Dynamic Supply and Threshold Voltage Scaling for CMOS Digital Circuits Using In-Situ Power Monitor

A generalized power tracking algorithm that minimizes power consumption of digital circuits by dynamic control of supply voltage and the body bias is proposed. A direct power monitoring scheme is proposed that does not need any replica and hence can sense total power consumed by load circuit across process, voltage, and temperature corners. Design details and performance of power monitor and tracking algorithm are examined by a simulation framework developed using UMC 90-nm CMOS triple well process. The proposed algorithm with direct power monitor achieves a power savings of 42.2% for activity of 0.02 and 22.4% for activity of 0.04. Experimental results from test chip fabricated in AMS 350 nm process shows power savings of 46.3% and 65% for load circuit operating in super threshold and near sub-threshold region, respectively. Measured resolution of power monitor is around 0.25 mV and it has a power overhead of 2.2% of die power. Issues with loop convergence and design tradeoff for power monitor are also discussed in this paper.

Effect of scaling on the non-quasi-static behaviour of the MOSFET for RF ICs

The effect of scaling (1 μm to 0.09 μm) on the non-quasi-static (NQS) behaviour of the MOSFET has been studied using process and device simulation. It is shown that under fixed gate (Vgs) and drain (Vds) bias voltages, the NQS transition frequency (fNQS) scales as 1/Leff rather than 1/L2eff due to the velocity saturation effect. However, under the practical scaling guidelines, considering the scaling of supply voltage as well, fNQS shows a turn around effect at the sub 100 nm regime. The relation between unity gain frequency (ft) and fNQS is also evaluated and it is shown that ft and fNQS have similar trends with scaling.

Dynamic Supply and Threshold Voltage Scaling for CMOS Digital Circuits Using In-Situ Power Monitor

A generalized power tracking algorithm that minimizes power consumption of digital circuits by dynamic control of supply voltage and the body bias is proposed. A direct power monitoring scheme is proposed that does not need any replica and hence can sense total power consumed by load circuit across process, voltage, and temperature corners. Design details and performance of power monitor and tracking algorithm are examined by a simulation framework developed using UMC 90-nm CMOS triple well process. The proposed algorithm with direct power monitor achieves a power savings of 42.2% for activity of 0.02 and 22.4% for activity of 0.04. Experimental results from test chip fabricated in AMS 350 nm process shows power savings of 46.3% and 65% for load circuit operating in super threshold and near sub-threshold region, respectively. Measured resolution of power monitor is around 0.25 mV and it has a power overhead of 2.2% of die power. Issues with loop convergence and design tradeoff for power monitor are also discussed in this paper.

Quenching across quantum critical points in periodic systems: Dependence of scaling laws on periodicity

We study the quenching dynamics of a many-body system in one dimension described by a Hamiltonian that has spatial periodicity. Specifically, we consider a spin-1/2 chain with equal xx and yy couplings and subject to a periodically varying magnetic field in the (z) over cap direction or, equivalently, a tight-binding model of spinless fermions with a periodic local chemical potential, having period 2q, where q is a positive integer. For a linear quench of the strength of the magnetic field (or chemical potential) at a rate 1/tau across a quantum critical point, we find that the density of defects thereby produced scales as 1/tau(q/(q+1)), deviating from the 1/root tau scaling that is ubiquitous in a range of systems. We analyze this behavior by mapping the low-energy physics of the system to a set of fermionic two-level systems labeled by the lattice momentum k undergoing a nonlinear quench as well as by performing numerical simulations. We also show that if the magnetic field is a superposition of different periods, the power law depends only on the smallest period for very large values of tau, although it may exhibit a crossover at intermediate values of tau. Finally, for the case where a zz coupling is also present in the spin chain, or equivalently, where interactions are present in the fermionic system, we argue that the power associated with the scaling law depends on a combination of q and the interaction strength.

Fatigue crack growth due to overloads in plain concrete using scaling laws

Scaling laws are represented in power law form and can be utilized to extract the characteristic properties of a new phenomenon with the help of self-similar solutions. In this work, an attempt has been made to propose a scaling law analytically, for plain concrete when subjected to variable amplitude loading. Due to the application of overload on concrete structures, acceleration in the crack growth process takes place. A closed form expression has been developed to capture the acceleration in crack growth rate in conjunction with the principles of dimensional analysis and self-similarity. The proposed model accounts for parameters such as, the tensile strength, fracture toughness, overload effect and the structural size. Knowing the governed and the governing parameters of the physical problem and by using the concepts of self-similarity, a relationship is obtained between the different parameters involved. The predicted results are compared with experimental crack growth data for variable amplitude loading and are found to capture the overload effect with sufficient accuracy. Through a sensitivity analysis, fracture toughness is found to be the most dominant parameter in accelerating the crack length due to application of overload.

