[hpc-announce] CFP for the BeyondMR workshop (Algorithms and Systems for MapReduce and Beyond) at SIGMOD 2017

Jan Hidders jan.hidders at vub.ac.be
Sun Oct 16 09:39:37 CDT 2016

[Apologies of you are receiving this CFP multiple times]

* Call for papers *

The 4th Workshop on Algorithms and Systems for MapReduce and Beyond, May 19, 2017.
https://sites.google.com/site/beyondmr2017/ <https://sites.google.com/site/beyondmr2017/>

Held in conjunction with SIGMOD 2017
Raleigh, NC, USA, May 14-19, 2017
http://sigmod2017.org/ <http://sigmod2017.org/>


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, networks of operations/MapReduce jobs, dataflows,
 and data-mashups. 
- Analysis of programs for workflow systems, e.g., Spark.
- Expressing and parallelising iterations, incremental iterations, and
 programs consisting of large networks 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

Resource Management for Many-Task Computing:
- Scheduling of tasks and load-balancing techniques.
- Study of cases where automatic data distribution in MapReduce and
 similar systems does not provide sufficient data balancing.
- Algorithms, methods and frameworks to address data skewness.

Papers submission deadline:             Wed Jan 27, 2017
Authors notification:                   Sun March 5, 2017
Deadline for camera-ready copy:         Sun March 19, 2017
Workshop:                               Fri May 19, 2017

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 <http://conferences.sigcomm.org/imc/2009/sig-alternate-10pt.cls>)

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

- Foto Afrati                   National Technical University of Athens, Greece)
- Jan Hidders                   Vrije Universiteit Brussel, Belgium
- Paris Koutris                 University of Wisconsin-Madison, USA
- Jacek Sroka                   University of Warsaw, Poland
- Jeffrey Ullman                Stanford University

Program Committee

- Paris Koutris,                University of Wisconsin-Madison (CHAIR)
- Foto Afrati,                  National Technical University of Athens
- Sourav S. Bhowmick,           Nanyang Technological University
- Yingyi Bu,                    Couchbase
- Ahmed Eldawy,                 University of California, Riverside
- Todd Green,                   LogicBlox
- Jan Hidders,                  Vrije Universiteit Brussel
- Asterios Katsifodimos,        Technical University of Berlin
- Paraschos Koutris,            University of Wisconsin-Madison
- Nectarios Koziris,            National Technical University of Athens
- Ulf Leser,                    Humboldt-Universität zu Berlin
- Dionysios Logothetis,         Facebook
- Frank McSherry
- Frank Neven,                  Hasselt University
- Daniel de Oliveira,           Fluminense Federal University
- Krzysztof Onak,               IBM T.J. Watson Research Center
- Fabio Porto,                  National Laboratory of Scientific Computation
- Chris Re,                     Stanford University
- Krzysztof Rzadca,             University of Warsaw
- Semih Salihoglu,              University of Waterloo
- Mark Santcroos,               Rutgers University
- Francesco Silvestri,          IT University of Copenhagen
- Yogesh Simmhan,               Indian Institute of Science, Bangalore
- Jacek Sroka,                  University of Warsaw
- Dan Suciu,                    University of Washington
- Jeffrey Ullman,               Stanford University
- Theodore Vassilakis,          Microsoft
- Jianwu Wang,                  University of Maryland, Baltimore County
- Zhengkui Wang,                National University of Singapore
- Ke Yi,                        Hong Kong University of Science and Technology
- Eiko Yoneki,                  University of Cambridge
- Matei Zaharia,                Stanford University
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