Fast and Accurate Power Estimation of FPGA DSP Components Based on High-level Switching Activity Models

Jevtic, Ruzica and Carreras Vaquer, Carlos and Caffarena Fernández, Gabriel (2008). Fast and Accurate Power Estimation of FPGA DSP Components Based on High-level Switching Activity Models. "International Journal of Electronics", v. 95 (n. 7); pp. 653-668. ISSN 0020-7217. https://doi.org/10.1080/00207210801924024.

Description

Title: Fast and Accurate Power Estimation of FPGA DSP Components Based on High-level Switching Activity Models
Author/s:
  • Jevtic, Ruzica
  • Carreras Vaquer, Carlos
  • Caffarena Fernández, Gabriel
Item Type: Article
Título de Revista/Publicación: International Journal of Electronics
Date: July 2008
ISSN: 0020-7217
Volume: 95
Subjects:
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Ingeniería Electrónica
UPM's Research Group: FPGA; low power; high-level synthesis; switching activity; power estimation.
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

When designing DSP circuits, it is important to predict their power consumption early in the design flow in order to reduce the repetition of time consuming design phases. High-level modelling is required for fast power estimation when a design is modified at the algorithm level. This paper presents a novel high-level analytical approach to estimate logic power consumption of arithmetic components implemented in FPGAs. In particular, models of adders and multipliers are presented in detail. The proposed methodology considers input signal correlation and glitching produced inside the component. It is based on an analytical computation of the switching activity in the component which takes into account the component architecture. The complete model can estimate the power consumption for any given clock frequency, signal statistics and operands’ word-lengths. Compared to other proposed power estimation methods, the number of circuit simulations needed for characterizing the power model of the component is highly reduced. The accuracy of the model is within 10% of low-level power estimates given by the tool XPower, and it achieves better overall performance.

More information

Item ID: 2879
DC Identifier: http://oa.upm.es/2879/
OAI Identifier: oai:oa.upm.es:2879
DOI: 10.1080/00207210801924024
Official URL: http://www.tandf.co.uk/journals/titles/00207217.asp
Deposited by: Memoria Investigacion
Deposited on: 23 Apr 2010 09:08
Last Modified: 20 Apr 2016 12:30
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