Variability-aware and fault-tolerant self-adaptive applications for many-core chips

The coming era of chips consisting of billions of gates foreshadows processors containing thousands of unreliable cores. In this context, high energy efficiency will be available, under the constraint that applications leverage the large amount of computing cores, while masking frequent faults of the chip. In this paper, an high-level method is proposed to map and manage a parallel application on an unreliable many-cores processor System on Chip. The approach takes into account versatile constraints relative to these processors (e.g. variability, core-level DVFS) and a generic algorithm is proposed. The distributed mapping process is based on the dynamic search of the best-suited processing node, upon task creation or node defect. An adaptive stop criteria is defined in order to balance the mapping impact and application efficiency gains. The validity of the proposition is assessed with high-level simulations, under different variability and application conditions.