Extended Deadline (24 August, 2013)
CALL FOR PAPERS
The First Workshop on
Benchmarks, Performance Optimization, and Emerging hardware of Big Data Systems and Applications (BPOE 2013)
http://prof.ict.ac.cn/
In conjunction with
2013 IEEE International Conference on Big Data (IEEE Big Data 2013)
October 6-9, 2013, Silicon Valley, CA, USA
******************************
OVERVIEW
This is the first workshop addressing the challenge of benchmarks, performance optimization, and emerging
hardware of Big Data systems and applications, in conjunction with IEEE Big Data conference 2013. Big Data
has emerged as a strategic property of nations and organizations. There are driving needs to generate
values from Big Data. However, the sheer volume of big data requires significant storage capacity,
transmission bandwidth, computations, and electrical energy. It is expected that systems with unprecedented
scales can resolve the problems caused by varieties of big data with daunting volumes. Nevertheless, owners
of Big Data can hardly make choice on which system is most suited for their specific requirements. They also
face the challenge on how to optimize the system and their solutions to earn most profits from existing data
collection. On the other hand, system researchers and developers are working on new hardware architecture,
system models, data management and mining techniques to improve the performance in dealing with Big Data.
Characteristics of Big Data Systems bring unique challenges for system benchmarking, and optimizing, which lead
to great opportunities for designing innovative Big Data infrastructure. The BPOE workshop aims at bringing
researchers and practitioners in related areas together to discuss the research issues at the intersection of
these areas, and also to draw much attention from the general architecture, systems, data management and mining
research communities to this new and highly promising field.
HIGHLIGHTS
This workshop shows the following highlights:
-Bring together big data researchers from communities of architecture, systems, and data management. We will
discuss the mutual influences of architectures, systems, and data management.
-Bridge the gap of big data researches and practices between industry and academia. Researchers from universities,
institutes, and companies will attend this workshop.
-The Technical Program Committee is comprised of active big data practioners from both industry and academia.
-All accepted papers will be published with the Proceeding of IEEE Big Data conference, and indexed by EI.
TOPICS
This workshop welcomes research and industry papers that address fundamental research issues in benchmarking,
characterizing, designing and optimizing Big Data systems based on novel hardware and software applications.
Topics of interest include, but are not limited to
-Benchmarking Big Data, cloud and data center computer systems
-Workload characterization of typical Big Data applications
-Performance analysis and optimization of Big Data systems and applications
-New experimental methodologies discussion: how to synthesizing PB-scale Big Data, simulating 100K-node systems,
or even obtaining insights of large-scale systems from small-scale deployments
-Innovative prototypes of Big Data infrastructures
-Practice report of evaluating and optimizing large-scale big data systems
-Emerging software and hardware technologies in Big Data systems
-Application examples and use cases in using cyber-infrastructure for Big Data in sciences and engineering
PAPER SUBMISSION
Please submit a full-length paper (upto 8 page IEEE 2-column format) through the online submission system:
https://wi-lab.com/cyberchair/
Papers should be formatted to IEEE Computer Society Proceedings Manuscript Formatting Guidelines
8.5" x 11" (DOC, PDF)
LaTex Formatting Macros
IMPORTANT DATES
Paper submission due: July 30, 2013, 11:59 p.m. PST
Notification to authors: August 30, 2013
Camera-ready files due: September 10, 2013
ORGANIZERS
Steering committee:
Lizy K John? University of Texas at Austin
Zhiwei Xu, Institute of Computing Tec hnology, Chinese Academy of Sciences
Cheng-zhong Xu, Wayne State University
Xueqi Cheng, Institute of Computing Technology, Chinese Academy of Sciences
Jianfeng Zhan, Institute of Computing Technology, Chinese Academy of Sciences
PC Co-chairs:
Jianfeng Zhan, Institute of Computing Technology, Chinese Academy of Sciences
Weijia Xu, Texas Advanced Computing Center, University of Texas at Austin
Publicity Chairs:
Zhibing Yu, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences
Yuqing Zhu, Institute of Computing Technology, Chinese Academy of Sciences
Gang Lu, Institute of Computing Technology, Chinese Academy of Sciences
Zhen Jia, Institute of Computing Technology, Chinese Academy of Sciences
