IEEE International Workshop on High-Performance Big Data Computing(HPBDC 2017)

May 29, 2017

Orlando,Florida

Call For Papers

Managing and processing large volumes of data, or “Big Data”, and gaining meaningful insights is a significant challenge facing the distributed computing community. This has significant impact on a wide range of domains including health care, bio-medical research, Internet search, finance and business informatics, and scientific computing. As data-gathering technologies and data-sources witness an explosion in the amount of input data, it is expected that in the future massive quantities of data in the order of hundreds or thousands of petabytes will need to be processed. Thus, it is critical that data-intensive computing middleware (such as Hadoop, HBase and Spark) to process such data are diligently designed, with high performance and scalability, in order to meet the growing demands of such Big Data applications.

The explosive growth of Big Data has caused many industrial firms to adopt High Performance Computing (HPC) technologies to meet the requirements of huge amount of data to be processed and stored. Modern HPC systems and the associated middleware (such as MPI and Parallel File systems) have been exploiting the advances in HPC technologies (multi/many-core architectures, accelerators, RDMA-enabled networking, NVRAMs and SSDs) during the last decade. However, Big Data middleware (such as Hadoop, HBase and Spark) have not embraced such technologies. These disparities are taking HPC and Big Data processing into ‘divergent trajectories’.

Topics

• High-performance Big Data analytics frameworks, programming models, and tools
• Performance optimizations for Big Data systems and applications with HPC technologies (multi/many-core architectures, accelerators, RDMA-enabled networking, NVRAMs and SSDs)
• High-performance in-memory computing technologies and abstractions
• Performance modeling and evaluation for emerging Big Data Computing technologies
• Big Data on HPC, Cloud, and Grid computing infrastructures
• Fault tolerance, reliability and availability for high-performance Big Data Computing
• Green Big Data Computing
• Scientific Computing with Big Data
• Streaming data processing architectures and technologies
• Papers should present original research. As Big Data spans many disciplines, papers should provide sufficient background material to make them accessible to the broader community.

Important Dates

• Submission Deadline  : January 17, 2017
• Notification Due            : February 17, 2017
• Final Version Due          : March 01, 2017

User Name : Claude
Posted 09-11-2016 on 08:36:48 AEDT

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