M[pi]log, Macromodeling via parametric identification of logic gates

This paper addresses the development of computational models of digital integrated circuit input and output buffers via the identification of nonlinear parametric models. The obtained models run in standard circuit simulation environments, offer improved accuracy and good numerical efficiency, and do not disclose information on the structure of the modeled devices. The paper reviews the basics of the parametric identification approach and illustrates its most recent extensions to handle temperature and supply voltage variations as well as power supply ports and tristate devices

IC design for reliability

textAs the feature size of integrated circuits goes down to the nanometer scale, transient and permanent reliability issues are becoming a significant concern for circuit designers. Traditionally, the reliability issues were mostly handled at the device level as a device engineering problem. However, the increasing severity of reliability challenges and higher error rates due to transient upsets favor higher-level design for reliability (DFR). In this work, we develop several methods for DFR at the circuit level. A major source of transient errors is the single event upset (SEU). SEUs are caused by high-energy particles present in the cosmic rays or emitted by radioactive contaminants in the chip packaging materials. When these particles hit a N+/P+ depletion region of an MOS transistor, they may generate a temporary logic fault. Depending on where the MOS transistor is located and what state the circuit is at, an SEU may result in a circuit-level error. We analyze SEUs both in combinational logic and memories (SRAM). For combinational logic circuit, we propose FASER, a Fast Analysis tool of Soft ERror susceptibility for cell-based designs. The efficiency of FASER is achieved through its static and vector-less nature. In order to evaluate the impact of SEU on SRAM, a theory for estimating dynamic noise margins is developed analytically. The results allow predicting the transient error susceptibility of an SRAM cell using a closedform expression. Among the many permanent failure mechanisms that include time-dependent oxide breakdown (TDDB), electro-migration (EM), hot carrier effect (HCE), and negative bias temperature instability (NBTI), NBTI has recently become important. Therefore, the main focus of our work is NBTI. NBTI occurs when the gate of PMOS is negatively biased. The voltage stress across the gate generates interface traps, which degrade the threshold voltage of PMOS. The degraded PMOS may eventually fail to meet timing requirement and cause functional errors. NBTI becomes severe at elevated temperatures. In this dissertation, we propose a NBTI degradation model that takes into account the temperature variation on the chip and gives the accurate estimation of the degraded threshold voltage. In order to account for the degradation of devices, traditional design methods add guard-bands to ensure that the circuit will function properly during its lifetime. However, the worst-case based guard-bands lead to significant penalty in performance. In this dissertation, we propose an effective macromodel-based reliability tracking and management framework, based on a hybrid network of on-chip sensors, consisting of temperature sensors and ring oscillators. The model is concerned specifically with NBTIinduced transistor aging. The key feature of our work, in contrast to the traditional tracking techniques that rely solely on direct measurement of the increase of threshold voltage or circuit delay, is an explicit macromodel which maps operating temperature to circuit degradation (the increase of circuit delay). The macromodel allows for costeffective tracking of reliability using temperature sensors and is also essential for enabling the control loop of the reliability management system. The developed methods improve the over-conservatism of the device-level, worstcase reliability estimation techniques. As the severity of reliability challenges continue to grow with technology scaling, it will become more important for circuit designers/CAD tools to be equipped with the developed methods.Electrical and Computer Engineerin

Macromodelling and its Applications to Signal and Power Integrity

Presented at the MCG RF Intel Colloquium, Munich, Germany, October 8, 201

Modeling Emerging Semiconductor Devices for Circuit Simulation

Circuit simulation is an indispensable part of modern IC design. The significant cost of fabrication has driven researchers to verify the chip functionality through simulation before submitting the design for final fabrication. With the impending end of Moore’s Law, researchers all over the world are looking for new devices with enhanced functionality. A plethora of promising emerging devices has been proposed in recent years. In order to leverage the full potential of such devices, circuit designers need fast, reliable models for SPICE simulation to explore different applications. Most of these new devices have complex underlying physical mechanism rendering the model development an extremely challenging task. For the models to be of practical use, they have to enable fast and accurate simulation that rules out the possibility of numerically solving a system of partial differential equations to arrive at a solution. In this chapter, we show how different modeling approaches can be used to simulate three emerging semiconductor devices namely, silicon- on- insulator four gate transistor(G4FET), perimeter gated single photon avalanche diode (PG-SPAD) and insulator-metal transistor (IMT) device with volatile memristance. All the models have been verified against experimental /TCAD data and implemented in commercial circuit simulator

Delay Extraction based Macromodeling with Parallel Processing for Efficient Simulation of High Speed Distributed Networks

This thesis attempts to address the computational demands of accurate modeling of high speed distributed networks such as interconnect networks and power distribution networks. In order to do so, two different approaches towards modeling of high speed distributed networks are considered. One approach deals with cases where the physical characteristics of the network are not known and the network is characterized by its frequency domain tabulated data. Such examples include long interconnect networks described by their Y parameter data. For this class of problems, a novel delay extraction based IFFT algorithm has been developed for accurate transient response simulation. The other modeling approach is based on a detailed knowledge of the physical and electrical characteristics of the network and assuming a quasi transverse mode of propagation of the electromagnetic wave through the network. Such problems may include two dimensional (2D) and three dimensional (3D) power distribution networks with known geometry and materials. For this class of problem, a delay extraction based macromodeling approaches is proposed which has been found to be able to capture the distributed effects of the network resulting in more compact and accurate simulation compared to the state-of-the-art quasi-static lumped models. Furthermore, waveform relaxation based algorithms for parallel simulations of large interconnect networks and 2D power distribution networks is also presented. A key contribution of this body of work is the identification of naturally parallelizable and convergent iterative techniques that can divide the computational costs of solving such large macromodels over a multi-core hardware