Enhancing multicore reliability through wear compensation in online assignment and scheduling

System reliability is a crucial concern especially in multicore systems which tend to have high power density and hence temperature. Existing reliability-aware methods are either slow and non-adaptive (offline techniques) or do not use task assignment and scheduling to compensate for uneven core wear states (online techniques). In this article, we present a dynamically-activated task assignment and scheduling algorithm based on theoretical results that explicitly optimizes system life-time. We also propose a data distillation method that dramatically reduces the size of the thermal profiles to make full system reliability analysis viable online. Simulation results show that our algorithm results in between 27–291% improvement to system lifetime compared to existing techniques for four-core systems.