Wanling Gao, Institute of Computing Technology, Chinese Academy of Sciences
Web Chairs:
Yingjie Shi, Institute of Computing Technology, Chinese Academy of Sciences
Xiaolong Jin, Institute of Computing Technology, Chinese Academy of Sciences
Program committee:
Lizy K John, University of Texas at Austin
Guoliang Chen, University of Science and Technology of China
Pradeep Dubey, Intel
Xiangyong Ouyang, Google
Matthew Lease, University of Texas at Austin
Scott Chen, Facebook
Rui Mao, Shenzhen University, China
Yongqiang He, Facebook
Richard Marciano, University of North Carolina
Xinchun Liu, Sugon
Li Zha, Institute of Computing Technology, CAS
Kenton McHenry, National Center for Supercomputing Applications
Richard Moore, San Diego Supercomputing Center
Lei Wang, Institute of Computing Technology, CAS
Nirav Merchant, University of Arizona
Zhibing Yu, Shenzhen Institutes of Advanced Technology, CAS
Dhabaleswar K Panda, Ohio State University
Keshav Pingali, University of Texas at Austin
J. Ray Scott, Pittsburg Supercomputing Center
Dan Stanzione, Texas Advanced Computing Center
Shujie Zhang, Huawei
Zhigang Huo, Institute of Computing Technology, CAS
Chunming Hu, Beihang University
Wei Huang, Tencent
Yunquan Zhang, Institute of Software, CAS
Songlin Hu, Institute of Computing Technology, CAS
Ling Qian, China Mobile Research Institute
Haining Wang, College of William and Mary
Yungang Bao, Institute of Computing Technology, CAS
Bo Liu, Facebook
Wenguang Chen, Tsinghua University
Haibo Chen, Shanghai Jiaotong University
Ming Zhao, Florida International University
Shengzhong Feng, Shenzhen Institutes of Advanced Technology, CAS
Jichuan Chang, HP Labs, USA.
Jian Li, IBM Research in Austin
Xiaoyao Liang, Shanghai Jiaotong University
Darren J. Kerbyson Pacific Northwest National Laboratory
Ananth Sankaranarayanan, Intel
Weiping Wang, Institute of Information Engineering, CAS
WenSong Zhang, Taobao, China
Yanpei Chen, Cloudera
Andrew Purtell, Intel and Apache Software Foundation
CALL FOR PAPERS
The First Workshop on
Benchmarks, Performance Optimization, and Emerging hardware of Big Data Systems and Applications (BPOE 2013)
http://prof.ict.ac.cn/
In conjunction with
2013 IEEE International Conference on Big Data (IEEE Big Data 2013)
October 6-9, 2013, Silicon Valley, CA, USA
******************************
OVERVIEW
This is the first workshop addressing the challenge of benchmarks, performance optimization, and emerging
hardware of Big Data systems and applications, in conjunction with IEEE Big Data conference 2013. Big Data
has emerged as a strategic property of nations and organizations. There are driving needs to generate
values from Big Data. However, the sheer volume of big data requires significant storage capacity,
transmission bandwidth, computations, and electrical energy. It is expected that systems with unprecedented
scales can resolve the problems caused by varieties of big data with daunting volumes. Nevertheless, owners
of Big Data can hardly make choice on which system is most suited for their specific requirements. They also
face the challenge on how to optimize the system and their solutions to earn most profits from existing data
collection. On the other hand, system researchers and developers are working on new hardware architecture,
system models, data management and mining techniques to improve the performance in dealing with Big Data.
Characteristics of Big Data Systems bring unique challenges for system benchmarking, and optimizing, which lead
to great opportunities for designing innovative Big Data infrastructure. The BPOE workshop aims at bringing
researchers and practitioners in related areas together to discuss the research issues at the intersection of
these areas, and also to draw much attention from the general architecture, systems, data management and mining
research communities to this new and highly promising field.
HIGHLIGHTS
This workshop shows the following highlights:
-Bring together big data researchers from communities of architecture, systems, and data management. We will
discuss the mutual influences of architectures, systems, and data management.
-Bridge the gap of big data researches and practices between industry and academia. Researchers from universities,
institutes, and companies will attend this workshop.
-The Technical Program Committee is comprised of active big data practioners from both industry and academia.
-All accepted papers will be published with the Proceeding of IEEE Big Data conference, and indexed by EI.
TOPICS
This workshop welcomes research and industry papers that address fundamental research issues in benchmarking,
characterizing, designing and optimizing Big Data systems based on novel hardware and software applications.
