Modeling techniques and verification methodologies for substrate coupling effects in mixed-signal system-on-chip designs

The substrate noise coupling problems in today's complex mixed-signal system-on-chip (MS-SOC) brings a new set of challenges for designers. In this paper, we propose a global methodology that includes an early verification in the design flow as well as a postlayout iterative optimization to deal with substrate noise, and helps designers to achieve a first silicon-success of their chips. An improved semi-analytical modeling technique exploiting the basic behaviors of this noise is developed. This method significantly accelerates the substrate modeling, avoids the dense matrix storage, and, hence, enables the implementation of an iterative noise-immunity optimization loop working at full-chip level. The integration of the methodology in a typical mixed-signal design flow is illustrated and its successful application to achieve a single-chip integration of a transceiver is demonstrated

Solución de predicción de temperaturas usando datos de un simulador térmico

The industry of integrated circuits is experiencing a moment of fierce change. As is, the methods used in all stages implied in its design process. The present work presents a method to predict temperatures for System on Chip (SoC) chiplet part with quite simple power map and a single thermal interface material using Machine Learning (ML) and its offspring Deep Learning (DL). The SoC part is represented as a response surface of a 2D model geometry surface used for a set of experiments to determine the relevant factors for the temperature prediction. In addition to the experiment design, a deployment strategy to implement a continuous integration and deployment process to be used for the target organization is also proposed. The idea is to achieve the principle of productive ML that states that models should be constantly learning by automating new data ingestion into the training process to enhance model performance in each of the cycle updates. The project proposes a method to strengthen the established thermal processes of the target organization by using ML tools and provide an alternative to speed up thermal model analysis using new available techniques derived from ML and Deep Learning

Automated model parameter extraction for noise coupling analysis in silicon substrates

An automated method, requiring the fabrication of a small set of test structures, efficiently extracts the coefficients of Z-parameter based macromodels. The extraction approach has been validated for both heavily and lightly doped substrates and can be applied to a variety of technologies. After the parameters of a macromodel have been extracted, the model can be used to quickly and accurately calculate the equivalent substrate network connecting an arbitrary number of contacts. This automated extraction process has been integrated into the Cadence DFII environment to provide a seamless flow for substrate noise analysis.Keywords: coupling, model, substrate, nois

The impact of design techniques in the reduction of power consumption of SoCs Multimedia

Orientador: Guido Costa Souza de AraújoDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: A indústria de semicondutores sempre enfrentou fortes demandas em resolver problema de dissipação de calor e reduzir o consumo de energia em dispositivos. Esta tendência tem sido intensificada nos últimos anos com o movimento de sustentabilidade ambiental. A concepção correta de um sistema eletrônico de baixo consumo de energia é um problema de vários níveis de complexidade e exige estratégias sistemáticas na sua construção. Fora disso, a adoção de qualquer técnica de redução de energia sempre está vinculada com objetivos especiais e provoca alguns impactos no projeto. Apesar dos projetistas conheçam bem os impactos de forma qualitativa, as detalhes quantitativas ainda são incógnitas ou apenas mantidas dentro do 'know-how' das empresas. Neste trabalho, de acordo com resultados experimentais baseado num plataforma de SoC1 industrial, tentamos quantificar os impactos derivados do uso de técnicas de redução de consumo de energia. Nos concentramos em relacionar o fator de redução de energia de cada técnica aos impactos em termo de área, desempenho, esforço de implementação e verificação. Na ausência desse tipo de dados, que relacionam o esforço de engenharia com as metas de consumo de energia, incertezas e atrasos serão frequentes no cronograma de projeto. Esperamos que este tipo de orientações possam ajudar/guiar os arquitetos de projeto em selecionar as técnicas adequadas para reduzir o consumo de energia dentro do alcance de orçamento e cronograma de projetoAbstract: The semiconductor industry has always faced strong demands to solve the problem of heat dissipation and reduce the power consumption in electronic devices. This trend has been increased in recent years with the action of environmental sustainability. The correct conception of an electronic system for low power consumption is an issue with multiple levels of complexities and requires systematic approaches in its construction. However, the adoption of any technique for reducing the power consumption is always linked with some specific goals and causes some impacts on the project. Although the designers know well that these impacts can affect the design in a quality aspect, the quantitative details are still unkown or just be kept inside the company's know-how. In this work, according to the experimental results based on an industrial SoC2 platform, we try to quantify the impacts of the use of low power techniques. We will relate the power reduction factor of each technique to the impact in terms of area, performance, implementation and verification effort. In the absence of such data, which relates the engineering effort to the goals of power consumption, uncertainties and delays are frequent. We hope that such guidelines can help/guide the project architects in selecting the appropriate techniques to reduce the power consumption within the limit of budget and project scheduleMestradoCiência da ComputaçãoMestre em Ciência da Computaçã

