SkyBridge-3D-CMOS 2.0: IC Technology for Stacked-Transistor 3D ICs beyond FinFETs

For sub-5nm technology nodes, gate-all-around (GAA) FETs are positioned to replace FinFETs to enable the continued miniaturization of ICs in the future. In this paper, we introduce SkyBridge-3D-CMOS 2.0, a 3D-IC technology featuring integration of stacked vertical GAAFETs and 3D interconnects. It aims to provide an integrated solution to critical technology aspects, especially when scaling to sub-5nm nodes. We address important aspects such as 3D fabric components, CAD tool flow, compact model for the GAAFETs and a scalable manufacturing process.

Attachment	Size
PDF	1.35 MB

Architecting for Artificial Intelligence with Emerging Nanotechnology

Artificial Intelligence is becoming ubiquitous in products and services that we use daily. Although the domain of AI has seen substantial improvements over recent years, its effectiveness is limited by the capabilities of current computing technology. Recently, there have been several architectural innovations for AI using emerging nanotechnology. These architectures implement mathematical computations of AI with circuits that utilize physical behavior of nanodevices purpose-built for such computations. This approach leads to a much greater efficiency vs.

Attachment	Size
PDF (In Press)	1.32 MB

A Wafer-scale Manufacturing Pathway for Fine-grained Vertical 3D-IC Technology

Three-dimensional integrated circuits (3D-ICs) provide a feasible path for scaling CMOS technology in the foreseeable future. IMEC and IRDS roadmaps project that 3D integration is a key avenue for the IC industry beyond 2024. They project that some form of 3D-IC technology based on nanosheets/nanowires is likely to become mainstream soon.

Attachment	Size
PDF	1.06 MB

Circuit Design Steps for Nano-Crossbar Arrays: Area-Delay-Power Optimization with Fault Tolerance

Nano-crossbar arrays have emerged to achieve high performance computing beyond the limits of current CMOS. They offer area and power efficiency in courtesy of their easyto-fabricate and dense physical

Attachment	Size
PDF	1.8 MB

SkyNet: Memristor-based 3D IC for Artificial Neural Networks

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.

Attachment	Size
PDF	1.33 MB

Fine-Grained 3D Reconfigurable Computing Fabric with RRAM

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.

Attachment	Size
PDF	368.41 KB

A 14nm FinFET transistor-level 3D partitioning design to enable high-performance and low-cost monolithic 3D IC

Monolithic 3D IC (M3D) shows degradation in performance compared to 2D IC due to the restricted thermal budget during fabrication of sequential device layers. A transistor-level (TR-L) partitioning design is used in M3D to mitigate this degradation. Silicon validated 14nm FinFET data and models are used in a device-to-system evaluation to compare the TR-L partitioned M3D’s (TR-L M3D) performance against the conventional gate-level (G-L) partitioned M3D’s performance as well as standard 2D IC.

Attachment	Size
PDF	1.13 MB

Structure Discovery for Gene Expression Networks with Emerging Stochastic Hardware

Gene Expression Networks (GENs) attempt to model how genetic information stored in the DNA (Genotype) results in the synthesis of proteins, and consequently, the physical traits of an organism (Phenotype). Deciphering GENs plays an important role in a wide range of applications from genetic studies of the origins of life to personalized healthcare. Probabilistic graphical models such as Bayesian Networks (BNs) are used to perform learning and inference of GENs from genetic data.

Attachment	Size
PDF	534.29 KB

Magneto-electric Approximate Computational Circuits for Bayesian Inference

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.

Attachment	Size
PDF	986.8 KB

Skybridge-3D-CMOS: A Fine-Grained 3D CMOS Integrated Circuit Technology

Parallel and monolithic 3D integration directions realize 3D integrated circuits (ICs) by utilizing layer-by-layer implementations, with each functional layer being composed in 2D. In contrast, vertically-composed 3D CMOS has eluded us likely due to the seemingly insurmountable requirement of highly customized complex routing and regional 3D doping to form and connect CMOS pull-up and pull-down networks in 3D. In the current layer-by-layer directions, routing can be worse than 2D CMOS because of the limited pin access.

Attachment	Size
PDF	1.58 MB

Nanoarchitecture/Devices/Circuits