:14    更新:2017-11-03 21:55    

Title:Scalable Big Data Management on clouds and HPC systems
时间:11月9日上午10:30
地点:科技楼1304会议室


Abstract:
We live in the era of Big Data, where the size of data generated by digital media, social networks and scientific instruments is increasing at an extreme rate. To realize the potential benefits of Big Data in practice (e.g., harnessing scientific discoveries, accelerating big and small business, and so on), we need to deal with several challenging issues, among which, data management is an important one. As the current data management techniques and infrastructure strain under the added weight of Big Data, there is a call for a paradigm shift in large scale data management and processing mechanisms (e.g., MapReduce, key-value stores) and computing infrastructure (e.g., Clouds, Exascale systems). In this talk, I will present recent work on addressing the main challenges when managing (storing, processing) big data at large-scale including I/O interference, performance variability, fault-tolerance, consistency, and so on.


Bio:
Shadi Ibrahim is a tenured Research Scientist in the Ascola/STACK team at Inria Rennes Bretagne Atlantique research center. He obtained his Ph.D. in Computer Science from Huazhong University of Science and Technology (HUST) in Wuhan of China in 2011. From November 2011 to September 2013, he was a Post-Doc researcher within the KerData team working on scalable Big Data managements on clouds. Since October 2013, he was hired as a permanent research scientist at Inria. He has served as a PC member for several international conferences in cloud, HPC and parallel and distributed systems (ACM/IEEE SC, IEEE ICPP, IEEE Cluster, ACM/IEEE CCGrid), and as Program co-chair for the 2018 IEEE International Congress on Big Data, the CEBDA 2018 Workshop, the 2017 ICA3PP conference, the 2017 EBDMA Workshop; and the PhD consortium of the 2014 CloudCom conference. His current research interests are in Big data management, Data-Intensive computing, HPC, cloud and Edge computing, virtualization technology, and file and storage systems. His papers are published in prestigious international journals (such as ACM ToPC, IEEE TPDS and FGCS) and proceedings (such as ACM/IEEE SuperComputing, IEEE ICDCS, IEEE IPDPS, and IEEE ICPP). He is currently leading the ANR KerStream project and is a member the DISCOVERY Inria Project Lab and JLESC (Joint Laboratory on Extreme-Scale Computing). 

深圳大学计算机与软件学院 2009-2016