11588495
SRAM Cell Optimization for Ultra-Low Power Standby
This paper proposes a comprehensive SRAM cell optimization scheme that minimizes leakage power under ultra-low standby supply voltage (VDD). The theoretical limit of data retention voltage (DRV), the minimum VDD that preserves the states of a memory cell, was derived to be 50 mV for an industrial 90 nm technology. A DRV design model was developed on parameters including body bias, sizing, and channel length. A test chip was implemented and measured to attain DRV sensitivities to key design parameters. Based on this, a low-leakage SRAM cell design methodology is derived and the feasibility of a 270 mV standby VDD was demonstrated, including a safety margin of 100 mV. As a result, the SRAM leakage power was reduced by 97%.
10919497
SRAM leakage suppression by minimizing standby supply voltage
Suppressing the leakage current in memories is critical in low-power design. By reducing the standby supply voltage (V/sub DD/) to its limit, which is the data retention voltage (DRV), leakage power can be substantially reduced. This paper explores how low DRV can be in a standard low leakage SRAM module and analyzes how DRV is affected by parameters such as process variations, chip temperature, and transistor sizing. An analytical model for DRV as a function of process and design parameters is presented, and forms the basis for further design space explorations. This model is verified using simulations as well as measurements from a 4 kB SRAM chip in a 0.13 /spl mu/m technology. It is demonstrated that an SRAM cell state can be preserved at sub-300 mV standby VDD, with more than 90% leakage power savings.
6475869
Modeling and minimization of PMOS NBTI effect for robust nanometer design
Negative bias temperature instability (NBTI) has become the dominant reliability concern for nanoscale PMOS transistors. In this paper, a predictive model is developed for the degradation of NBTI in both static and dynamic operations. Model scalability and generality are comprehensively verified with experimental data over a wide range of process and bias conditions. By implementing the new model into SPICE for an industrial 90nm technology, key insights are obtained for the development of robust design solutions: (1) the most effective techniques to mitigate the NBTI degradation are VDD tuning, PMOS sizing, and reducing the duty cycle; (2) an optimal VDD exists to minimize the degradation of circuit performance; (3) tuning gate length or the switching frequency has little impact on the NBTI effect; (4) a new switching scenario is identified for worst case timing analysis during NBTI stress
27267454
Optimization of loss-balanced multicast in all-optical WDM networks
In wavelength-division multiplexing (WDM) optical networks, multicast is implemented by constructing a light-forest, which is a set of light-trees with each light-tree rooted from the multicast source and terminated at a partition subset of the destination nodes. Multicast routing scenario has considerable impact on the quality of optical signal received at each destination. To guarantee the fairness of signal quality at different destinations in a multicast session, it is desirable to construct a loss-balanced light-forest to deliver the multicast traffic. A loss-balanced light-forest is composed of a set of light-trees bounded in size (number of destinations per multicast tree), in size variation (difference in the number of destinations among different multicast trees), and in dimension (maximum source-to-destination distance on each multicast tree). This paper investigates the multicast routing and wavelength assignment (MC-RWA) problem under the loss-balance constraint. The problem is formulated as an optimization model using integer linear programming (ILP). Numerical solutions to the optimization model can supply useful performance benchmarks for loss-balance-constrained optical multicast in WDM networks.
13313549
Modeling of intra-die process variations for accurate analysis and optimization of nano-scale circuits
This paper proposes the use of Karhunen-Loeve expansion (KLE) for accurate and efficient modeling of intra-die correlations in the semiconductor manufacturing process. We demonstrate that the KLE provides a significantly more accurate representation, of the underlying stochastic process compared to the traditional approach of dividing the layout into grids and applying principal component analysis (PCA). By comparing the results of leakage analysis using both KLE and the existing approaches, we show that using KLE can provide up to 4-5times reduction in the variability space (number of random variables) while maintaining the same accuracy. We also propose an efficient leakage minimization algorithm that maximizes the leakage yield while satisfying probabilistic constraints on the delay
1446657
Fast Statistical Circuit Analysis with Finite-Point Based Transistor Model
A new approach of transistor modeling is developed for fast statistical circuit simulation in the presence of variations. For both I-V and C-V characteristics of a transistor, finite data points are identified by their physical meaning; the impact of process and design variations is embedded into these points as closed-form expressions. Then, the entire I-V and C-V are extrapolated using polynomial formulas. This novel approach significantly enhances the simulation speed with sufficient accuracy. The model is implemented in Verilog-A at 65nm node. Compared to simulations with the BSIM model, the computation time can be reduced by 7times in transient analysis and 9times in Monte-Carlo simulations
13444952
Expressive speech-driven facial animation
Speech-driven facial motion synthesis is a well explored research topic. However, little has been done to model expressive visual behavior during speech. We address this issue using a machine learning approach that relies on a database of speech-related high-fidelity facial motions. From this training set, we derive a generative model of expressive facial motion that incorporates emotion control, while maintaining accurate lip-synching. The emotional content of the input speech can be manually specified by the user or automatically extracted from the audio signal using a Support Vector Machine classifier.
2266938
Cooperative Mobile Robotics: Antecedents and Directions
There has been increased research interest in systems composed of multiple autonomous mobile robots exhibiting cooperative behavior. Groups of mobile robots are constructed, with an aim to studying such issues as group architecture, resource conflict, origin of cooperation, learning, and geometric problems. As yet, few applications of cooperative robotics have been reported, and supporting theory is still in its formative stages. In this paper, we give a critical survey of existing works and discuss open problems in this field, emphasizing the various theoretical issues that arise in the study of cooperative robotics. We describe the intellectual heritages that have guided early research, as well as possible additions to the set of existing motivations.