Skybridge-3D-CMOS: A Fine-Grained Vertical 3D-CMOS Technology Paving New Direction for 3D IC

2D CMOS integrated circuit (IC) technology scaling faces severe challenges that result from device scaling limitations, interconnect bottleneck that dominates power and performance, etc. 3D ICs with die-die and layer-layer stacking using Through Silicon Vias (TSVs) and Monolithic Inter-layer Vias (MIVs) have been explored in recent years to generate circuits with considerable interconnect saving for continuing technology scaling. However, these 3D IC technologies still rely on conventional 2D CMOS’s device, circuit and interconnect mindset showing only incremental benefits while adding new challenges reliability issues, robustness of power delivery network design and short-channel effects as technology node scaling. Skybridge-3D-CMOS (S3DC) is a fine-grained 3D IC fabric that uses vertically-stacked gates and 3D interconnections composed on vertical nanowires to yield orders of magnitude benefits over 2D ICs. This 3D fabric fully uses the vertical dimension instead of relying on a multi-layered 2D mindset. Its core fabric aspects including device, circuit-style, interconnect and heat-extraction components are co-architected considering the major challenges in 3D IC technology. In S3DC, the 3D interconnections provide greater routing capacity in both vertical and horizontal directions compared to conventional 3D ICs, which eliminates the routability issue in conventional 3D IC technology while enabling ultra-high density design and significant benefits over 2D. Also, the improved vertical routing capacity in S3DC is beneficial for achieving robust and high-density power delivery network (PDN) design while conventional 3D IC has design issues in PDN design due to limited routing resource in vertical direction. Additionally, the 3D gate-all-around transistor incorporating with 3D interconnect in S3DC enables significant SRAM design benefits and good tolerance of process variation compared to conventional 3D IC technology as well as 2D CMOS. The transistor-level (TR-L) monolithic 3D IC (M3D) is the state-of-the-art monolithic 3D technology which shows better benefits than other M3D approaches as well as the TSV-based 3D IC approach. The S3DC is evaluated in large-scale benchmark circuits with comparison to TR-L M3D as well as 2D CMOS. Skybridge yields up to 3x lower power against 2D with no routing congestion in benchmark circuits while TR-L M3D only has up-to 22% power saving with severe routing congestions in the design. The PDN design in S3DC show

Physical design methodologies for monolithic 3D ICs

The objective of this research is to develop physical design methodologies for monolithic 3D ICs and use them to evaluate the improvements in the power-performance envelope offered over 2D ICs. In addition, design-for-test (DfT) techniques essential for the adoption of shorter term through-silicon-via (TSV) based 3D ICs are explored. Testing of TSV-based 3D ICs is one of the last challenges facing their commercialization. First, a pre-bond testable 3D scan chain construction technique is developed. Next, a transition-delay-fault test architecture is presented, along with a study on how to mitigate IR-drop. Finally, to facilitate partitioning, a quick and accurate framework for test-TSV estimation is developed. Block-level monolithic 3D ICs will be the first to emerge, as significant IP can be reused. However, no physical design flows exist, and hence a monolithic 3D floorplanning framework is developed. Next, inter-tier performance differences that arise due to the not yet mature fabrication process are investigated and modeled. Finally, an inter-tier performance-difference aware floorplanner is presented, and it is demonstrated that high quality 3D floorplans are achievable even under these inter-tier differences. Monolithic 3D offers sufficient integration density to place individual gates in three dimensions and connect them together. However, no tools or techniques exist that can take advantage of the high integration density offered. Therefore, a gate-level framework that leverages existing 2D ICs tools is presented. This framework also provides congestion modeling and produces results that minimize routing congestion. Next, this framework is extended to commercial 2D IC tools, so that steps such as timing optimization and clock tree synthesis can be applied. Finally, a voltage-drop-aware partitioning technique is presented that can alleviate IR-drop issues, without any impact on the performance or maximum operating temperature of the chip.Ph.D

SPRING: A Sparsity-Aware Reduced-Precision Monolithic 3D CNN Accelerator Architecture for Training and Inference

CNNs outperform traditional machine learning algorithms across a wide range of applications. However, their computational complexity makes it necessary to design efficient hardware accelerators. Most CNN accelerators focus on exploring dataflow styles that exploit computational parallelism. However, potential performance speedup from sparsity has not been adequately addressed. The computation and memory footprint of CNNs can be significantly reduced if sparsity is exploited in network evaluations. To take advantage of sparsity, some accelerator designs explore sparsity encoding and evaluation on CNN accelerators. However, sparsity encoding is just performed on activation or weight and only in inference. It has been shown that activation and weight also have high sparsity levels during training. Hence, sparsity-aware computation should also be considered in training. To further improve performance and energy efficiency, some accelerators evaluate CNNs with limited precision. However, this is limited to the inference since reduced precision sacrifices network accuracy if used in training. In addition, CNN evaluation is usually memory-intensive, especially in training. In this paper, we propose SPRING, a SParsity-aware Reduced-precision Monolithic 3D CNN accelerator for trainING and inference. SPRING supports both CNN training and inference. It uses a binary mask scheme to encode sparsities in activation and weight. It uses the stochastic rounding algorithm to train CNNs with reduced precision without accuracy loss. To alleviate the memory bottleneck in CNN evaluation, especially in training, SPRING uses an efficient monolithic 3D NVM interface to increase memory bandwidth. Compared to GTX 1080 Ti, SPRING achieves 15.6X, 4.2X and 66.0X improvements in performance, power reduction, and energy efficiency, respectively, for CNN training, and 15.5X, 4.5X and 69.1X improvements for inference

