Call for Papers
|When||Jun 18, 2012 - Jun 19, 2012|
|Where||Delft, the Netherlands|
|Submission Deadline||Mar 4, 2012|
|Notification Due||Mar 26, 2012|
|Final Version Due||Apr 16, 2012|
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.
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.