Low power digitally controlled oscillator for IoT applications

This work is focused on the design of a Low Power CMOS DCO for IEEE 802.11ah in IoT applications. The design methodology is based on the Unified current-control model (UICM), which is a physics-based model and enables an accurate all-region model of the operation of the device. Additionally, a transformer-based resonator has been used to solve the low-quality factor issue of integrated inductors. Two digitally controlled oscillators (DCO) have been implemented to show the advantages of utilizing a transformedbased resonator and the methodology based on the UICM model. These designs aim for the operation in low voltage supply (VDD) since VDD scaling is a trend in systems-onchip (SoCs), in which the circuitry is mostly digital. Despite the degradation caused by VDD scaling, new RF and analog circuits must deliver similar performance of the older CMOS nodes. The first DCO design was a low power LC-tank DCO, implemented in 40nm bulk-CMOS. The first design presented a DCO operating at 45% of the nominal VDD without compromise the performance. By reducing the VDD below the nominal value, this DCO reduces power consumption, which is a crucial feature for IoT circuits. The main contribution of this first DCO is the reduction of VDD scaling impact on the phase-noise do the DCO. The LC-based DCO operates from 1.8 to 1.86 GHz. At the maximum frequency and 0.395V VDD, the power consumption is a mere 380 W with a phase-noise of -119.3 dBc/Hz at 1 MHz. The circuit occupies an area of 0.46mm2 in 40 nm CMOS, mostly due to the inductor. The second DCO design was a low-power transformer-based DCO design, implemented in 28nm bulk-CMOS. This second design aims for the VDD reduction to below 0.3 V. Operating in a frequency range similar to the LC-based DCO, the transformer-based DCO operated with 0.280V VDD with a power consumption of 97 W. Meanwhile, the phase-noise was -101.95 dBc/Hz at 1 MHz. Even in the worst-case scenario (i.e., slow-slow and 85oC), this second DCO was able to operate at 0.330V VDD, consuming 126 W, while it keeps a similar phase-noise performance of the typical case. The core circuit occupies an area of 0.364 mm2.Este trabalho objetiva o projeto de um DCO de baixa potência em CMOS para aplicações de IoT e aderentes ao padrão IEEE 802.11ah. A metodologia de projeto é baseada no modelo de controle de corrente unificado (UICM), que é um modelo com embasamento físico que permite uma operação precisa em todas as regiões de operação do dispositivo. Adicionalmente, é utilizado um ressonador baseado em transformador visando solucionar os problemas provenientes do baixo fator de qualidade de indutores integrados. Para destacar as melhorias obtidas com o projeto do ressonador baseado em transformador e com a metodologia baseada no modelo UICM, dois projetos de DCO são realizados. Esses projetos visam a operação com baixa tensão de alimentação (VDD), uma vez que o escalonamento do VDD é uma tendência em sistemas em chip (SoCs), em que o circuito é majoritariamente digital. Independente da degradação causada pelo escalonamento de VDD, circuitos analógicos e de RF atuais devem oferecer desempenho semelhante ao alcançado em tecnologias CMOS mais antigas. O primeiro projeto foi um DCO de baixa potência com tanque LC, implementado em tecnologia bulk-CMOS de 40nm. O primeiro projeto apresentou uma operação a 45% do VDD nominal sem comprometer o desempenho. Ao reduzir o VDD abaixo do valor nominal, este DCO reduz o consumo de energia, que é uma característica crucial para circuitos IoT. A principal contribuição deste DCO é a redução do impacto do escalonamento do VDD no ruído de fase. O DCO com tanque LC opera de 1,8 a 1,86 GHz. Na frequência máxima e com VDD de apenas 0,395V, o consumo de energia é 380 W e o ruído de fase é -119,3 dBc/Hz a 1 MHz. O circuito ocupa uma área de 0.46mm2 em processo CMOS de 40 nm. O segundo projeto foi um DCO de baixa potência baseado em transformador, implementado em tecnologia bulk- CMOS de 28nm. Este projeto visa a redução de VDD abaixo de 0,3 V. Operando em uma faixa de frequência semelhante ao primeiro DCO, o DCO baseado em transformador opera com VDD de 0,280V e com consumo de potência de 97 W. O ruído de fase foi de -101,95 dBc/Hz a 1 MHz. Mesmo no pior caso de processo, este DCO opera a um VDD de 0,330V, consumindo 126 W, com o ruído de fase semelhante ao caso típico. O circuito ocupa uma área de 0.364mm2

