Probabilistic graphical models like Bayesian Networks (BNs) are powerful cognitive-computing formalisms, with many similarities to human cognition. These models have a multitude of real-world applications. New emerging-technology based circuit paradigms leveraging physical equivalence e.g., operating directly on probabilities vs. introducing layers of abstraction, have shown promise in raising the performance and overall efficiency of BNs, enabling networks with millions of random variables.

Thermal management is one of the critical challenges in 3D integrated circuits. Incorporating thermal optimizations during the circuit design stages requires a convenient automatic method of doing thermal characterization for feedback purposes. In this paper, we present a methodology, which supports thermal characterization by automatically extracting the steady-state thermal modeling resistance network from a post-placement physical design. The method follows a two-level hierarchical approach.

Continuous scaling of CMOS has been the major catalyst in miniaturization of integrated circuits (ICs) and crucial for global socio-economic progress. However, scaling to sub-20nm technologies is proving to be challenging as MOSFETs are reaching their fundamental limits and interconnection bottleneck is dominating IC operational power and performance. Migrating to 3-D, as a way to advance scaling, has eluded us due to inherent customization and manufacturing requirements in CMOS that are incompatible with 3-D organization.

Neuromorphic computing mimicking the functionalities of mammalian brain holds the promise for cognitive capabilities enabling new intelligent applications. However, research efforts so far mainly focused on using analog and digital CMOS technologies to emulate neural activities, and are yet to achieve expected benefits. They suffer from limited scalability, density overhead, interconnection bottleneck and power consumption related constraints. In this paper, we present a transformative approach for neuromorphic computing with Wave Interference Functions (WIF).

Migration to 3-D provides a possible pathway for future Integrated Circuits (ICs) beyond 2-D CMOS, which is at the brink of its own fundamental limits. Partial attempts so far for 3-D integration using die to die and layer to layer stacking do not represent true progression , and suffer from their own challenges with lack of intrinsic thermal management being among the major ones. Our proposal for 3-D IC, Skybridge, is a truly fine-grained vertical nanowire based fabric that solves technology scaling challenges, and at the same time achieves orders of magnitude benefits over 2-D CMOS.