BEYONDMR'16
3rd Workshop on Algorithms and Systems for MapReduce and Beyond, July 1, 2016.
https://sites.google.com/site/beyondmr2016/

Held in conjunction with SIGMOD 2016
San Francisco, USA, June 26th - July 1st, 2016
http://sigmod2016.org/

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WORKSHOP FOCUS
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The third BeyondMR workshop aims to explore algorithms, computational models, architectures, languages and interfaces for systems that need large-scale parallelization and systems designed to support efficient parallelization and fault tolerance. These include specialized programming and data-management systems based on MapReduce and extensions, graph processing systems, data-intensive workflow and dataflow systems.

We invite submissions on topics such as

Frameworks for Large-Scale Analytical Processing:
- Models, architectures and languages for data processing pipelines, data-intensive workflows, DAGs of operations/MapReduce jobs, dataflows, and data-mashups.
- Extensions of MapReduce with more fundamental functions other than Map and Reduce and more complex dataflow connections between function inputs and outputs.
- Expressing and parallelising iterations, incremental iterations, and programs consisting of large DAGs of operations.
- Approaches to achieving fault tolerance and to recovering from failures.

Algorithms for Large-Scale Data Processing:
- Methods and techniques for designing efficient algorithms for MapReduce and similar systems.
- Experiments and experience with new algorithms in these settings.

Cost Models and Optimization Techniques:
- Formal definitions of models that evaluate the efficiency of algorithms in large-scale parallel processing systems taking into account the requirements of such systems in different applications.
- Testing and benchmarking of MapReduce extensions and data-intensive workflows.

Resource Management for Many-Task Computing:
- Scheduling of tasks and load-balancing techniques.
- Methods to tackle data skewness.
- Study of cases where automatic data distribution in MapReduce and similar systems does not provide sufficient data balancing.
- Design of algorithms that avoid skewness.
- Extensions of MapReduce that automatically tackle data skewness.

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IMPORTANT DATES
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Papers submission deadline: Sun March 5, 2016
Authors notification: Sun April 11, 2016
Deadline for camera-ready copy: Sun May 1, 2016
Workshop: Fri July 1, 2016

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SUBMISSION GUIDELINES
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We invite full research or experience papers (up to 10 pages), or short papers (up to 4 pages) describing research in progress, formatted using the ACM double-column style (http://conferences.sigcomm.org/imc/2009/sig-alternate-10pt.cls)

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PUBLICATION
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The workshop proceedings will be published in ACM DL and the organizers will prepare a SIGMOD Record report.

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ORGANIZERS
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Foto Afrati (National Technical University of Athens, Greece)
Jan Hidders (TU Delft, The Netherlands)
Christopher Re (Stanford, USA)
Jacek Sroka (University of Warsaw, Poland)
Jeffrey Ullman (Stanford University)

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Program Committee (in progress)
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– Chris Re, Stanford University (PC chair)
– Foto Afrati, National Technical University of Athens
– Jeffrey Ullman, Stanford University
– Jacek Sroka, University of Warsaw
– Jan Hidders, Delft University of Technology
– Zhengkui Wang, Singapore Institute of Technology
– Khalid Belhajjame, PSL, Universite Paris-Dauphine, LAMSADE
– Sourav Bhowmick, Nanyang Technological University
– Graham Cormode, University of Warwick
– Asterios Katsifodimos, Technical University of Berlin
– Paris Koutris, University of Washington
– Dionysios Logothetis, Facebook
– Frank McSherry, ETH Zurich
– Krzysztof Onak, IBM Research
– Mark Santcroos, Rutgers University
– Gautam Shroff, Tata Consultancy Services RD
– Dan Suciu, University of Washington
– Jianwu Wang, San Diego Supercomputer Center, University of California, San Diego
– Tim Kraska, Brown University
– Krzysztof Rzadca, University of Warsaw
– Semih Salihoglu, Stanford University
- Ulf Leser, Humboldt-Universität zu Berlin
- Fabio Porto, National Laboratory of Scientific Computation, Brasil
- Eiko Yoneki, University of Cambridge
- Umut Acar, Carnegie Mellon University
- Daniel De Oliveira, Fluminense Federal University
- Tamer Özsu, University of Waterloo
- Anthony Tung, National University of Singapore
- Sergei Vassilvitskii, Google
- Yogesh Simmhan, Indian Institute of Science, Bangalore