MapReduce 2012 - The Third Int'l Workshop on MapReduce and its Applications

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