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

Jevtic, Ruzica; Carreras Vaquer, Carlos y 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.

Descripción

Título: Fast and Accurate Power Estimation of FPGA DSP Components Based on High-level Switching Activity Models
Autor/es:
  • Jevtic, Ruzica
  • Carreras Vaquer, Carlos
  • Caffarena Fernández, Gabriel
Tipo de Documento: Artículo
Título de Revista/Publicación: International Journal of Electronics
Fecha: Julio 2008
Volumen: 95
Materias:
Escuela: E.T.S.I. Telecomunicación (UPM)
Departamento: Ingeniería Electrónica
Grupo Investigación UPM: FPGA; low power; high-level synthesis; switching activity; power estimation.
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

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.

Más información

ID de Registro: 2879
Identificador DC: http://oa.upm.es/2879/
Identificador OAI: oai:oa.upm.es:2879
Identificador DOI: 10.1080/00207210801924024
URL Oficial: http://www.tandf.co.uk/journals/titles/00207217.asp
Depositado por: Memoria Investigacion
Depositado el: 23 Abr 2010 09:08
Ultima Modificación: 20 Abr 2016 12:30
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