Parallel Performance Studies for a Clustering Algorithm
| dc.contributor.author | Blasberg, Robin V. | |
| dc.contributor.author | Gobbert, Matthias K. | |
| dc.date.accessioned | 2018-10-24T19:30:33Z | |
| dc.date.available | 2018-10-24T19:30:33Z | |
| dc.date.issued | 2008 | |
| dc.description.abstract | Affinity propagation is a clustering algorithm that functions by identifying similar datapoints in an iterative process. Its structure allows for taking full advantage of parallel computing by enabling the solution of larger problems and by solving them faster than possible in serial. We show that our memory-optimal implementation with minimal number of communication commands per iteration performs excellently on the distributed-memory cluster hpc and that it is efficient to use all 128 processor cores currently available. | en |
| dc.description.uri | https://userpages.umbc.edu/~gobbert/papers/BlasbergGobbertTR2008clustering.pdf | en |
| dc.format.extent | 11 pages | en |
| dc.genre | Technical Report | en |
| dc.identifier | doi:10.13016/M2K649X3S | |
| dc.identifier.uri | http://hdl.handle.net/11603/11676 | |
| dc.language.iso | en | en |
| dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
| dc.relation.ispartof | UMBC Mathematics Department Collection | |
| dc.relation.ispartof | UMBC Faculty Collection | |
| dc.relation.ispartofseries | HPCF Technical Report;HPCF-2008-5 | |
| dc.rights | This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author. | |
| dc.subject | affinity propagation | |
| dc.subject | Parallel Performance | en |
| dc.subject | Clustering Algorithm | en |
| dc.subject | datapoints | en |
| dc.subject | memory-optimal | en |
| dc.subject | UMBC High Performance Computing Facility (HPCF) | en |
| dc.title | Parallel Performance Studies for a Clustering Algorithm | en |
| dc.type | Text | en |