Multi-core for k-means clustering on FPGA
In this paper, a configurable many-core hardware/ software architecture is proposed to efficiently execute the widely known and commonly used K-means clustering algorithm. A prototype was designed and implemented on a Xilinx Zynq- 7000 All Programmable SoC. A single core configured with the slowest...
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| Outros Autores: | , |
| Formato: | article |
| Idioma: | eng |
| Publicado em: |
2016
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| Assuntos: | |
| Texto completo: | http://hdl.handle.net/10400.21/6601 |
| País: | Portugal |
| Oai: | oai:repositorio.ipl.pt:10400.21/6601 |
| Resumo: | In this paper, a configurable many-core hardware/ software architecture is proposed to efficiently execute the widely known and commonly used K-means clustering algorithm. A prototype was designed and implemented on a Xilinx Zynq- 7000 All Programmable SoC. A single core configured with the slowest configuration achieves a 10X speed-up compared to the software only solution. The system is fully scalable and capable of achieving much higher speed-ups by increasing its parallelism. |
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