Continuous circuit miniaturization and increased process variability point to a future with diminishing returns from dynamic voltage scaling. Operation below Vcc-min has been proposed recently as a mean to reverse this trend. The goal of this paper is to minimize the performance loss due to reduced cache capacity when operating below Vcc-min. A simple method is proposed: disable faulty blocks at low voltage. The method is based on observations regarding the distributions of faults in an array according to probability theory. The key lesson, from the probability analysis, is that as the number of uniformly distributed random faulty cells in an array increases the faults increasingly occur in already faulty blocks. The probability analysis is also shown to be useful for obtaining insight about the reliability implications of other cache techniques.For one configuration used in this paper, block disabling is shown to have on the average 6.6% and up to 29% better performance than a previously proposed scheme for low voltage cache operation. Furthermore, block-disabling is simple and less costly to implement and does not degrade performance at or above Vcc-min operation. Finally, it is shown that a victim-cache enables higher and more deterministic performance for a block-disabled cache.

This paper presents a first-order analytical model for determining the performance degradation caused by permanently faulty cells in architectural and non-architectural arrays. We refer to this degradation as the performance vulnerability factor (PVF).The study assumes a future where cache blocks with faulty cells are disabled resulting in less cache capacity and extra misses while faulty predictor cells are still used but cause additional mispredictions.For a given program run, random probability of permanent cell failure, and processor configuration, the model can rapidly provide the expected PVF as well as lower and upper PVF probability distribution bounds for an individual array or array combination.The model is used to predict the PVF for the three predictors and the last level cache, used in this study, for a wide range of cell failure rates. The analysis reveals that for cell failure rate of up to 1.5e-6 the expected PVF is very small. For higher failure rates the expected PVF grows noticeably mostly due to the extra misses in the last level cache. The expected PVF of the predictors remains small even at high failure rates but the PVF distribution reveals cases of significant performance degradation with a non-negligible probability.These results suggest that designers of future processors can leverage trade-offs between PVF and reliability to sustain area, performance and energy scaling. The paper demonstrates this approach by exploring the implications of different cell size on yield and PVF.

No abstract

No abstract

No abstract