[hpc-announce] CFP: BigGraphs 2016 workshop at IEEE BigData 2016

[Kamesh Madduri]

*The Third International Workshop on High Performance **
**Big Graph Data Management, Analysis, and Mining* (*BigGraphs 2016*)

To be held in conjunction with *IEEE BigData 2016*
**Dec 5-8, 2016, Washington, D.C., USA./

//Website: /
http://www.biggraphs.org
/
//Important Dates:/
*Oct 20, 2016*: Submission deadline
   Nov  6, 2016: Notification of paper acceptance to authors
   Nov 15, 2016: Camera-ready submissions due

///Call for papers:/
Modern Big Data increasingly appears in the form of complex graphs and 
networks.
Examples include the physical Internet, the world wide web, online 
social networks,
phone networks, and biological networks. In addition to their massive 
sizes, these
graphs are dynamic, noisy, and sometimes transient. They also conform to 
all five Vs
(Volume, Velocity, Variety, Value and Veracity) that define Big Data. 
However, many
graph-related problems are computationally difficult, and thus big graph 
data brings
unique challenges, as well as numerous opportunities for researchers, to 
solve various
problems that are significant to our communities. This workshop aims to 
bring together
researchers from different paradigms solving big graph problems under a 
unified
platform for sharing their work and exchanging ideas. We are soliciting 
novel and
original research contributions related to big graph data management, 
analysis, and
mining (algorithms, software systems, applications, best practices, 
performance).
Significant work-in-progress papers are also encouraged. Papers can be 
from any of
the following areas, including but not limited to:
* Parallel algorithms for big graph analysis on HPC systems
* Heterogeneous CPU-GPU solutions to solve big graph problems
* Extreme-scale computing for large graph, tensor, and network problems
* Sampling and summarization of large graphs
* Graph algorithms for large-scale scientific computing problems
* Graph clustering, partitioning, and classification methods
* Scalable graph topology measurement: diameter approximation,
   eigenvalues, triangle and graphlet counting
* Parallel algorithms for computing graph kernels
* Inference on large graph data
* Graph evolution and dynamic graph models
* Graph streams
* Graph databases, novel querying and indexing strategies for RDF data
* Novel applications of big graph problems in bioinformatics, health care,
   security, and social networks
* New software systems and runtime systems for big graph data mining

Submissions must be at most 8 pages long, including all figures, tables, 
and references.
They must be formatted according to the style files used by the IEEE 
BigData 2016
conference proceedings. Papers must be submitted online through the 
workshop submissions
page 
(http://wi-lab.com/cyberchair/2016/bigdata16/scripts/submit.php?subarea=S19) 

by 11.59 pm PDT (Pacific Daylight Time) on October 20, 2016./

Workshop Organizers:/
   Nesreen Ahmed
   Intel Labs
nesreen.k.ahmed at intel.com

   Mohammad Al Hasan
   Indiana University-Purdue University Indianapolis
alhasan at cs.iupui.edu

   Kamesh Madduri
   The Pennsylvania State University
madduri at cse.psu.edu

/Program Committee:/
Nesreen Ahmed (Intel Labs)
   Mohammad Al Hasan (Indiana University - Purdue University)
   Ariful Azad (Lawrence Berkeley National Laboratory)
   Sanjukta Bhowmick (University of Nebraska at Omaha)
   Mehmet Deveci (Sandia National Laboratories)
   Nick Duffield (Texas A&M University)
   Assefaw Gebremedhin (Washington State University)
   Oded Green (Georgia Institute of Technology)
   Irena Holubova (Charles University)
   Kamesh Madduri (The Pennsylvania State University)
   Ali Pinar (Sandia National Laboratories)
   Ryan Rossi (Palo Alto Research Center)
   George Slota (Rensselaer Polytechnic Institute)
   Narayanan Sundaram (Intel Labs)
   Ted Willke (Intel Labs)
   Yinglong Xia (Huawei Research America)

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