Influence of parasitic capacitance variations on 65 nm and 32 nm predictive technology model SRAM core-cells

The continuous improving of CMOS technology allows the realization of digital circuits and in particular static random access memories that, compared with previous technologies, contain an impressive number of transistors. The use of new production processes introduces a set of parasitic effects that gain more and more importance with the scaling down of the technology. In particular, even small variations of parasitic capacitances in CMOS devices are expected to become an additional source of faulty behaviors in future technologies. This paper analyzes and compares the effect of parasitic capacitance variations in a SRAM memory circuit realized with 65 nm and 32 nm predictive technology model

Performance Analysis of FinFET Based Inverter circuit, NAND and NOR Gate at 22nm and 14nm Node technologies.

The size of integrated devices such as PC, mobiles etc are reducing day by day with multiple operations, all of these is happening because of the scaling down the size of MOSFETs which is the main component in memory, processors and so on. As we scale down the MOSFETs to the nanometer regime the short channel effects arises which degrades the system performance and reliability. Here in this paper we describe the alternative MOSFET called FinFET which reduces the short channel effects and its performance analysis of digital applications such as inverter circuit, nand and nor gates at 22nm and 14nm node technologies. DOI: 10.17762/ijritcc2321-8169.15050

Modeling of thermally induced skew variations in clock distribution network

Clock distribution network is sensitive to large thermal gradients on the die as the performance of both clock buffers and interconnects are affected by temperature. A robust clock network design relies on the accurate analysis of clock skew subject to temperature variations. In this work, we address the problem of thermally induced clock skew modeling in nanometer CMOS technologies. The complex thermal behavior of both buffers and interconnects are taken into account. In addition, our characterization of the temperature effect on buffers and interconnects provides valuable insight to designers about the potential impact of thermal variations on clock networks. The use of industrial standard data format in the interface allows our tool to be easily integrated into existing design flow

Quantifying Near-Threshold CMOS Circuit Robustness

In order to build energy efficient digital CMOS circuits, the supply voltage must be reduced to near-threshold. Problematically, due to random parameter variation, supply scaling reduces circuit robustness to noise. Moreover, the effects of parameter variation worsen as device dimensions diminish, further reducing robustness, and making parameter variation one of the most significant hurdles to continued CMOS scaling. This paper presents a new metric to quantify circuit robustness with respect to variation and noise along with an efficient method of calculation. The method relies on the statistical analysis of standard cells and memories resulting an an extremely compact representation of robustness data. With this metric and method of calculation, circuit robustness can be included alongside energy, delay, and area during circuit design and optimization

Delay models and design guidelines for MCML gates with resistor or PMOS load

In this paper we present propagation delay models for MCML gates with resistor- or triode-PMOS-based output I–V conversion. The dependence of the parasitic capacitance of triode PMOS devices is accurately evaluated for the first time in the literature. The proposed models are able to accurately predict the propagation delay as a function of the bias current ISS in different design scenarios which require different tradeoffs between speed, area and power efficiency. The proposed models are validated against transistor level simulations referring to a 28 ​nm CMOS process showing a maximum percentage error lower than 6.5%. Based on these models, a comparative analysis is carried out and useful guidelines for the design of MCML gates are proposed

Multi-Frequency Magnonic Logic Circuits for Parallel Data Processing

We describe and analyze magnonic logic circuits enabling parallel data processing on multiple frequencies. The circuits combine bi-stable (digital) input/output elements and an analog core. The data transmission and processing within the analog part is accomplished by the spin waves, where logic 0 and 1 are encoded into the phase of the propagating wave. The latter makes it possible to utilize a number of bit carrying frequencies as independent information channels. The operation of the magnonic logic circuits is illustrated by numerical modeling. We also present the estimates on the potential functional throughput enhancement and compare it with scaled CMOS. The described multi-frequency approach offers a fundamental advantage over the transistor-based circuitry and may provide an extra dimension for the Moor's law continuation. The shortcoming and potentials issues are also discussed

Statistical modelling of nano CMOS transistors with surface potential compact model PSP

The development of a statistical compact model strategy for nano-scale CMOS transistors is presented in this thesis. Statistical variability which arises from the discreteness of charge and granularity of matter plays an important role in scaling of nano CMOS transistors especially in sub 50nm technology nodes. In order to achieve reasonable performance and yield in contemporary CMOS designs, the statistical variability that affects the circuit/system performance and yield must be accurately represented by the industry standard compact models. As a starting point, predictive 3D simulation of an ensemble of 1000 microscopically different 35nm gate length transistors is carried out to characterize the impact of statistical variability on the device characteristics. PSP, an advanced surface potential compact model that is selected as the next generation industry standard compact model, is targeted in this study. There are two challenges in development of a statistical compact model strategy. The first challenge is related to the selection of a small subset of statistical compact model parameters from the large number of compact model parameters. We propose a strategy to select 7 parameters from PSP to capture the impact of statistical variability on current-voltage characteristics. These 7 parameters are used in statistical parameter extraction with an average RMS error of less than 2.5% crossing the whole operation region of the simulated transistors. Moreover, the accuracy of statistical compact model extraction strategy in reproducing the MOSFET electrical figures of merit is studied in detail. The results of the statistical compact model extraction are used for statistical circuit simulation of a CMOS inverter under different input-output conditions and different number of statistical parameters. The second challenge in the development of statistical compact model strategy is associated with statistical generation of parameters preserving the distribution and correlation of the directly extracted parameters. By using advanced statistical methods such as principal component analysis and nonlinear power method, the accuracy of parameter generation is evaluated and compared to directly extracted parameter sets. Finally, an extension of the PSP statistical compact model strategy to different channel width/length devices is presented. The statistical trends of parameters and figures of merit versus channel width/length are characterized