NDLI: An efficient power estimation methodology for complex RISC processor-based platforms

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An efficient power estimation methodology for complex RISC processor-based platforms

Content Provider	ACM Digital Library
Author	Ben Atitallah, Rabie Niar, Smail Senn, Eric Dekeyser, Jean-Luc Rethinagiri, Santhosh Kumar
Abstract	In this contribution, we propose an efficient power estimation methodology for complex RISC processor-based platforms. In this methodology, the Functional Level Power Analysis (FLPA) is used to set up generic power models for the different parts of the system. Then, a simulation framework based on virtual platform is developed to evaluate accurately the activities used in the related power models. The combination of the two parts above leads to a heterogeneous power estimation that gives a better trade-off between accuracy and speed. The usefulness and effectiveness of our proposed methodology is validated through ARM9 and ARM CortexA8 processor designed respectively around the OMAP5912 and OMAP3530 boards. This efficiency and the accuracy of our proposed methodology is evaluated by using a variety of basic programs to complete media benchmarks. Estimated power values are compared to real board measurements for the both ARM940T and ARM CortexA8 architectures. Our obtained power estimation results provide less than 3% of error for ARM940T processor, 3.5% for ARM CortexA8 processor-based system and 1x faster compared to the state-of-the-art power estimation tools.
Starting Page	239
Ending Page	244
Page Count	6
File Format	PDF
ISBN	9781450312448
DOI	10.1145/2206781.2206839
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2012-05-03
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Asic Tlm Flpa Power estimation Virtual platform Systemc
Content Type	Text
Resource Type	Article

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