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Implementation of a low-power LVQ architecture on FPGA

Chalbi, Najoua ; Boubaker, Mohamed ; Hedi Bedoui, Mohamed

IET circuits, devices & systems, 2017-11, Vol.11 (6), p.597-604 [Periódico revisado por pares]

The Institution of Engineering and Technology

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Título:
Implementation of a low-power LVQ architecture on FPGA
Autor: Chalbi, Najoua ; Boubaker, Mohamed ; Hedi Bedoui, Mohamed
Assuntos: analytical power model ; architecture-optimising methodology ; circuit optimisation ; decision circuitry ; embedded architecture ; embedded systems ; energy consumption ; ergonomic utilisation ; field programmable gate arrays ; FPGA software design tools ; low-power electronics ; low-power LVQ architecture ; low-power-energy architecture ; LVQ neural network ; LVQ topology ; neural chips ; neural net architecture ; power consumption ; reconfigurable architectures ; Research Article ; Xpower tool
É parte de: IET circuits, devices & systems, 2017-11, Vol.11 (6), p.597-604
Descrição: This study presents an architecture-optimising methodology for embedding an learning vector quantization (LVQ) neural network on an field programmable gate array (FPGA) device. The embedded architecture contains both learning and decision circuitry and is optimised towards the lowest power/energy consumption. The low-power/energy architecture is obtained through the selection of the best one amongst a number of architectures produced by FPGA software design tools that combine power, area and the ergonomic utilisation of internal FPGA resources. A complete characterisation of power at the architectural level was carried out using the Xpower tool. An analytical power model was determined by the following parameters: area, delay and LVQ topology. Concerning the authors’ architecture, there is a 28% gain in the area design. Moreover, it consumes 8% power in the nanoboard 3000 compared with the other ones.
Editor: The Institution of Engineering and Technology
Idioma: Inglês

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Implementation of a low-power LVQ architecture on FPGA

Chalbi, Najoua ; Boubaker, Mohamed ; Hedi Bedoui, Mohamed

The Institution of Engineering and Technology

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