Wear-out related permanent faults are projected to make system lifetime a critical issue for all designs. In embedded systems, lifetime can be increased using slack, underutilization in execution and storage resources, so that when components fail, data and tasks can be re-mapped and re-scheduled. The design space of possible slack allocation is both large and complex. However, based on the observation that useful slack is often quantized, we have developed an approach that effectively and efficiently allocates execution and storage slack to jointly optimize system lifetime and cost. While exploring less than 1.4% of the slack allocation design space, our approach consistently outperforms alternative slack allocation techniques to find sets of designs within 1.4% of the lifetime-cost Pareto-optimal front.
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