Special issue of
PARALLEL
COMPUTING
PARALLEL DATA INTENSIVE ALGORITHMS AND APPLICATIONS
http://www.cs.clemson.edu/~srimani/parco/cfp.html
Data-intensive applications are those that explore, query, analyze,
visualize,
in general, manipulate very large scale data sets. Data-intensive applications
can benefit of the use of parallel and distributed computing systems
both to
improve performance and quality of data analysis. When data-intensive
algorithms, applications and tools are implemented on high-performance
computers, they can analyze massive databases in a reasonable time.
Faster processing also means that users can experiment with more models
to understand complex data. High performance makes it practical for
users to analyze greater quantities of data.
Both the size of the data available and the complexity of the algorithms
required for concept extraction suggest that high-performance parallel
and distributed computing has an important role to play. In particular,
when very large data sets must be analyzed and manipulated, parallelism
is the only possibility if accuracy must be assured. On the other hand,
distributed techniques are necessary to handle
geographically distributed data repositories. This special issue offers
the
opportunity to present and discuss problems and report both theoretical
and
practical solutions in the area, to identify new ideas, and to shape
future
directions for research.
Areas of interest include, but are not limited to:
- Parallel data-intensive algorithms;
- Data mining of very large data sets and Web mining;
- Large data warehousing and OLAP;
- Data-intensive grid systems and applications;
- Programming models for parallelization of data-intensive applications;
- Parallel data fusion;
- Data-intensive visualization;
- Parallel data reduction techniques;
- Data representation and storage for fast access.
Papers should report well-defined innovative ideas and practical results
in
real-life applications; they should include evaluations through analysis,
simulation
and experiments possibly on different parallel platforms. Papers must
be
written in the Parallel Computing style.
Please submit your manuscript electronically (pdf or ps files) to either
of
the guest editors by February 28, 2001:
Domenico Talia
Pradip K. Srimani
ISI-CNR
Dept. of Computer Science
Via P. Bucci, cubo 41-C
Clemson University
8036 Rende (CS), Italy
Clemson, SC 29634, USA
Voice: +39 (984) 839047
Voice: (864) 656-7552
Fax: +39 (984) 839054
Fax: (864) 656-0145
Email: talia@si.deis.unical.it
Email: srimani@cs.clemson.edu
Instructions for submitting papers: Papers should include a 100- to
200-word abstract and five to ten index words. Authors must follow
the Parallel Computing guidelines regarding the manuscript and its
format.
For more details, please refer to Information for Authors at
http://www.elsevier.nl/inca/publications/store/5/0/5/6/1/7/
.
Electronic submissions are strongly encouraged.
========================================================================= This message is forwarded to members of the COSC/Management/Maths research group on stochastic simulation at the University of Canterbury, Christchurch, New zealand, and anybody else interested in research in this area ------------------------------------------------------------------------- Associate Professor Krzysztof Pawlikowski Department of Computer Science, University of Canterbury Christchurch, New Zealand ph. +(64) 3 3642 987 ext.7772 email: krys@cosc.canterbury.ac.nz fax. +(64) 3 3642 569 URL: http://www.cosc.canterbury.ac.nz/~krys -------------------------------------------------------------------------