Topics of interest include, but are not limited to
-Benchmarking Big Data, cloud and data center computer systems
-Workload characterization of typical Big Data applications
-Performance analysis and optimization of Big Data systems and applications
-New experimental methodologies discussion: how to synthesizing PB-scale Big Data, simulating 100K-node systems,
or even obtaining insights of large-scale systems from small-scale deployments
-Innovative prototypes of Big Data infrastructures
-Practice report of evaluating and optimizing large-scale big data systems
-Emerging software and hardware technologies in Big Data systems
-Application examples and use cases in using cyber-infrastructure for Big Data in sciences and engineering
PAPER SUBMISSION
Please submit a full-length paper (upto 8 page IEEE 2-column format) through the online submission system:
https://wi-lab.com/cyberchair/
Papers should be formatted to IEEE Computer Society Proceedings Manuscript Formatting Guidelines
8.5" x 11" (DOC, PDF)
LaTex Formatting Macros
IMPORTANT DATES
Paper submission due: July 30, 2013, 11:59 p.m. PST
Notification to authors: August 30, 2013
Camera-ready files due: September 10, 2013
ORGANIZERS
Steering committee:
Lizy K John? University of Texas at Austin
Zhiwei Xu, Institute of Computing Tec hnology, Chinese Academy of Sciences
Cheng-zhong Xu, Wayne State University
Xueqi Cheng, Institute of Computing Technology, Chinese Academy of Sciences
Jianfeng Zhan, Institute of Computing Technology, Chinese Academy of Sciences
PC Co-chairs:
Jianfeng Zhan, Institute of Computing Technology, Chinese Academy of Sciences
Weijia Xu, Texas Advanced Computing Center, University of Texas at Austin
Publicity Chairs:
Zhibing Yu, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences
Yuqing Zhu, Institute of Computing Technology, Chinese Academy of Sciences
Gang Lu, Institute of Computing Technology, Chinese Academy of Sciences
Zhen Jia, Institute of Computing Technology, Chinese Academy of Sciences
Wanling Gao, Institute of Computing Technology, Chinese Academy of Sciences
Web Chairs:
Yingjie Shi, Institute of Computing Technology, Chinese Academy of Sciences
Xiaolong Jin, Institute of Computing Technology, Chinese Academy of Sciences
Program committee:
Lizy K John, University of Texas at Austin
Guoliang Chen, University of Science and Technology of China
Pradeep Dubey, Intel
Xiangyong Ouyang, Google
Matthew Lease, University of Texas at Austin
Scott Chen, Facebook
Rui Mao, Shenzhen University, China
Yongqiang He, Facebook
Richard Marciano, University of North Carolina
Xinchun Liu, Sugon
Li Zha, Institute of Computing Technology, CAS
Kenton McHenry, National Center for Supercomputing Applications
Richard Moore, San Diego Supercomputing Center
Lei Wang, Institute of Computing Technology, CAS
Nirav Merchant, University of Arizona
Zhibing Yu, Shenzhen Institutes of Advanced Technology, CAS
Dhabaleswar K Panda, Ohio State University
Keshav Pingali, University of Texas at Austin
J. Ray Scott, Pittsburg Supercomputing Center
Dan Stanzione, Texas Advanced Computing Center
Shujie Zhang, Huawei
Zhigang Huo, Institute of Computing Technology, CAS
Chunming Hu, Beihang University
Wei Huang, Tencent
Yunquan Zhang, Institute of Software, CAS
Songlin Hu, Institute of Computing Technology, CAS
Ling Qian, China Mobile Research Institute
Haining Wang, College of William and Mary
Yungang Bao, Institute of Computing Technology, CAS
Bo Liu, Facebook
Wenguang Chen, Tsinghua University
Haibo Chen, Shanghai Jiaotong University
Ming Zhao, Florida International University
Shengzhong Feng, Shenzhen Institutes of Advanced Technology, CAS
Jichuan Chang, HP Labs, USA.
Jian Li, IBM Research in Austin
Xiaoyao Liang, Shanghai Jiaotong University
Darren J. Kerbyson Pacific Northwest National Laboratory
Ananth Sankaranarayanan, Intel
Weiping Wang, Institute of Information Engineering, CAS
WenSong Zhang, Taobao, China
Yanpei Chen, Cloudera
Andrew Purtell, Intel and Apache Software Foundation
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