Optimizing MPI Collective Communication by Orthogonal Structures

Optimizing MPI Collective Communication by Orthogonal Structures

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Many parallel applications from scientific computing use MPI collective communication operations to collect or distribute data. Since the execution times of these communication operations increase with the number of participating processors, scalability problems might occur. In this article, we show...

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Bibliographic Details
Main Authors: Kühnemann, Matthias, Rauber, Thomas, Rünger, Gudula
Other Authors: TU Chemnitz, Fakultät für Informatik
Format: Others
Language:English
Published: Universitätsbibliothek Chemnitz 2007
Subjects:
communication operations
message passing
optimization
parallel programming
scientific computing
ddc:000
MPI <Schnittstelle>
Parallelverarbeitung
Online Access:http://nbn-resolving.de/urn:nbn:de:swb:ch1-200701061
http://nbn-resolving.de/urn:nbn:de:swb:ch1-200701061
http://www.qucosa.de/fileadmin/data/qucosa/documents/5422/data/CSR-03-03.pdf
http://www.qucosa.de/fileadmin/data/qucosa/documents/5422/20070106.txt

Internet

http://nbn-resolving.de/urn:nbn:de:swb:ch1-200701061
http://nbn-resolving.de/urn:nbn:de:swb:ch1-200701061
http://www.qucosa.de/fileadmin/data/qucosa/documents/5422/data/CSR-03-03.pdf
http://www.qucosa.de/fileadmin/data/qucosa/documents/5422/20070106.txt

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