posted by user: sebastianbress || 269 views || tracked by 1 users: [display]

HardBD 2017 : International Workshop on Big Data Management on Emerging Hardware

FacebookTwitterLinkedInGoogle

Link: http://hardbd2017.dfki.de/
 
When Apr 22, 2017 - Apr 22, 2017
Where San Diego, CA, USA
Submission Deadline Dec 6, 2016
Notification Due Jan 6, 2017
Final Version Due Jan 20, 2017
Categories    emerging hardware   big data
 

Call For Papers

International Workshop on Big Data Management on Emerging Hardware (HardBD 2017)
To be Sponsored by and Held in Conjunction with ICDE 2017 (San Diego, CA)

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. 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


Organizers

- Sebastian Breß, German Research Center for Artificial Intelligence, sebastian.bress@dfki.de
- Vassilis J. Tsotras, University of California - Riverside, tsotras@cs.ucr.edu

PC members for the workshop

- Max Heimel, Snowflake
- Tim Kraska, Brown University
- Justin Levandoski, Microsoft Research
- Walid Najjar, University of California - Riverside
- Mohammad Sadoghi, Purdue University
- Kai-Uwe Sattler, Ilmenau University of Technology
- Jens Teubner, TU Dortmund University
- Stratis Viglas, University of Edinburgh
- Xiaodong Zhang, Ohio State University


Important dates of the workshop

Paper submission: December 6, 2016
Notification of acceptance: January 6, 2017
Camera-ready copies: January 20, 2017
Workshop: April 22, 2017

Submission Guidelines

Papers can be submitted in three tracks: abstracts, short papers, and regular research papers. Abstracts have a limit of one page and should sketch the ongoing work that is to be presented. Regular research papers have a limit of eight pages (including references) and short papers have a limit of four pages (including references). They should present novel ideas, visionary thoughts, or new experimental evaluations. If accepted, authors are expected to give a 20 minute presentation during the workshop.

For submissions to all tracks, authors are requested to prepare their papers following the IEEE double-column format of the ICDE 2017 using the templates available at http://icde2017.sdsc.edu/submission-guidelines. Papers must be uploaded as PDF files to the submission website at https://easychair.org/conferences/?conf=hardbd2017. Each paper will be reviewed by PC members in a single-blind process.

Website: http://hardbd2017.dfki.de/

Related Resources

ICIEM 2016   International Conference on Integrated Environmental Management for Sustainable Development
ICBDA 2017   The 2017 IEEE International Conference on Big Data Analysis (ICBDA 2017) - Ei Compendex
CIKM 2017   The 26th 2017 ACM Conference on Information and Knowledge Management
IEEE-ICCCBDA 2017   2nd International Conference on Cloud Computing and Big Data Analysis ICCCBDA -IEEE,Ei Compendex
BDCloud 2017   The 7th IEEE International Conference on Big Data and Cloud Computing
DSAA 2017   The 4th IEEE International Conference on Data Science and Advanced Analytics 2017
HDMM 2017   2nd International Workshop on Health Data Management and Mining (HDMM) 2017
Big Data- ADDS 2017   Special Issue on Big Data Analytics & Data-Driven Science
CEWIT 2017   13th International Conference & Expo on Emerging Technologies for a Smarter World
Elsevier JOCS NCP&BD 2017   Elsevier Journal of Computational Science (SCI IF=1.078) Special Issue on The Convergence of New Computing Paradigms and Big Data Analytics Methodologies for Online Social Networks