NDLI: Analytical models for leakage power estimation of memory array structures

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Analytical models for leakage power estimation of memory array structures

Content Provider	ACM Digital Library
Author	Khouri, Kamal Dutt, Nikil Mamidipaka, Mahesh Abadir, Magdy
Abstract	There is a growing need for accurate power models at the system level. Memory structures such as caches, Branch Target Buffers (BTBs), and register files occupy significant area in contemporary SoC designs and are the main contributors to system leakage power dissipation. Existing models for leakage power estimation in array structures typically use coefficients derived from elaborate SPICE simulations. However, these methodologies are not applicable to array designs in a newer technology, that require power estimates early in the design cycle. In this paper, we propose analytical models for array structures that are based only on high level design parameters. Assuming typical circuit implementation styles, we identify the transistors that contribute to the leakage power in each array sub-circuit and develop models as a function of the operation (read/write/idle) on the array and organizational parameters of the array. The developed models are validated by comparing their estimates against the leakage power measured using SPICE simulations on industrial array designs belonging to the $e500^{1}$ processor core. The comparison shows that the models are accurate with an error margin of less than 21.5% and thus can be used in high-level power-performance exploration. Interestingly, in array designs with dual threshold voltage technology, we observed that contrary to the general expectation, the array memory core contributes to just 9% and the address decoder contributes to as much as 62% of the total leakage power.
Starting Page	146
Ending Page	151
Page Count	6
File Format	PDF
DOI	10.1145/1016720.1016757
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2004-09-08
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Estimation Leakage power Srams
Content Type	Text
Resource Type	Article

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