Design, Fabrication, and Run-time Strategies for Hardware-Assisted Security

Today, electronic computing devices are critically involved in our daily lives, basic infrastructure, and national defense systems. With the growing number of threats against them, hardware-based security features offer the best chance for building secure and trustworthy cyber systems. In this dissertation, we investigate ways of making hardware-based security into a reality with primary focus on two areas: Hardware Trojan Detection and Physically Unclonable Functions (PUFs). Hardware Trojans are malicious modifications made to original IC designs or layouts that can jeopardize the integrity of hardware and software platforms. Since most modern systems critically depend on ICs, detection of hardware Trojans has garnered significant interest in academia, industry, as well as governmental agencies. The majority of existing detection schemes focus on test-time because of the limited hardware resources available at run-time. In this dissertation, we explore innovative run-time solutions that utilize on-chip thermal sensor measurements and fundamental estimation/detection theory to expose changes in IC power/thermal profile caused by Trojan activation. The proposed solutions are low overhead and also generalizable to many other sensing modalities and problem instances. Simulation results using state-of-the-art tools on publicly available Trojan benchmarks verify that our approaches can detect Trojans quickly and with few false positives. Physically Unclonable Functions (PUFs) are circuits that rely on IC fabrication variations to generate unique signatures for various security applications such as IC authentication, anti-counterfeiting, cryptographic key generation, and tamper resistance. While the existence of variations has been well exploited in PUF design, knowledge of exactly how variations come into existence has largely been ignored. Yet, for several decades the Design-for-Manufacturability (DFM) community has actually investigated the fundamental sources of these variations. Furthermore, since manufacturing variations are often harmful to IC yield, the existing DFM tools have been geared towards suppressing them (counter-intuitive for PUFs). In this dissertation, we make several improvements over current state-of-the-art work in PUFs. First, our approaches exploit existing DFM models to improve PUFs at physical layout and mask generation levels. Second, our proposed algorithms reverse the role of standard DFM tools and extend them towards improving PUF quality without harming non-PUF portions of the IC. Finally, since our approaches occur after design and before fabrication, they are applicable to all types of PUFs and have little overhead in terms of area, power, etc. The innovative and unconventional techniques presented in this dissertation should act as important building blocks for future work in cyber security

FOCSI: A new layout regularity metric

Technical ReportDigital CMOS Integrated Circuits (ICs) suffer from serious layout features printability issues associated to the lithography manufacturing process. Regular layout designs are emerging as alternative solutions to reduce these ICs systematic subwavelength lithography failures. However, there is no metric to evaluate and compare the layout regularity of those regular designs. In this paper we propose a new layout regularity metric called Fixed Origin Corner Square Inspection (FOCSI). FOCSI allows the comparison and quantification of designs in terms of regularity and for any given degree of granularity. When FOCSI is oriented to the evaluation of regularity while applying Lithography Enhancement Techniques, it comprehends layout layers measurements considering the optical interaction length and combines them to obtain the complete layout regularity measure. Examples are provided for 32-bit adders in the 90 nm technology node for the Standard Cell approach and for Via-Configurable Transistor Array regular designs. We show how layouts can be sorted accurately even if their degree of regularity is similar.Preprin

Layout regularity metric as a fast indicator of process variations

Integrated circuits design faces increasing challenge as we scale down due to the increase of the effect of sensitivity to process variations. Systematic variations induced by different steps in the lithography process affect both parametric and functional yields of the designs. These variations are known, themselves, to be affected by layout topologies. Design for Manufacturability (DFM) aims at defining techniques that mitigate variations and improve yield. Layout regularity is one of the trending techniques suggested by DFM to mitigate process variations effect. There are several solutions to create regular designs, like restricted design rules and regular fabrics. These regular solutions raised the need for a regularity metric. Metrics in literature are insufficient for different reasons; either because they are qualitative or computationally intensive. Furthermore, there is no study relating either lithography or electrical variations to layout regularity. In this work, layout regularity is studied in details and a new geometrical-based layout regularity metric is derived. This metric is verified against lithographic simulations and shows good correlation. Calculation of the metric takes only few minutes on 1mm x 1mm design, which is considered fast compared to the time taken by simulations. This makes it a good candidate for pre-processing the layout data and selecting certain areas of interest for lithographic simulations for faster throughput. The layout regularity metric is also compared against a model that measures electrical variations due to systematic lithographic variations. The validity of using the regularity metric to flag circuits that have high variability using the developed electrical variations model is shown. The regularity metric results compared to the electrical variability model results show matching percentage that can reach 80%, which means that this metric can be used as a fast indicator of designs more susceptible to lithography and hence electrical variations

Design for Manufacturing in IC Fabrication: Mask Cost, Circuit Performance and Convergence

Ph.DDOCTOR OF PHILOSOPH

Analog layout design automation: ILP-based analog routers

The shrinking design window and high parasitic sensitivity in the advanced technology have imposed special challenges on the analog and radio frequency (RF) integrated circuit design. In this thesis, we propose a new methodology to address such a deficiency based on integer linear programming (ILP) but without compromising the capability of handling any special constraints for the analog routing problems. Distinct from the conventional methods, our algorithm utilizes adaptive resolutions for various routing regions. For a more congested region, a routing grid with higher resolution is employed, whereas a lower-resolution grid is adopted to a less crowded routing region. Moreover, we strengthen its speciality in handling interconnect width control so as to route the electrical nets based on analog constraints while considering proper interconnect width to address the acute interconnect parasitics, mismatch minimization, and electromigration effects simultaneously. In addition, to tackle the performance degradation due to layout dependent effects (LDEs) and take advantage of optical proximity correction (OPC) for resolution enhancement of subwavelength lithography, in this thesis we have also proposed an innovative LDE-aware analog layout migration scheme, which is equipped with our special routing methodology. The LDE constraints are first identified with aid of a special sensitivity analysis and then satisfied during the layout migration process. Afterwards the electrical nets are routed by an extended OPC-inclusive ILP-based analog router to improve the final layout image fidelity while the routability and analog constraints are respected in the meantime. The experimental results demonstrate the effectiveness and efficiency of our proposed methods in terms of both circuit performance and image quality compared to the previous works

