article · 2007
Fault Modeling and Detection for
Wei Pei, Wen-Ben Jone, Yiming Hu
Cited by 0Abstract and details only
Abstract
Due to the spatial-locality property of data caches and the temporal-locality property of instruction caches, signif- icant leakage reduction can be achieved by switching a large number of cache lines into the low-power standby or drowsy mode. It has been shown that 80%-90% of the data cache lines can be maintained in drowsy state without affecting the performance by more than 0.6% (IEEE Trans. Very Large Scale Integr. (VLSI) Syst., vol. 12, no. 2, pp. 167-184, Feb. 2004). However, with the introduction of the drowsy-cache design technique, new fault be- haviors appear and more restrictive design rules must be applied to the chip fabrication process. In this paper, we simulate all possible spot defects (SDs) under normal mode and drowsy mode in different resistance regions using HSpice. Six new fault models appear with the introduction of drowsy mode for memory arrays. When we derive a march algorithm for the new fault models of this low-power cache, several simplification rules are utilized to reduce the test complexity. According to these simplification rules, each of these new faults has its equivalent counterpart existent in both data caches and instruction caches. As a result, we develop a march algorithm which can detect all SDs in either data caches or instruction caches. Since some faults occur only in drowsy mode, a built-in self-repair (BISR) scheme is developed. By utilizing BISR, the cache can still work even if some cache lines fail to work in drowsy mode.
Cite this paper
Pei, W., Jone, W.-B., & Hu, Y. (2007). Fault Modeling and Detection for.
Pei, Wei, et al. “Fault Modeling and Detection for.” 2007.
Pei, Wei, Wen-Ben Jone, and Yiming Hu. 2007. “Fault Modeling and Detection for.”
Pei, W., Jone, W.-B. and Hu, Y. (2007) ‘Fault Modeling and Detection for’.
@article{pei2007fault,
title = {{Fault Modeling and Detection for}},
author = {Pei, Wei and Jone, Wen-Ben and Hu, Yiming},
year = {2007}
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