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HardBD 2016 : International Workshop on Big Data Management on Emerging Hardware

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Link: http://idke.ruc.edu.cn/HardBD2016/
 
When May 20, 2016 - May 20, 2016
Where Helsinki, Finland
Submission Deadline Jan 25, 2016
Notification Due Feb 7, 2016
Final Version Due Feb 15, 2016
 

Call For Papers

*Important update: we will collaborate with special section on data management and data mining in Journal of Computer Science and Technology (JCST, see details in JCST CFP http://jcst.ict.ac.cn:8080/jcst/EN/column/item145.shtml). First, the extensions of 1-2 best papers will be recommended to the special section. Second, we will encourage the extensions of other paper submissions to the special section.*

Data properties and hardware characteristics are two key aspects for efficient data management. A clear trend in the first aspect, data properties, is the increasing demand to manage and process Big Data in both enterprise and consumer applications, characterized by the fast evolution of “Big Data Systems”. Examples of big data systems include NoSQL storage systems, MapReduce/Hadoop, data analytics platforms, search and indexing platforms, messaging infrastructures, event log processing systems, as well as novel extensions to relational database systems. These systems address needs for processing structured, semi-structured, and unstructured data across a wide spectrum of domains such as web, social networks, enterprise, mobile computing, sensor networks, multimedia/streaming, cyber-physical and high performance systems, and for a great many application areas such as e-commerce, finance, healthcare, transportation, telecommunication, and scientific computing.

At the same time, the second aspect, hardware characteristics, is undergoing rapid changes, imposing new challenges for the efficient utilization of hardware resources. Recent trends include massive multi-core processing systems, high performance co-processors, very large main memory systems, storage-class memory, fast networking interconnects, big computing clusters, and large data centers that consume massive amounts of energy.

Utilizing new hardware technologies for efficient Big Data management is of urgent importance. However, many essential issues in this area have yet to be explored, including system architecture, data storage, indexes, query processing, energy efficiency and proportionality, and so on. The aim of this half-day workshop is to bring together researchers, practitioners, system administrators, and others interested in this area to share their perspectives on the efficient management of big data over new hardware platforms, and to discuss and identify future directions and challenges in this area.

[Submissions are managed through CMT] https://cmt.research.microsoft.com/HARDBD2016/

Topics of interest include but not limited to:
● New systems architecture
● New storage devices and indexes
● Query processing
● Transaction processing
● Energy-efficient and energy-proportional data processing
● Benchmarking
● Fault management and reliability
● Heterogeneous hardware
● Main memory data management
● Sustainable power management
● Scalable and reconfigurable challenges

*Submission Guidelines
Papers should be prepared in the IEEE format and submitted as a single PDF file. The paper length should not exceed 6 pages.

*Workshop Co-Chairs
Shimin Chen, Chinese Academy of Sciences, chensm@ict.ac.cn
Bingsheng He, Nanyang Technological University, Singapore, bshe@ntu.edu.sg
Xiaofeng Meng, Renmin University of China, xfmeng@ruc.edu.cn

*PC members for the workshop
Philippe Bonnet, IT University of Copenhagen
Bin Cui, Peking University, China
Qiong Luo,Hong Kong University of Science and Technology, China
Peiquan Jin, University of Science and Technology of China (USTC), China
Ioannis Koltsidas, IBM Zurich
Jianliang Xu, Hong Kong Baptist University, China
Sang-Wook Kim, Hanyang University, Korea
Bongki Moon, Seoul National University, South Korea
Yinan Li, Microsoft Research, USA
Vo Hoang Tam, IBM Australia, Australia
Zeke Wang, Nanyang Technological University, Singapore
Eric Lo, Hong Kong Polytechnic University, China
Theo Harder, University of Kaiserslautern
Sebastian Bre? TU Dortmund
Witold Andrzejewski,Poznan University of Technology, Poland,
Sang-Won Lee, Sungkyunkwan University, South Korea

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