Self-Test and Adaptation for Random Variations in Reliability

Abstract

Random physical variations and noise are growing challenges for advanced electronic systems. Field programmable systems can, in principle, adapt to these phenomena, but two main problems must be addressed: how to efficiently characterize random variations and how to perform subsequent optimization. This paper addresses both of these questions. First, an approach to self-test is presented that uses on-chip noise emulation to quickly characterize some of the hidden variations in latches. Our noise-injection experiments demonstrate that there can be significant spreads in latch reliability even with current 65nm field-programmable gate arrays (FPGAs). We detected coefficients of variation as high as 77%. Second, we propose an approach to self-optimization using local resource swapping. Experiments on two FPGAs show improvements in mean-time-between-failures (MTBF) of up to 60%.

Low-cost sensing with ring oscillator arrays for healthier reconfigurable systems

“…An example of off-line characterization of FPGA component delays is given in Sedcole and Cheung [2006]. While the present article is focused on correlated variation, an important and related issue is sensing stochastic variation; in Zick and Hayes [2010b] we address the sensing of stochastic variations in component single event upset susceptibility. There has been much work in the area of online testing for hard defects which are in a sense highly localized variations.…”