Power Consumption Model for Partial Dynamic Reconfiguration - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2012

Power Consumption Model for Partial Dynamic Reconfiguration


In the context of embedded systems development, two important challenges are the efficient use of silicon area and the energy consumption minimization. Hardware accelerated tasks allow to reduce energy consumption of several orders of magnitude, compared to software execution, but these tasks require silicon area and consume power even when they are unused (idle power). Dynamic and Partial Reconfiguration (DPR) brings, to System-on-Chip architectures, an interesting answer by allowing to share a piece of silicon surface between different dedicated accelerators and thus brings the opportunity to reduce power consumption. Nevertheless, many parameters like reconfiguration overhead, accelerator area and performance tradeoff, idle power consumption, etc. make power consumption gain difficult to evaluate. In order to take good implementation choices, it is important to have a precise power and energy consumption estimation of the partial reconfiguration process. In this context, this paper presents a detailed investigation of power consumption of a DPR process using Xilinx ICAP reconfiguration controller. From these results we propose three power models with different complexity/accuracy tradeoffs which helps to analyze the benefits of using accelerated and dynamically reconfigurable tasks in comparison with classical static configuration or full software execution
No file

Dates and versions

hal-00741611 , version 1 (14-10-2012)



Robin Bonamy, Daniel Chillet, Sebastien Bilavarn, Olivier Sentieys. Power Consumption Model for Partial Dynamic Reconfiguration. International Conference on ReConFigurable Computing and FPGA (RECONFIG'2012), Dec 2012, Cancun, Mexico. pp.1-8, ⟨10.1109/ReConFig.2012.6416772⟩. ⟨hal-00741611⟩
161 View
0 Download



Gmail Facebook Twitter LinkedIn More