[hpc-announce] Final CFP: Petascale Data Analytics: Challenges, and Opportunities (PDAC-12) with SC-12

[Vatsavai, Raju]

(Apologies for multiple/cross-postings)

Call For Papers
3rd International Workshop on Petascale Data Analytics: Challenges and Opportunities (PDAC-12)
(aka Big Data Analytics)

In Cooperation with ACM/IEEE SC12, 12 November 2012, Salt Lake City, Utah, USA.
http://www.ornl.gov/sci/knowledgediscovery/CloudComputing/PDAC-SC12/


Important Deadlines
Paper Submission
September 30, 2012
Acceptance Notice
October 15, 2012
Camera-Read Copy
December 1, 2012

The 3rd International Workshop on Petascale Data Analytics: Challenges, and Opportunities (PDAC-12), to be held in cooperation with 24th IEEE/ACM International Conference for High Performance Computing, Networking, Storage, and Analysis (SC12), provides an international platform to share and discuss recent research results in adopting high-end computing including clouds and distributed computing resources for petascale - exascale data frameworks, analytics, and visualization.

Synopsis: In the last ten years, computing capability has increased many-fold, and correspondingly data volumes have grown by an even larger amount. Many traditional application domains have now become data intensive. It is estimated that organizations with high-performance computing infrastructures and data centers are doubling the amount of data that they are archiving every year. Recent advances in computing architectures require that middleware and application software be reengineered to fully exploit heterogeneous resources, memory hierarchies, and I/O pipelines. Cloud computing has become a practical and cost effective solution for providers and consumers, ranging from business analytics to scientific computing. The utility of cloud computing has been shown to provide significant benefits in data mining, machine learning and knowledge discovery. Cloud computing also has great potential to revolutionize extreme scale data analytics; but there are many obstacles which must be overcome to gain wide spread adoption. The integration of HPC and cloud infrastructure, for example, must be addressed in a manner that is both usable and scalable. This workshop intends to bring together members of academia, government and industry to discuss new and emerging trends in computing architectures, programming models, I/O services, and data analytics. This workshop will also identify the greatest challenges in embracing high-end computing infrastructure for scaling I/O and algorithms to extreme scale datasets. We invite researchers, developers, and users to participate in this workshop to share, contribute, and discuss the emerging challenges in developing knowledge discovery solutions and frameworks targeting clouds and high-end computing platforms.
Topics: The major topics of interest to the workshop include but are not limited to:

* Programing models and tools needed for data mining (DM), machine learning (ML), and knowledge discovery (KD)
* Fault tolerant data mining in clouds
* Storing and mining the streaming data in clouds
* Programming models for the integration of HPC and cloud technologies
* I/O pipelines
* Techniques for visualizing massive datasets
* Visualization in virtualized environments
* Storage technologies for clouds
* Data movement and caching
* Distributed file systems
* Scalability and complexity issues
* Security and privacy issues
* Algorithms that best suit cloud and distributed computing platforms
* Performance studies comparing various distributed file systems for data intensive applications
* Performance comparisons between clouds and HPC systems
* Workflow technologies for cloud computing
* Customizations and extensions of existing software infrastructures such as Hadoop and Dryad for extreme scale data analytics
* Applications and case studies
* Future research challenges for petascale data analytics and beyond

Paper Submission: This is an open call-for-papers. We invite regular research paper submissions (maximum 10 pages), work-in-progress (5 pages), demo papers (3 pages), and position papers (3 pages). For detailed submission instructions and paper templates, consult PDAC-12 (http://www.ornl.gov/sci/knowledgediscovery/CloudComputing/PDAC-SC12/) website. All accepted papers will be included in the workshop proceedings to be published by IEEE digital library.

Organizing Committee:
Program Chairs
Ranga Raju Vatsavai, Oak Ridge National Laboratory, USA
Scott A Klasky, Oak Ridge National Laboratory, USA
Manish Parashar, Rutgers University, USA

Publicity Chairs
Varun Chandola, Oak Ridge National Laboratory, USA

Program Committee (under construction)
Mohammad H. Abbasi, Oak Ridge National Laboratories, USA
Gagan Agrawal, Ohio State University, USA
Kanishka Bhaduri, NASA, USA
Joydeep Ghosh, UT-Austin, USA
Amol Ghoting, IBM T. J. Watson Research
Daniel S. Katz, University of Chicago, USA
Kun Liu, Yahoo! Labs, USA
Yan Liu, IBM TJ Watson, USA
Qing Liu, Oak Ridge National Laboratory, USA
Gerald F. Lofstead, Sandia National Laboratories, USA
Kenneth Moreland, Sandia National Laboratories, USA
Norbert Podhorszki, Oak Ridge National Laboratories, USA
Sanjay Ranka, University of Florida, USA
Joel H. Saltz, Emory University, US
Karsten Schwan, Georgia Institute of Technology, USA
Kesheng (John) Wu, Lawrence Berkeley National Laboratory,  USA