Life Guard: A Reinforcement Learning-Based Task Mapping Strategy for Performance-Centric Aging Management

Device scaling to subdeca nanometer has pushed device aging as a primary design concern. In manycore systems, inevitable process variation further adds to delay degradation and, coupled with the scalability issues in manycores, makes aging management, while meeting performance demands, a complex problem. Life-Guard is a performance-centric reinforcement learning-based task mapping strategy that leverages the different impact of applications on aging for improving system health. Experimental results, comparing LifeGuard with two state-of-the-art aging optimizing techniques, on a 256-core system, showed that LifeGuard led to improved health for, respectively, 57% and 74% of the cores, and also an enhanced aggregate core frequency.