@article{
 title = {Towards efficient mapreduce using MPI},
 type = {article},
 year = {2009},
 keywords = {Cluster nodes; Collective operations; Common strat,Message passing,Phase interfaces},
 pages = {240-249},
 volume = {5759 LNCS},
 websites = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-70350443831&doi=10.1007%2F978-3-642-03770-2-30&partnerID=40&md5=c37c845cc6ee284a7da6de01d1d703cb},
 city = {Espoo},
 id = {82e9c14a-78de-3a68-a1c4-25466d017f19},
 created = {2018-01-09T20:30:38.199Z},
 file_attached = {false},
 profile_id = {42d295c0-0737-38d6-8b43-508cab6ea85d},
 last_modified = {2018-03-12T19:03:18.860Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Hoefler2009240},
 source_type = {article},
 notes = {cited By 45; Conference of 16th European Parallel Virtual Machine and Message Passing Interface Users' Group Meeting, EuroPVM/MPI ; Conference Date: 7 September 2009 Through 10 September 2009; Conference Code:77831},
 folder_uuids = {2aba6c14-9027-4f47-8627-0902e1e2342b},
 private_publication = {false},
 abstract = {MapReduce is an emerging programming paradigm for data-parallel applications. We discuss common strategies to implement a MapReduce runtime and propose an optimized implementation on top of MPI. Our implementation combines redistribution and reduce and moves them into the network. This approach especially benefits applications with a limited number of output keys in the map phase. We also show how anticipated MPI-2.2 and MPI-3 features, such as MPI-Reduce-local and nonblocking collective operations, can be used to implement and optimize MapReduce with a performance improvement of up to 25% on 127 cluster nodes. Finally, we discuss additional features that would enable MPI to more efficiently support all MapReduce applications. © 2009 Springer Berlin Heidelberg.},
 bibtype = {article},
 author = {Hoefler, T and Lumsdaine, A and Dongarra, J},
 doi = {10.1007/978-3-642-03770-2-30},
 journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}
}

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