Michael B. Steer

The number of design rules is drastically increasing as technology nodes scale down. This increase makes the creation of the design rule decks and the checking process complex and time-consuming. This work presents a design rule checking approach using deep learning. The core of the work consists of a framework to generate convolutional neural networks and a parametrized synthetic data generator for training. The models incorporate incremental transfer learning to reduce the training time when adding new rules. The results show that we can capture most of the checks from a design kit rule manual with less than 1% error and up to 7.5x faster than traditional design rule checkers.

The major objective of this research is to model the response of heterogeneous systems subjected to electromagnetic excitation that result in the mechanical dynamic behavior of metallic objects embedded in different soil systems. In this investigation, we characterized how several factors affect the coupled response of the heterogeneous system. One of the factors affecting the

Magnetic materials and components play a critical role in the technology we use in our daily lives. Many things, from electric motors to data storage, radar, and communication systems, rely on the properties of magnetic materials. The inherent physics of magnetic materials provides us with signal processing and control that either cannot be replicated or is difficult to replicate with electric-field-based devices alone.

Military communications networks can leverage much of the millimeter-wave (mm-wave) technology being investigated and developed for 5G cellular, but require special attention to the unique military requirements. This paper highlights the special communications requirements of specific military local area networks and discusses how higher band mm-wave technology can contribute to high data rates and simultaneously achieve covertness. Adaptive tuning for varying atmospheric absorption meets the military requirements for quickly adjusting covert communication zones to accommodate potentially rapid movements of network nodes, dynamic output power constraints, and changing environmental conditions.

The physical mechanism of the experimentally observed dependence of passive intermodulation (PIM) in printed circuits on conductor surface roughness is studied. It is shown that electrothermal (ET) nonlinearity, arising due to heating of imperfect conductors by high-power carriers in a multicarrier system, is correlated with conductor surface roughness and has a unique signature. Carriers modulate the conductor resistivity, skin depth, and surface impedance which generate PIM products. The detailed analysis demonstrates that ET-PIM depends on the conductor resistivity, shape, and roughness profile and also on the electric and thermal properties of the substrate. Their effects on PIM are illustrated by examples of uniform microstrip lines with different conductor and substrate materials, and periodically perturbed and meandered microstrip lines.

Microwave excitation of energetic materials can remotely incite ignition and deflagration. While this has been experimentally observed, the underlying principles are not well understood due to the complexity of analytical solutions. Further complicating understanding is the sensitivity of the effect to geometry and the difficulty of creating simulation environments representative of realistic materials. Manageable analysis requires abstractions, and here abstractions ranging from regularly arranged spheres and cubes to randomly arranged spheres, cubes, and arbitrarily shaped crystals are examined. The randomly arranged cube model provides acceptable prediction of thermal and peak electric field hotspots while having manageable computational complexity. The hotspots resulting from multiple subwavelength scattering occur inside the body of the energetic material and are localized in time and space having spans that are a few percent or less of the period and wavelength of pulsed electromagnetic excitation.

The radio signal transmitted from a vibrating antenna is modulated producing spectral content that can interfere with a nearby receiver. The additional spectral content is centered at the transmitted RF signal, and with chaotic vibrations, the spectrum has significant content beyond the fundamental frequency of vibration. Thus, the effect of vibration on co-site interference is much greater than expected. A controlled experiment using a monopole antenna driven at 900 MHz and vibrating at 150 Hz has significant RF spectral content extending to 5 kHz.

System architects traditionally use high-level models of component blocks to predict trends for various design metrics. However, with continually increasing design complexity and a confusing array of manufacturing choices, system-level design decisions cannot be made without considering physical-level details. This effect is more pronounced for 3-D integrated circuits (ICs) because it provides a plethora of physical-level design choices, such as the number of stacking layers and the type of 3-D bonding method, along with the choices provided by 2-D ICs. Thus, it is necessary for system-level flows to predict the complex interactions among system performance, power, temperature, floorplanning, process technology, computer architecture, and software/workloads. This is often called pathfinding. This paper presents a pathfinding flow that integrates SystemC transaction-level electrical and dynamic thermal simulations. The goal of this flow is to pass complex physical constraints to system architects in a convenient form. The applicability of the proposed flow is shown using an example stacking of two processor cores and L2 cache in two-tier 3-D stack.

The degraded thermal path of 3-D integrated circuits (3DICs) makes thermal analysis at the chip-scale an essential part of the design process. Performing an appropriate thermal analysis on such circuits requires a model with junction-level fidelity; however, the computational burden imposed by such a model is tremendous. In this paper, we present enhancements to two thermal modeling techniques for integrated circuits to make them applicable to 3DICs. First, we present a resistive mesh-based approach that improves on the fidelity of prior approaches by constructing a thermal model of the full structure of 3DICs, including the interconnect. Second, we introduce a method for dividing the thermal response caused by a heat load into a high fidelity “near response” and a lower fidelity “far response” in order to implement Power Blurring high definition (HD), a hierarchical thermal simulation approach based on Power Blurring that incorporates the resistive mesh-based models and allows for junction-level accuracy at the full-chip scale. The Power Blurring HD technique yields approximately three orders of magnitude of improvement in memory usage and up to six orders of magnitude of improvement in runtime for a three-tier synthetic aperture radar circuit, as compared to using a full-chip junction-scale resistive mesh-based model. Finally, measurement results are presented showing that Power Blurring high definition (HD) accurately determines the shape of the thermal profile of the 3DIC surface after a correction factor is added to adjust for a discrepancy in the absolute temperature values.