Smart energy management and conversion

This chapter introduced power management circuits and energy storage unit designs for sub‐1 mW low power energy harvesting technologies, including indoor light energy harvesting, thermoelectric energy harvesting and vibration energy harvesting. The solutions address several of the problems associated with energy harvesting, power management and storage issues including low voltage operation, self‐start, efficiency (conversion efficiency as well as impact of power consumption of the power management circuit itself), energy density and leakage current levels. Additionally, efforts to miniaturize and integrate magnetic parts as well as integrate discrete circuits onto silicon are outlined to offer improvements in cost, size and efficiency. Finally initial results from efforts to improve energy density of storage devices using nanomaterials are introduced

Predictive methodologies for substrate parasitic extraction and modeling in heavily doped CMOS substrates

This thesis presents an automated methodology to calibrate the substrate profile for accurate prediction of substrate parasitics using Green's function based extractors. The technique requires fabrication of only a few test structures and results in an accurate three layered approximation of a heavily doped epitaxial silicon substrate. The obtained substrate resistances are accurate to about 10% of measurements. Advantages and limitations of several common measurement techniques used to measure substrate z-parameters and resistances are discussed. A new and accurate z-parameter based macro-model has been developed that can be used up to a few GHz for P⁺ for contacts that are as close as 2μm. This enhanced model also addresses the limitations of previous models with regards to implementation aspects and ease of integration in a CAD framework. Limitations of this modeling approach have been investigated. The calibration methodology can be used along with the scalable macromodel for a qualitative pre-design and pre-layout estimation of the digital switching noise that couples though the substrate to sensitive analog/RF circuits

Digital Suppression of EMI-Induced Errors in a Baseband Acquisition Front-End including Off-the-Shelf, EMI-Sensitive Operational Amplifiers

In this paper, the susceptibility to Electromagnetic Interference (EMI) of an analog signal acquisition front-end (AFE) due to EMI distortion in opamp-based pre-conditioning amplifiers is addressed. More specifically, the possibility to correct EMI-induced errors in the digital domain by post-processing the acquired digital waveforms is discussed and experimentally demonstrated for the first time with reference to an AFE based on EMI-sensitive, off-the-shelf operational amplifiers mounted on a specific EMI test PCB. Extensive experimental characterization in the presence of continuous wave and amplitude modulated EMI reveals the superior immunity to EMI of the proposed AFE and the robustness of the approach