Nano-crossbar arrays have emerged as area and power efficient structures with an aim of achieving high performance computing beyond the limits of current CMOS. Due to the stochastic nature of nano-fabrication, nano arrays show different properties both in structural and physical device levels compared to conventional
Hardware implementations of artificial neural networks (ANNs) have become feasible due to the advent of persistent 2-terminal devices such as memristor, phase change memory, MTJs, etc. Hybrid memristor crossbar/CMOS systems have been studied extensively and demonstrated experimentally. In these circuits, memristors located at each cross point in a crossbar are, however, stacked on top of CMOS circuits using back end of line processing (BOEL), limiting scaling.
Non-volatile 3D FPGA research to date utilizes layer-by-layer stacking of 2D CMOS / RRAM circuits. On the other hand, vertically-composed 3D FPGA that integrates CMOS and RRAM circuits has eluded us, owing to the difficult requirement of highly customized regional doping and material insertion in 3D to build and route complementary p- and n-type transistors as well as resistive switches. In the layer-by-layer nonvolatile 3D FPGA, the connectivity between the monolithically stacked RRAMs and underlying CMOS circuits is likely to be limited and lead to large parasitic RCs.
Design for power-delivery network (PDN) is one of the major challenges in 3D IC technology. In the typical layer-by-layer stacked monolithic 3D (M3D) approaches, PDN has limited accessibility to the device layer away from power/ground source due to limited routability and routing resources in the vertical direction. This results in an incomplete and low-density PDN design and also severe IR-drop issue. Some improved M3D approaches try to enlarge design area to create additional vertical routing resources for robust and high-density PDN design.
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.
Conventional 2D CMOS technology is reaching fundamental scaling limits, and interconnect bottleneck is dominating integrated circuit (IC) power and performance. While 3D IC technologies using Through Silicon Via or Monolithic Inter-layer Via alleviate some of these challenges, they follow a similar layout and routing mindset as 2D CMOS. This is insufficient to address routing requirements in high-density 3D ICs and even causes severe routing congestion at large-scale designs, limiting their benefits and scalability.
This paper introduces a new fine-grained 3D IC fabric technology called NP-Dynamic Skybridge. Skybridge is a family of 3D IC technologies that provides fine-grained vertical integration. In comparison to the original 3D Skybridge, the NP-Dynamic approach enables a more comprehensive logic style for improved efficiency. It addresses device, circuit, connectivity and manufacturability requirements with an integrated 3D mindset. The NP-Dynamic 3D circuit style enables wide range of logic expressions, simple clocking scheme, and reduces buffer requirements.
Conventional CMOS technology is reaching fundamental scaling limits, and interconnection bottleneck is dominating IC power and performance. Migrating to 3-D integrated circuits, though promising, has eluded us due to inherent customization and manufacturing requirements in CMOS that are incompatible with 3-D organization. Skybridge, a fine-grained 3-D IC fabric technology was recently proposed towards this aim, which offers a paradigm shift in technology scaling and design.
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.
Probabilistic machine intelligence paradigms such as Bayesian Networks (BNs) are widely used in critical real-world applications. However they cannot be employed efficiently for large problems on conventional computing systems due to inefficiencies resulting from layers of abstraction and separation of logic and memory. We present an unconventional nanoscale magneto-electric machine paradigm, architected with the principle of physical equivalence to efficiently implement causal inference in BNs.