[hpc-announce] Special Issue on Scalable Computing Systems for Big Data Applications (JPDC, IF: 1.011) - extended deadline until July 15 2015

[Marc-Eduard Frincu]

We invite researchers and practitioners focusing on scalable systems and Big
Data applications to submit their results in this special issue on 'Scalable
Computing Systems for Big Data Applications' published in Journal of Parallel
and Distributed Computing (Elsevier).
 
The submission site and details can be found here:
 
http://www.journals.elsevier.com/journal-of-parallel-and-distributed-computing/call-for-papers/special-issue-on-scalable-computing-systems-for-big-data-app/
 
When submitting select "SI: Scalable Systems Big Data" from the list of options in the Elsevier JPDC submission site.

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Guest Editors:
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Prof. Dr. Xian-He Sun
Department of Computer Science, Illinois Institute of Technology, USA
 
Dr. Marc Eduard Frincu
Department of Electrical Engineering, University of Southern California, USA

Dr. Charalampos Chelmis
Department of Electrical Engineering, University of Southern California, USA
 
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Background and Scope:
=====================
 
The continuous growth of our society has led to complex systems, and also to the
need to optimize certain aspects of our day to day activities. Time sensitive
applications such as real time power management for smart grids, traffic
control or network monitoring require on demand large scale information
processing and real time responses. The data these applications gathered on a
regular basis from monitoring sensors exceeds the normal storage and capacity
power of normal machines or even clusters. In addition, the complexities
arising from handling large networked data include but are not limited to data
heterogeneity (i.e. variability), data quality (missing/approximate), data
temporality (i.e. high-velocity), or data volume. Utilizing new hardware
technologies for near real-time Big Data management and processing is of urgent
importance as hardware characteristics in state of art scalable computing
platforms such as clouds, is undergoing rapid changes, imposing new challenges
for the efficient utilization of hardware resources. Recent trends include
massive multi-core processing systems, and specialized, high performance
co-processors such as GPUs and FPGAs for accelerating large-scale computations.
On the storage front, FLASH-based solid state devices (SSDs) and IO
accelerators are becoming ubiquitous. In spite of these trends bringing the
computational capabilities of supercomputers to cheaper commodity machines,
naive usage of these technologies for fast Big Data processing might lead to
unbalanced systems or underutilized resources.

In this special issue, we invite articles on innovative research to address
challenges of fast Big Data processing on emerging compute platforms such as
heterogeneous clouds or hybrid architectures, with emphasis on addressing
real-time requirements imposed by critical decision making applications in
science and engineering.
 
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Topics of Interest:
===================

Topics of interests for the special issue include but are not limited to:

   Novel programming models and platforms for large scale I/O intensive applications
   Scalable software platforms for fast Big Data analytics on heterogeneous clouds and hybrid architectures
   Acceleration of domain specific Big Data applications on heterogeneous hardware
 
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Special Issue details:
======================
 
Title: Special Issue on Scalable Computing Systems for Big Data Applications

Guest editors:  Xian-He Sun, Marc Eduard Frincu, Charalampos Chelmis
 
Submission deadline: July 15, 2015 (extended)

Final notification (after review rounds): March 2016
 
Publication: June 2016
 
Open call: Yes