High Performance Data Clustering : A Comparative Analysis of Performance for GPU, RASC, MPI, and OpenMP Implementations
Compared to Beowulf clusters and shared-memory machines, GPU and FPGA are emerging alternative architectures that provide massive parallelism and great computational capabilities. These architectures can be utilized to run compute-intensive algorithms to analyze ever-enlarging datasets and provide s...
| Veröffentlicht in: | The Journal of supercomputing. - 1998. - 70(2014), 1 vom: 01. Okt., Seite 284-300 |
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| Format: | Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2014
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| Zugriff auf das übergeordnete Werk: | The Journal of supercomputing |
| Schlagworte: | Journal Article HPC K-means Clustering Parallel Data Clustering Reconfigurable Computing Scalability |