One of the fundamental challenges to the performance gain in advanced semiconductor technology
is aging-induced delay degradation of transistors, which consequently increases the
logic gates delays and eventually critical paths delays. Hence, designers have to add significant
time margin as guardband to the main critical path, which imposes considerable
performance degradation to the system. Temperature and stress (or usage) are the major
sources of transistor’s aging, which vary for different applications and are highly workload
dependent. This thesis covers challenges and opportunities in monitoring aging, its effects
and methods to combat the imposed performance and lifetime degradation in nanometer
scales semiconductor platforms.
We devise methods to monitor and mitigate aging in computing platforms ranging from
the conventional reconfigurable architectures to the contemporary 3D network-on-chips and
many-core systems. To monitor aging-induced delay degradation on critical paths, we proposed
SENSIBLE, a highly scalable aging sensor design that can help system-level designers
to detect aging and react accordingly. Additionally, we proposed an application-dependant
filtering methodology to select Representative Critical Paths (RCPs) among a large pool of
critical paths for aging monitoring in reconfigurable architectures. Furthermore, two proactive
methods are presented to mitigate aging impacts on application’s critical paths and SRAM cells in reconfigurable architectures. The former is a high-level physical planning
coupled with a reconfiguration policy and the latter is STABLE, a post-synthesis stress aware
Boolean matching technique. To mitigate and monitor aging on Network on Chip
(NoC) components in both 2D and 3D IC designs we proposed AROMa, which is an aging-aware
adaptive routing algorithm. To this end, we devised Centralized Aging Table (CAT) to
convert transistor level aging phenomenon to the workloads’ behavior in NoC-based manycore
systems. Finally, an aging-aware task mapping, ADAMANT, is proposed to balance
aging in many-core heterogeneous architectures’ components.