A Holistic Solution for Reliability of 3D Parallel Systems

As device scaling slows down, emerging technologies such as 3D integration and carbon nanotube field-effect transistors are among the most promising solutions to increase device density and performance. These emerging technologies offer shorter interconnects, higher performance, and lower power. However, higher levels of operating temperatures and current densities project significantly higher failure rates. Moreover, due to the infancy of the manufacturing process, high variation, and defect densities, chip designers are not encouraged to consider these emerging technologies as a stand-alone replacement for Silicon-based transistors. The goal of this dissertation is to introduce new architectural and circuit techniques that can work around high-fault rates in the emerging 3D technologies, improving performance and reliability comparable to Silicon. We propose a new holistic approach to the reliability problem that addresses the necessary aspects of an effective solution such as detection, diagnosis, repair, and prevention synergically for a practical solution. By leveraging 3D fabric layouts, it proposes the underlying architecture to efficiently repair the system in the presence of faults. This thesis presents a fault detection scheme by re-executing instructions on idle identical units that distinguishes between transient and permanent faults while localizing it to the granularity of a pipeline stage. Furthermore, with the use of a dynamic and adaptive reconfiguration policy based on activity factors and temperature variation, we propose a framework that delivers a significant improvement in lifetime management to prevent faults due to aging. Finally, a design framework that can be used for large-scale chip production while mitigating yield and variation failures to bring up Carbon Nano Tube-based technology is presented. The proposed framework is capable of efficiently supporting high-variation technologies by providing protection against manufacturing defects at different granularities: module and pipeline-stage levels.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/168118/1/javadb_1.pd

Modeling and Design Techniques for 3-D ICs under Process, Voltage, and Temperature Variations

Three-dimensional (3-D) integration is a promising solution to further enhance the density and performance of modern integrated circuits (ICs). In 3-D ICs, multiple dies (tiers or planes) are vertically stacked. These dies can be designed and fabricated separately. In addition, these dies can be fabricated in different technologies. The effect of different sources of variations on 3-D circuits, consequently, differ from 2-D ICs. As technology scales, these variations significantly affect the performance of circuits. Therefore, it is increasingly important to accurately and efficiently model different sources of variations in 3-D ICs. The process, voltage, and temperature variations in 3-D ICs are investigated in this dissertation. Related modeling and design techniques are proposed to design a robust 3-D IC. Process variations in 3-D ICs are first analyzed. The effect of process variations on synchronization and 3-D clock distribution networks, is carefully studied. A novel statistical model is proposed to describe the timing variation in 3-D clock distribution networks caused by process variations. Based on this model, different topologies of 3-D clock distribution networks are compared in terms of skew variation. A set of guidelines is proposed to design 3-D clock distribution networks with low clock uncertainty. Voltage variations are described by power supply noise. Power supply noise in 3-D ICs is investigated considering different characteristics of potential 3-D power grids in this thesis. A new algorithm is developed to fast analyze the steady-state IR-drop in 3-D power grids. The first droop of power supply noise, also called resonant supply noise, is usually the deepest voltage drop in power distribution networks. The effect of resonant supply noise on 3-D clock distribution networks is investigated. The combined effect of process variations and power supply noise is modeled by skitter consisting of both skew and jitter. A novel statistical model of skitter is proposed. Based on this proposed model and simulation results, a set of guidelines has been proposed to mitigate the negative effect of process and voltage variations on 3-D clock distribution networks. Thermal issues in 3-D ICs are considered by carefully modeling thermal through silicon vias (TTSVs) in this dissertation. TTSVs are vertical vias which do not carry signals, dedicated to facilitate the propagation of heat to reduce the temperature of 3-D ICs. Two analytic models are proposed to describe the heat transfer in 3-D circuits related to TTSVs herein, providing proper closed-form expressions for the thermal resistance of the TTSVs. The effect of different physical and geometric parameters of TTSVs on the temperature of 3-D ICs is analyzed. The proposed models can be used to fast and accurately estimate the temperature to avoid the overuse of TTSVs occupying a large portion of area. A set of models and design techniques is proposed in this dissertation to describe and mitigate the deleterious effects of process, voltage, and temperature variations in 3-D ICs. Due to the continuous shrink in the feature size of transistors, the large number of devices within one circuit, and the high operating frequency, the effect of these variations on the performance of 3-D ICs becomes increasingly significant. Accurately and efficiently estimating and controlling these variations are, consequently, critical tasks for the design of 3-D ICs