If you use the MR-MPI library in one of your publications, please cite the following paper and also list the URL of the MR-MPI WWW site, namely http://mapreduce.sandia.gov.
This paper describes the MR-MPI library and several MapReduce graph algorithms for informatics problems:
MapReduce in MPI for Large-Scale Graph Algorithms, S. J. Plimpton and K. D. Devine, Parallel Computing, 37, 610-632 (2011). (abstract) (preprint)
The authors of the MR-MPI library are Steve Plimpton (sjplimp at sandia.gov) and Karen Devine (kddevin at sandia.gov).
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This is a paper by Seung-Jin Sul and Andrey Tovchigrechko (J Craig Venter Institute) on using the MR-MPI library to parallelize two computational biology algorithms: BLAST and a neural network approach called SOM. They've run their models successfully on up to 1024 processors of the U Texas Ranger machine.
Parallelizing BLAST and SOM algorithms with MapReduce-MPI library, S.-J. Sul and A. Tovchigrechko, IEEE International Parallel & Distributed Processing HICOMB Symposium, (2011). (abstract) (download paper from HICOMB 2011 proceedings site)
Ths is a paper by Boyu Zhang and Michela Taufer (U Delaware) and collaborators who wrote two variants of a general analysis algorithm for large structural biology datasets requiring distributed memory. The algorithm performance was evaluated on 1024 cores across 15 data sets.
On Efficiently Capturing Scientific Properties in Distributed Big Data without Moving the Data: A Case Study in Distributed Structural Biology using MapReduce, B. Zhang, T. Estrada, P. Cicotti, and M. Taufer, in the Proceedings of the 16th IEEE International Conferences on Computational Science and Engineering (CSE), Sydney, Australia (2013). (abstract) (download paper from http://gcl.cis.udel.edu/publications/conferences/13_CSE_zhang.pdf)