NDLI: A lightweight-system-level power and area estimation methodology for application specific instruction set processors

Content Provider	IEEE Xplore Digital Library
Author	Shah, S.A.A. Wagner, J. Schuster, T. Berekovic, M.
Copyright Year	2014
Description	Author affiliation: Chip Design for Embedded Comput., Tech. Univ. Braunschweig, Braunschweig, Germany (Shah, S.A.A.; Wagner, J.; Schuster, T.; Berekovic, M.)
Abstract	Detailed power estimation is a tedious and time consuming task in modern ASIP design. To facilitate this process, we present faster and fully automated estimation models for use at system level. In the first step of our approach, we calculate normalized values for all the basic design components of the processor that are related to power and area (e.g. memories, register files, function units, etc). These normalized values are estimated based on processors with different configurations (e.g., different memory sizes) and then stored in a database. Later, in the second step, this information is used to estimate the power of new derived architectures. To that end, we combine the previously calculated normalized power data with the component configurations and switching information from system-level simulation. The approach is demonstrated on the example of an Intel ASIP design flow (Silicon Hive). We report power and area estimates for four different ASIP designs. The mean error of the area prediction is 10%, while the mean error in power prediction is 15%.
Starting Page	1
Ending Page	5
File Size	1125967
Page Count	5
File Format	PDF
ISBN	9781479954124
DOI	10.1109/PATMOS.2014.6951886
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-09-29
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	ASIPs Program processors System-level cost estimation Computational modeling Estimation Computer architecture Architecture synthesis Silicon Registers System-on-chip
Content Type	Text
Resource Type	Article

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