AI/ML Algorithms and Applications in VLSI Design and Technology

An evident challenge ahead for the integrated circuit (IC) industry in the nanometer regime is the investigation and development of methods that can reduce the design complexity ensuing from growing process variations and curtail the turnaround time of chip manufacturing. Conventional methodologies employed for such tasks are largely manual; thus, time-consuming and resource-intensive. In contrast, the unique learning strategies of artificial intelligence (AI) provide numerous exciting automated approaches for handling complex and data-intensive tasks in very-large-scale integration (VLSI) design and testing. Employing AI and machine learning (ML) algorithms in VLSI design and manufacturing reduces the time and effort for understanding and processing the data within and across different abstraction levels via automated learning algorithms. It, in turn, improves the IC yield and reduces the manufacturing turnaround time. This paper thoroughly reviews the AI/ML automated approaches introduced in the past towards VLSI design and manufacturing. Moreover, we discuss the scope of AI/ML applications in the future at various abstraction levels to revolutionize the field of VLSI design, aiming for high-speed, highly intelligent, and efficient implementations

DFM Techniques for the Detection and Mitigation of Hotspots in Nanometer Technology

With the continuous scaling down of dimensions in advanced technology nodes, process variations are getting worse for each new node. Process variations have a large influence on the quality and yield of the designed and manufactured circuits. There is a growing need for fast and efficient techniques to characterize and mitigate the effects of different sources of process variations on the design's performance and yield. In this thesis we have studied the various sources of systematic process variations and their effects on the circuit, and the various methodologies to combat systematic process variation in the design space. We developed abstract and accurate process variability models, that would model systematic intra-die variations. The models convert the variation in process into variation in electrical parameters of devices and hence variation in circuit performance (timing and leakage) without the need for circuit simulation. And as the analysis and mitigation techniques are studied in different levels of the design ow, we proposed a flow for combating the systematic process variation in nano-meter CMOS technology. By calculating the effects of variability on the electrical performance of circuits we can gauge the importance of the accurate analysis and model-driven corrections. We presented an automated framework that allows the integration of circuit analysis with process variability modeling to optimize the computer intense process simulation steps and optimize the usage of variation mitigation techniques. And we used the results obtained from using this framework to develop a relation between layout regularity and resilience of the devices to process variation. We used these findings to develop a novel technique for fast detection of critical failures (hotspots) resulting from process variation. We showed that our approach is superior to other published techniques in both accuracy and predictability. Finally, we presented an automated method for fixing the lithography hotspots. Our method showed success rate of 99% in fixing hotspots

Lithography aware physical design and layout optimization for manufacturability

textAs technology continues to scale down, semiconductor manufacturing with 193nm lithography is greatly challenging because the required half pitch size is beyond the resolution limit. In order to bridge the gap between design requirements and manufacturing limitations, various resolution enhancement techniques have been proposed to avoid potentially problematic patterns and to improve product yield. In addition, co-optimization between design performance and manufacturability can further provide flexible and significant yield improvement, and it has become necessary for advanced technology nodes. This dissertation presents the methodologies to consider the lithography impact in different design stages to improve layout manufacturability. Double Patterning Lithography (DPL) has been a promising solution for sub-22nm node volume production. Among DPL techniques, self-aligned double patterning (SADP) provides good overlay controllability when two masks are not aligned perfectly. However, SADP process places several limitations on design flexibility and still exists many challenges in physical design stages. Starting from the early design stage, we analyze the standard cell designs and construct a set of SADP-aware cell placement candidates, and show that placement legalization based on this SADP awareness information can effectively resolve DPL conflicts. In the detailed routing stage, we propose a new routing cost formulation based on SADP-compliant routing guidelines, and achieve routing and layout decomposition simultaneously. In the case that limited routing perturbation is allowed, we propose a post-routing flow based on lithography simulation and lithography-aware design rules. Both routing methods, one in detailed routing stage and one in post routing stage, reduce DPL conflicts/violations significantly with negligible wire length impact. In the layout decomposition stage, layout modification is restricted and thus the manufacturability is even harder to guaranteed. By taking the advantage of complementary lithography, we present a new layout decomposition approach with e-beam cutting, which optimizes SADP overlay error and e-beam lithography throughput simultaneously. After the mask layout is defined, optical proximity correction (OPC) is one of the resolution enhancement techniques that is commonly required to compensate the image distortion from the lithography process. We propose an inverse lithography technique to solve the OPC problem considering design target and process window co-optimization. Our mask optimization is pixel based and thus can enable better contour fidelity. In the final physical verification stage, a complex and time-consuming lithography simulation needs to be performed to identify faulty patterns. We provide a classification method based on support vector machine and principle component analysis that detects lithographic hotspots efficiently and accurately.Electrical and Computer Engineerin

Performance-Based Optical Proximity Correction

Ph.DDOCTOR OF PHILOSOPH