ebdma 2017 - BigStorage
Important days
Submission Deadline:
January 9, 2017
Notification of Acceptance:
February 10, 2017
Camera Ready:
EBDMA 2017
1st Workshop on the Integration of Extreme Scale Computing and
Big Data Management and Analytics
in conjunction with IEEE/ACM CCGrid 2017
February 24, 2017
Workshop Co-Chairs
Shadi Ibrahim
Inria, France
Manish Parashar
Rutgers University, USA
Anna Queralt,
Barcelona Supercomputing
Center, Spain
Domenico Talia
University of Calabria, Italy
The deployment of extreme scale computing platforms in research and industry coupled with the
proliferation of large and distributed digital data sources have the potential for unprecedented
insights and understanding in all areas of science, engineering, business, and society in general.
However, challenges related to the Big Data generated and processed by these systems remain a
significant barrier in achieving this potential.
Addressing these challenges requires a seamless integration of the extreme scale/high
performance computing, cloud computing, storage technologies, data management, energy
efficiency, and big data analytics research approaches, framework/technologies, and
communities. The convergence and integration of HPC, cloud computing and data analysis is
crucial to the future. To achieve this goal, both communities need to collectively explore and
embrace emerging disruptions in architecture and hardware technologies as well as new datadriven application areas such as those enabled by the Internet of Things. Finally, educational and
workforce development structures have to evolved to develop the required integrated skillsets.
The goal of this workshop is to bring leading researchers from these communities together to jointly
explore such integration, and to develop a research agenda towards brings the diverging research
groups and technologies stack toward a more convergent path. The workshop provides a forum
for scientists and engineers in academia and industry to present their latest research findings on
major and emerging topics in this field.
A partial list of topics of interest is as follows:
• Models and techniques for scalable data analysis
• Extreme data discovery solutions
• HPC and extreme scale platforms for Big Data analytics
• Exascale data analysis programming abstractions and services
• Parallel and distributed Big Data analysis algorithms
• Data analysis as a service infrastructure
• Code coordination and data integration on HPC platforms
• Interoperability of Big Data analytics frameworks
• Adaption of data mining algorithms on extreme scale systems
• Data-centric scalable programming tools and algorithms
• High-performance and Big Data analytics frameworks, programming models, and tools
• Leveraging processing, storage and communications technologies (multi/many-core
architectures, accelerators, RDMA-enabled networking, NVRAMs and SSDs) in integrated HPC
Big Data applications
• Performance modeling and evaluation of integrated HPC Big Data applications
• Fault tolerance, reliability and availability for high-performance Big Data computing
• New storage devices for Big Data management in HPC and Clouds
• Security issues in Big Data analysis and management in HPC and Clouds
• Energy-efficiency issues in Big Data analysis and management in HPC and Clouds
• Stream data processing in HPC and Clouds
• Case studies of data-intensive applications in HPC and Clouds
• Scheduling and provisioning data analytics on hybrid Cloud and HPC infrastructure
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