Fourth Workshop on Big Data Benchmarks, Performance Optimization, and Emerging Hardware (BPOE4)
Call for Papers (co-located with ASPLOS 2014 ? Salt Lake City, Utah, USA)
**** Important Dates ****
Abstract submission deadline, December 31, 2013
Submission Deadline: January 7, 2014 (11:59pm PST)
Author Notification: January 25, 2014
Final Copy Due: February 17, 2014
Workshop: Saturday, March 1, 2014
Workshop home page: http://prof.ict.ac.cn/bpoe_4_
Submission Web page: https://www.easychair.org/
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 power consumption. It is expected that systems with unprecedented
scales can resolve the problems caused by varieties of big data with daunting volumes. Nevertheless, it is very difficult for big data owners to make choice
on which system is most suited for their specific requirements. They also face challenges on how to optimize the systems and their solutions. Meanwhile, system
researchers are working on new hardware architecture, operating systems, programming systems, and data management systems to improve performance in dealing with
big data.
This workshop, the fourth in its series, 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 architecture, systems, programming, and data management research communities to this new and highly promising field.
Topics
The workshop seeks papers that address hot topic issues in benchmarking, designing and optimizing big data systems. Early stage work, new ideas, unconventional
approaches are encouraged. Specific topics of interest include but are not limited to:
> Big data workload characterization and benchmarking
> Innovative computer and memory architecture for big data
> Emerging hardware technologies in big data systems
> Innovative operating systems and programming systems for big data
> Interactions among architecture, systems and data management
> Performance analysis and optimization of big data systems
> Innovative prototypes of big data infrastructures
> Practice report of evaluating and optimizing large-scale big data systems
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.
Steering committee:
Christos Kozyrakis, Stanford
Xiaofang Zhou, University of Queensland
Dhabaleswar K Panda, Ohio State University
Aoying Zhou, East China Normal University
Raghunath Nambiar, Cisco
Lizy K John, University of Texas at Austin
Xiaoyong Du, Renmin University of China
Ippokratis Pandis, IBM Almaden Research Center
Xueqi Cheng, ICT, Chinese Academy of Sciences
Bill Jia, Facebook
Lidong Zhou, Microsoft Research Asia
H. Peter Hofstee, IBM Austin Research Laboratory
Haibo Chen, Shanghai Jiaotong University
Alexandros Labrinidis, University of Pittsburgh
Cheng-Zhong Xu, Wayne State University
Jianfeng Zhan, ICT, Chinese Academy of Sciences
Program Chair:
Jianfeng Zhan, ICT, Chinese Academy of Sciences
Chuliang Weng, Shannon (IT) Lab, Huawei
Web Chair:
Lei Wang, ICT, Chinese Academy of Sciences
Publicity Chairs:
Yuqing Zhu (Data management), ICT, CAS
Gang Lu (Operating systems), ICT, CAS
Zhen Jia (Architecture), ICT, CAS
Program Committee
Onur Mutlu, Carnegie Mellon University
Xu Liu, Rice University
Yunquan Zhang, ICT, Chinese Academy of Sciences
Meikel Poess, Oracle Corporation
Dejun Jiang, ICT, Chinese Academy of Sciences
Yueguo Chen, Renmin University
Rene Mueller, IBM
Xiaoyi Lu, Ohio State University
Yongqiang He, Dropbox
Edwin Sha, University of Texas at Dallas
Kun Wang, IBM Research China
Rong Chen, Shanghai Jiaotong University
Jens Teubner, Tu Dortmund University
Mauricio Breternitz, AMD Research
Seetharami Seelam, IBM
Farhan Tauheed, EPFL
Gansha Wu, Intel
Bingsheng He, Nanyang Technological University
Zhibin Yu, SIAT, Chinese Academy of Sciences
Lei Wang, ICT, Chinese Academy of Sciences
Yuanchun Zhou, CNIC, Chinese Academy of Sciences
Tilmann Rabl, University of Toronto
Weijia Xu, TACC, University of Texas at Austin
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Call for Papers (co-located with ASPLOS 2014 ? Salt Lake City, Utah, USA)
**** Important Dates ****
Abstract submission deadline, December 31, 2013
Submission Deadline: January 7, 2014 (11:59pm PST)
Author Notification: January 25, 2014
Final Copy Due: February 17, 2014
Workshop: Saturday, March 1, 2014
Workshop home page: http://prof.ict.ac.cn/bpoe_4_
Submission Web page: https://www.easychair.org/
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 power consumption. It is expected that systems with unprecedented
scales can resolve the problems caused by varieties of big data with daunting volumes. Nevertheless, it is very difficult for big data owners to make choice
on which system is most suited for their specific requirements. They also face challenges on how to optimize the systems and their solutions. Meanwhile, system
researchers are working on new hardware architecture, operating systems, programming systems, and data management systems to improve performance in dealing with
big data.
