Special Session on Parallel Data Processing at the World Congress on Information and Communication Technologies (PDP@WICT 2012)

October 30 - November 02
Trivandrum, India

http://www.mirlabs.net/wict12/ss16.html
http://www.mirlabs.net/wict12


Important dates
Paper submission due: *** Aug. 31, 2012 ***
Notification of paper acceptance: Sep. 15, 2012
Final manuscript due: Sep. 30, 2012
Registration and full payment due: Sep. 30, 2012
Conference date: Oct. 30-31, Nov. 1-2, 2012

Processing large datasets generated by research and industry represents one of the most important challenges in data mining. The growing volumes of data represent an opportunity for the application of data processing and data mining methods. Although advanced data analysis is the main goal of data mining, even general processing of large volumes of high-dimensional data is extremely time-consuming and in conclusion unusable for practical applications.
Parallel processing has been clearly identified as one of the most effective methods for fast solution of complex data-intensive problems. The emergence of inexpensive parallel computers such as commodity desktop multiprocessors, clusters of workstations or PCs, grids, and GPUs has made such parallel methods generally applicable.
Data-intensive applications such as information retrieval, data mining, and data analysis have established a new challenge for the modern generation of parallel platforms. Emerging areas such as computational biology and nanotechnology have implications for algorithms and systems development, while fast changes in architectures and programming models and applications have implications for how parallel platforms can be used to solve practical problems.
The special session seeks contributions about foundations of parallel data processing as well as case studies, empirical, and other methodological works related to models, tools, and environments for concurrent analysis of data. It will provide an opportunity to disseminate latest results in this growing field.
The main topics cover the design and use of various models, algorithms, tools, libraries, and environments for the design and implementation of parallel approaches to data-intensive applications.

Recommended topics include but are not limited to the following:
1. Parallel data processing algorithms
2. Parallel knowledge discovery
3. Parallel pattern detection and matching
4. Parallel classification and clustering
5. Multicore data processing on the CPUs and beyond
6. Manycore data processing on the GPUs and beyond
7. Distributed data processing
8. Parallel data processing in the cloud and on the Web
9. Performance analysis of parallel data processing
10. Parallel processing of streams of data
11. Implementation issues of parallel data processing
12. Platforms and tools for parallel data processing
13. Applications of parallel data processing

Session Chair/Cochairs
1. Václav Snášel, Department of Computer Science, VSB - Technical University of Ostrava, vaclav.snasel@vsb.cz
2. Pavel Krömer, Department of Computer Science, VSB - Technical University of Ostrava, pavel.kromer@vsb.cz
3. Petr Gajdoš, Department of Computer Science, VSB - Technical University of Ostrava,
petr.gajdos@vsb.cz

Contacts
Pavel Krömer, pavel.kromer@vsb.cz
Eliška Ochodková, eliska.ochodkova@vsb.cz

Program committee (tentative)
Vaclav Snasel, VSB-Technical University of Ostrava, Czech Republic
Milos Kudelka, VSB-Technical University of Ostrava, Czech Republic
Pavel Kromer, VSB-Technical University of Ostrava, Czech Republic
Jan Platos, VSB-Technical University of Ostrava, Czech Republic
Pavel Moravec, VSB-Technical University of Ostrava, Czech Republic
Petr Gajdos, VSB-Technical University of Ostrava, Czech Republic
Jan Martinovic, VSB-Technical University of Ostrava, Czech Republic
Dusan Husek, Institute of Computer Science, Academy of Science, Czech Republic
Ivan Zelinka, VSB-Technical University of Ostrava, Czech Republic
Petr Musilek, University of Alberta, Canada
Suhail S. Owais, AL-Balaqa University, Jordan
Eyas El-Quwashme, Jordan University of Science and Technology, Jordan
Hideyasu Sasaki, University of Hong Kong, Hong Kong
Juan D. Velasquez, University of Chile, Santiago, Chile
Michal Wozniak, Wroclaw University of Technology, Poland
Milos Besta, Google, New York
Nashwa Mamdouh El-Bendary, Arab Academy for Science, Technology, and Maritime Transport, Egypt
Dr. Muhanned Al Farras, College of Computer Engineering & Sciences, Gulf University, Bahrain
Aboul Ella Hassanien, Cairo University, Egypt