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Rapid Energy Estimation for Hardware-Software Codesign Using FPGAs

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Abstract

By allowing parts of the applications to be executed either on soft processors (as software programs) or on customized hardware peripherals attached to the processors, FPGAs have made traditional energy estimation techniques inefficient for evaluating various design tradeoffs. In this paper, we propose a high-level simulation-based two-step rapid energy estimation technique for hardware-software codesign using FPGAs. In the first step, a high-level hardware-software cosimulation technique is applied to simulate both the hardware and software components of the target application. High-level simulation results of both software programs running on the processors and the customized hardware peripherals are gathered during the cosimulation process. In the second step, the high-level simulation results of the customized hardware peripherals are used to estimate the switching activities of their corresponding register-transfer/gate level ("low-level") implementations. We use this information to employ an instruction-level energy estimation technique and a domain-specific energy performance modeling technique to estimate the energy dissipation of the complete application. A Matlab/Simulink-based implementation of our approach and two numerical computation applications show that the proposed energy estimation technique can achieve more than 6000x speedup over low-level simulation-based techniques while sacrificing less than 10% estimation accuracy. Compared with the measured results, our experimental results show that the proposed technique achieves an average estimation error of less than 12%.

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Correspondence to Jingzhao Ou.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Keywords

  • Estimation Accuracy
  • Average Estimation
  • Energy Estimation
  • Software Component
  • Energy Performance