Scalable analytical model for reliability measures in aging VLSI by interacting Markovian agents

Aging phenomena in VLSI are enhanced by the shrinkage in transistor dimension with consequent increase in operating temperature and current density, and are now recognized as a major cause in the reduction of the chip lifetime and reliability. The present study proposes an analytical framework based on an Markovian Agent Model (MAM), able to capture aging effects in VLSI systems, while considering at the same time the interactions between VLSI components as a function of their local position on the chip and the dynamic redistribution of the workload with the progressive failure of components. The paper presents the MAM formalism and how a fairly general aging model can be built with this formalism. The flexibility and the effectiveness of the model are illustrated by computing performance–reliability related measures on two case studies with a different flavor: a Multi-Core System-on-Chip and a Solid State Drive.