You are viewing a plain text version of this content. The canonical link for it is here.
Posted to mapreduce-user@hadoop.apache.org by Gilles Fedak <Gi...@inria.fr> on 2011/01/06 09:30:10 UTC

CFP Workshop on MapReduce and its Application (with HPDC'2011) Feb 1st

             Happy New Year 2011


-------------------------------------------------------------------
                           CALL FOR PAPERS

                The Second International Workshop on

            MapReduce and its Applications (MAPREDUCE'11)

            June 8, 2011 HPDC'2011, San Jose, CA, USA

                (http://graal.ens-lyon.fr/mapreduce/)


-------------------------------------------------------------------


SCOPE

Since its introduction in 2004 by Google, MapReduce has become the
programming model of choice for processing large data sets. MapReduce
borrows from functional programming, where a programmer can define
both a Map task that maps a data set into another data set, and a
Reduce task that combines intermediate outputs into a final
result. Although MapReduce was originally developed for use by web
enterprises in large data-centers, this technique has gained a lot of
attention from the scientific community for its applicability in large
parallel data analysis (including geographic, high energy physics,
genomics, etc..).

The purpose of the workshop is to provide a forum for discussing
recent advances, identifying open issues, introducing developments and
tools, and presenting applications and enhancements for MapReduce (or
very similar) systems. We therefore cordially invite contributions
that investigate these issues, introduce new execution environments,
apply performance evaluations and show the applicability to science
and enterprise applications.

TOPICS OF INTEREST

  * MapReduce implementation issues and improvements
  * Implementation optimization for GPU and multi-core systems
  * Extensions to the programing model
  * Large-scale MapReduce (Grid and Desktop Grid)
  * Use of CDN and P2P techniques
  * Heterogeneity and fault-tolerance
  * Scientific data-sets analysis
  * Data and compute-intensive applications
  * Tools and environments for MapReduce
  * Algorithms using the MapReduce paradigm

PAPER SUBMISSIONS

Authors are invited to submit full papers of at most 8 pages,
including all figures and references. Papers should be formatted in
the ACM proceedings style (e.g.,
http://www.acm.org/sigs/publications/proceedings-templates). Submitted
papers must be original work that has not appeared in and is not under
consideration for another conference or a journal. Accepted papers
will be published by ACM in the conference workshops proceedings.

Papers should be submitted here:
http://www.easychair.org/conferences/?conf=mapreduce2011.

IMPORTANT DATES

  * Manuscript submission deadline : February 1st, 2011
  * Acceptance notification : March 1st, 2011
  * Camera-ready paper deadline : March 24, 2011
  * Workshop dates : June 8, 2011

ORGANIZATION COMMITTEE

General Chairs

 Gilles Fedak, INRIA/LIP (contact: Gilles.Fedak AT inria.fr)
 Geoffrey Fox, Indiana University

Publicity chair

 Haiwu He, INRIA

PROGRAM COMMITTEE

  * Alexandre de Assis Bento Lima, Federal University of Rio de Janeiro
  * Gabriel Antoniu, INRIA
  * Francisco V. Brasileiro, Federal University of Campina Grande
  * Franck Cappello, JointLab INRIA UUIC
  * Christian Engelmann, Oak Ridge National Laboratory
  * Jose A.B. Fortes, University of Florida
  * Shantenu Jha, Louisiana State University
  * Jacob Leverich, Standford University
  * Heshan Lin, Virginia Polytechnic Institute and State University
  * Oleg Lodygensky, CNRS
  * Carlo Mastroianni, ICAR-CNR
  * Hidemoto Nakada, AIST
  * Christian Perez, INRIA
  * Judy Qiu, Indiana University
  * Michael C. Schatz, Cold Spring Harbor Laboratory
  * Xuanhuan Shi, Huazhong University of Science and Technology
  * Frederic Suter, IN2P3/CNRS
  * Patrick Valduriez, INRIA
  * Yang Yang, Netflix
  * Jerry Zhao, Google
  -------------------------------------------------------------------