[hpc-announce] CFP: Special Issue on Scalable Computing Systems for Big Data Applications (JPDC, IF: 1.011)

[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/

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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:
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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:
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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:
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Title: Special Issue on Scalable Computing Systems for Big Data Applications

Guest editors:  Xian-He Sun, Marc Eduard Frincu, Charalampos Chelmis

Submission deadline: June 15, 2015

Acceptance notification: March 2016

Publication: June 2016

Open call: Yes