Call for papers
The term "Big Data" refers to the continuing massive expansion in the data volume and diversity as well as the speed and complexity of data processing. The use of big data underpins critical activities in all sectors of our society. Achieving the full transformative potential of big data in this increasingly digital world requires both new data analysis algorithms and a new class of systems to handle the dramatic data growth, the demand to integrate structured and unstructured data analytics, and the increasing computing needs of massive-scale analytics.
We are pleased to request papers for presentation at the upcoming seventh Workshop on Architectures and Systems for Big Data (ASBD 2017) held in conjunction with ISCA-44. The workshop will provide a forum to exchange research ideas related to all critical aspects of emerging analytics systems for big data, including architectural support, benchmarks and metrics, data management software, operating systems, and emerging challenges and opportunities. We hope to attract a group of interdisciplinary researchers from academia, industry and government research labs. To encourage discussion between participants, the workshop will include significant time for interactions between the presenters and the audience. We also plan to have a keynote speaker and/or panel session.
Topics of interest include but are not limited to:
- Processor, memory and system architectures for data analytics
- Benchmarks, metrics and workload characterization for big data
- Accelerators for analytics and data-intensive computing
- Heterogeneous computing and heterogeneous system architecture
- Implications of data analytics to mobile and embedded systems
- Energy efficiency and energy-efficient designs for analytics
- Availability, fault tolerance and data recovery in big data environments
- Scalable system and network designs for high concurrency/bandwidth streaming
- Data management and analytics for vast amounts of unstructured data
- Evaluation tools, methodologies and workload synthesis
- OS, distributed systems and system management support for large-scale analytics
- Debugging and performance analysis tools for analytics and big data
- Programming systems and language support for deep analytics
- MapReduce and other processing paradigms for analytics
We encourage researchers from all institutions to submit their work for review. Preliminary results of interesting ideas and work-in-progress are welcome. Submissions that are likely to generate vigorous discussion will be favored!
Yungang Bao, ICT/CAS
Xuehai Qian, University of Southern California