Systems for Hyperspectral Imaging Cancer Detection Daniel Madroal - - PowerPoint PPT Presentation
Energy Consumption Reduction on High Performance Embedded Systems for Hyperspectral Imaging Cancer Detection Daniel Madroal Universidad Politcnica de Madrid (UPM) School of Telecommunications Engineering and Systems (ETSIST) Research
Universidad Politécnica de Madrid (UPM) School of Telecommunications Engineering and Systems (ETSIST) Research Center for Software Technologies and Multimedia Systems (CITSEM)
CPS Summer School, Alghero Monday 25th September, 2017
Daniel Madroñal
Energy Consumption Reduction on High Performance Embedded Systems for Hyperspectral Imaging Cancer Detection
2
Energy Consumption Reduction on High Performance Embedded Systems for Hyperspectral Imaging Cancer Detection
3
Energy Consumption Reduction on High Performance Embedded Systems for Hyperspectral Imaging Cancer Detection
4
8 10 12 14 16 18 1 2 3 4
8 10 12 14 16 18 1 2 3 4
Power (W) Workpoint
Energy Consumption Reduction on High Performance Embedded Systems for Hyperspectral Imaging Cancer Detection
5
PE PE PE PE PE PE PE PE PE PE PE PE PE PE PE PE Shared Memory (2 MB)
DMA DMA DMA DMA DMA DMA DMA DMA
2GB DDR I/O South I/O North 2GB DDR
Energy Consumption Reduction on High Performance Embedded Systems for Hyperspectral Imaging Cancer Detection
6
Power (W)
STRESS 8,55 8,93 13,31 15,18 14,55 3,26 0,06 0,05 0,04 29,14 0,82 0,80 0,56
0,01 0,1 1 10 100 8 9 10 11 12 13 14 15 16 0-400-0 1-400-1 256-400-1 256-500-1 256-500-8
Time (s) / Energy (J) Power (W) PEs / Freq / Total DMAs
SVM
Energy Consumption Reduction on High Performance Embedded Systems for Hyperspectral Imaging Cancer Detection
7