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MapReduce MPI library (MR-MPI) v. 1.0

RESOURCE

Publicly Accessible Repository
https://github.com/sandialabs/mapreduce
https://doi.org/10.11578/dc.20171025.on.1024

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Abstract

The MapReduce MPI library is a software tool for performing MapReduce operations on a distributed memory parallel computer via message passing (MPI). These are data-processing or computational operations which achieve parallelism by breaking a large task into two stages, a map and a reduce . Each of these are formulated as simple on-processor functions which the user can easily write. The library assigns independent tasks to processors and performs the parallel data movement and transformations behind the scenes.
Developers:
Release Date:
2009-01-08
Project Type:
Open Source, Publicly Available Repository
Software Type:
Scientific
Programming Languages:
C++
Shell
C
Makefile
HTML
Python
Odin
Version:
1.0
Licenses:
BSD 3-clause "New" or "Revised" License
Sponsoring Org.:
Code ID:
6015
Site Accession Number:
SCR# 1174
Research Org.:
Sandia National Laboratories
Country of Origin:
United States

RESOURCE

Publicly Accessible Repository
https://github.com/sandialabs/mapreduce
https://doi.org/10.11578/dc.20171025.on.1024

SAVE / SHARE



SNL Badge

Citation Formats

PLIMPTON, STEVEN. MapReduce MPI library (MR-MPI) v. 1.0. Computer Software. https://github.com/sandialabs/mapreduce. USDOE. 08 Jan. 2009. Web. doi:10.11578/dc.20171025.on.1024.
PLIMPTON, STEVEN. (2009, January 08). MapReduce MPI library (MR-MPI) v. 1.0. [Computer software]. https://github.com/sandialabs/mapreduce. https://doi.org/10.11578/dc.20171025.on.1024.
PLIMPTON, STEVEN. "MapReduce MPI library (MR-MPI) v. 1.0." Computer software. January 08, 2009. https://github.com/sandialabs/mapreduce. https://doi.org/10.11578/dc.20171025.on.1024.
@misc{ doecode_6015,
title = {MapReduce MPI library (MR-MPI) v. 1.0},
author = {PLIMPTON, STEVEN},
abstractNote = {The MapReduce MPI library is a software tool for performing MapReduce operations on a distributed memory parallel computer via message passing (MPI). These are data-processing or computational operations which achieve parallelism by breaking a large task into two stages, a map and a reduce . Each of these are formulated as simple on-processor functions which the user can easily write. The library assigns independent tasks to processors and performs the parallel data movement and transformations behind the scenes.},
doi = {10.11578/dc.20171025.on.1024},
url = {https://doi.org/10.11578/dc.20171025.on.1024},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20171025.on.1024}},
year = {2009},
month = {jan}
}