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A detailed power model for field-programmable gate arrays

Poon, Kara K. W., Wilton, Steven J. E., Yan, Andy·2005·ACM Transactions on Design Automation of Electronic Systems

Abstract

Power has become a critical issue for field-programmable gate array (FPGA) vendors. Understanding the power dissipation within FPGAs is the first step in developing power-efficient architectures and computer-aided design (CAD) tools for FPGAs. This article describes a detailed and flexible power model which has been integrated in the widely used Versatile Place and Route (VPR) CAD tool. This power model estimates the dynamic, short-circuit, and leakage power consumed by FPGAs. It is the first flexible power model developed to evaluate architectural tradeoffs and the efficiency of power-aware CAD tools for a variety of FPGA architectures, and is freely available for noncommercial use. The model is flexible, in that it can estimate the power for a wide variety of FPGA architectures, and it is fast, in that it does not require extensive simulation, meaning it can be used to explore a large architectural space. We show how the model can be used to investigate the impact of various architectural parameters on the energy consumed by the FPGA, focusing on the segment length, switch block topology, lookuptable size, and cluster size.

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Metadata

Authors
Poon, K. K. W., Wilton, S. J. E., & Yan, A.
Venue
ACM Transactions on Design Automation of Electronic Systems
Published
2005-04
Volume
10
Issue
2
Pages
279-302
ISSN
  • 1084-4309 (ISSN-L)
  • 1557-7309
OpenAlex
W2095558812
Cited by
170
References
0
FWCI
13.67
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: A detailed power model for field-programmable gate arrays. https://app.cochat.ai/papers/10.1145/1059876.1059881
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Poon, K. K. W., Wilton, S. J. E., & Yan, A. (2005). A detailed power model for field-programmable gate arrays. ACM Transactions on Design Automation of Electronic Systems. https://doi.org/10.1145/1059876.1059881

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.