This workshop, the fourth in its series, 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 architecture, systems, programming, and data management research communities to this new and highly promising field.
Topics
The workshop seeks papers that address hot topic issues in benchmarking, designing and optimizing big data systems. Early stage work, new ideas, unconventional
approaches are encouraged. Specific topics of interest include but are not limited to:
> Big data workload characterization and benchmarking
> Innovative computer and memory architecture for big data
> Emerging hardware technologies in big data systems
> Innovative operating systems and programming systems for big data
> Interactions among architecture, systems and data management
> Performance analysis and optimization of big data systems
> Innovative prototypes of big data infrastructures
> Practice report of evaluating and optimizing large-scale big data systems
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.
Steering committee:
Christos Kozyrakis, Stanford
Xiaofang Zhou, University of Queensland
Dhabaleswar K Panda, Ohio State University
Aoying Zhou, East China Normal University
Raghunath Nambiar, Cisco
Lizy K John, University of Texas at Austin
Xiaoyong Du, Renmin University of China
Ippokratis Pandis, IBM Almaden Research Center
Xueqi Cheng, ICT, Chinese Academy of Sciences
Bill Jia, Facebook
Lidong Zhou, Microsoft Research Asia
H. Peter Hofstee, IBM Austin Research Laboratory
Haibo Chen, Shanghai Jiaotong University
Alexandros Labrinidis, University of Pittsburgh
Cheng-Zhong Xu, Wayne State University
Jianfeng Zhan, ICT, Chinese Academy of Sciences
Program Chair:
Jianfeng Zhan, ICT, Chinese Academy of Sciences
Chuliang Weng, Shannon (IT) Lab, Huawei
Web Chair:
Lei Wang, ICT, Chinese Academy of Sciences
Publicity Chairs:
Yuqing Zhu (Data management), ICT, CAS
Gang Lu (Operating systems), ICT, CAS
Zhen Jia (Architecture), ICT, CAS
Program Committee
Onur Mutlu, Carnegie Mellon University
Xu Liu, Rice University
Yunquan Zhang, ICT, Chinese Academy of Sciences
Meikel Poess, Oracle Corporation
Dejun Jiang, ICT, Chinese Academy of Sciences
Yueguo Chen, Renmin University
Rene Mueller, IBM
Xiaoyi Lu, Ohio State University
Yongqiang He, Dropbox
Edwin Sha, University of Texas at Dallas
Kun Wang, IBM Research China
Rong Chen, Shanghai Jiaotong University
Jens Teubner, Tu Dortmund University
Mauricio Breternitz, AMD Research
Seetharami Seelam, IBM
Farhan Tauheed, EPFL
Gansha Wu, Intel
Bingsheng He, Nanyang Technological University
Zhibin Yu, SIAT, Chinese Academy of Sciences
Lei Wang, ICT, Chinese Academy of Sciences
Yuanchun Zhou, CNIC, Chinese Academy of Sciences
Tilmann Rabl, University of Toronto
Weijia Xu, TACC, University of Texas at Austin
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