Scaling analysis: Equivalence of convective and radiative heating of levitated droplet

This letter develops theoretical relationships for equilibrium timescale and temperature scale of a vaporizing droplet in a convective and a radiative environment. The transient temperature normalized by the respective scales exhibits a unified profile for both modes of heating. The analysis allows for the prediction of the required laser flux to show its equivalence in a corresponding heated gas stream. The theoretical equivalence shows good agreement with experiments across a range of droplet sizes. Simple experiments can be conducted in a levitator to extrapolate information in realistic convective environments like combustion and spray drying. (C) 2012 American Institute of Physics. http://dx.doi.org/10.1063/1.4720092]

Singlet-state creation and universal quantum computation in NMR using a genetic algorithm

The experimental implementation of a quantum algorithm requires the decomposition of unitary operators. Here we treat unitary-operator decomposition as an optimization problem, and use a genetic algorithm-a global-optimization method inspired by nature's evolutionary process-for operator decomposition. We apply this method to NMR quantum information processing, and find a probabilistic way of performing universal quantum computation using global hard pulses. We also demonstrate the efficient creation of the singlet state (a special type of Bell state) directly from thermal equilibrium, using an optimum sequence of pulses. © 2012 American Physical Society.

Singlet-state creation and universal quantum computation in NMR using a genetic algorithm

The experimental implementation of a quantum algorithm requires the decomposition of unitary operators. Here we treat unitary-operator decomposition as an optimization problem, and use a genetic algorithm-a global-optimization method inspired by nature's evolutionary process-for operator decomposition. We apply this method to NMR quantum information processing, and find a probabilistic way of performing universal quantum computation using global hard pulses. We also demonstrate the efficient creation of the singlet state (a special type of Bell state) directly from thermal equilibrium, using an optimum sequence of pulses.

Scaling Analysis of Solidification of Liquid Aluminum Alloy Flowing on Cooling Slope

Among all methods of metal alloy slurry preparation, the cooling slope method is the simplest in terms of design and process control. The method involves pouring of the melt from top, down an oblique and channel shaped plate cooled from bottom by counter flowing water. The melt, while flowing down, partially solidifies and forms columnar dendrites on plate wall. These dendrites are broken into equiaxed grains and are washed away with melt. The melt, together with the equiaxed grains, forms semisolid slurry collected at the slope exit and cast into billets having non-dendritic microstructure. The final microstructure depends on several process parameters such as slope angle, slope length, pouring superheat, and cooling rate. The present work involves scaling analysis of conservation equations of momentum, energy and species for the melt flow down a cooling slope. The main purpose of the scaling analysis is to obtain a physical insight into the role and relative importance of each parameter in influencing the final microstructure. For assessing the scaling analysis, the trends predicted by scaling are compared against corresponding numerical results using an enthalpy based solidification model with incorporation of solid phase movement.

Direct Observation of Valley Hybridization and Universal Symmetry of Graphene with Mesoscopic Conductance Fluctuations

In graphene, the valleys represent spinlike quantities and can act as a physical resource in valley-based electronics to produce novel quantum computation schemes. Here we demonstrate a direct route to tune and read the valley quantum states of disordered graphene by measuring the mesoscopic conductance fluctuations. We show that the conductance fluctuations in graphene at low temperatures are reduced by a factor of 4 when valley triplet states are gapped in the presence of short-range potential scatterers at high carrier densities. We also show that this implies a gate tunable universal symmetry class that outlines a fundamental feature arising from graphene's unique crystal structure.

Orthogonal biofunctionalization of magnetic nanoparticles via ``clickable'' poly(ethylene glycol) silanes: a ``universal ligand'' strategy to design stealth and target-specific nanocarriers

The present work demonstrates a novel strategy to synthesize orthogonally bio-engineered magnetonanohybrids (MNPs) through the design of versatile, biocompatible linkers whose structure includes: (i) a robust anchor to bind with metal-oxide surfaces; (ii) tailored surface groups to act as spacers and (iii) a general method to implement orthogonal functionalizations of the substrate via ``click chemistry''. Ligands that possess the synthetic generality of features (i)-(iii) are categorized as ``universal ligands''. Herein, we report the synthesis of a novel, azido-terminated poly(ethylene glycol) (PEG) silane that can easily self-assemble on MNPs through hetero-condensation between surface hydroxyl groups and the silane end of the ligand, and simultaneously provide multiple clickable sites for high density, chemoselective bio-conjugation. To establish the universal-ligand-strategy, we clicked alkyl-functionalized folate onto the surface of PEGylated MNPs. By further integrating a near-infrared fluorescent (NIRF) marker (Alexa-Fluor 647) with MNPs, we demonstrated their folate-receptor mediated internalization inside cancer cells and subsequent translocation into lysosomes and mitochondria. Ex vivo NIRF imaging established that the azido-PEG-silane developed in course of the study can effectively reduce the sequestration of MNPs by macrophage organs (viz. liver and spleen). These folate-PEG-MNPs were not only stealth and noncytotoxic but their dual optical and magnetic properties aided in tracking their whereabouts through combined magnetic resonance and optical imaging. Together, these results provided a strong motivation for the future use of the ``universal ligand'' strategy towards development of ``smart'' nanohybrids for theragnostic applications.

Time-Temperature Scaling of Conductivity Spectra of Organic Plastic Crystalline Conductors

Organic plastic crystalline soft matter ion conductors are interesting alternatives to liquid electrolytes in electrochemical storage devices such as Lithium-ion batteries. The solvent dynamics plays a major role in determining the ion transport in plastic crystalline ion conductors. We present here an analysis of the frequency-dependent ionic conductivity of succinonitrile-based plastic crystalline ion conductors at varying salt composition (0.005 to 1 M) and temperature (-20 to 60 degrees C) using time-temperature superposition principle (TTSP). The main motivation of the work has been to establish comprehensive insight into the ion transport mechanism from a single method viz, impedance spectroscopy rather than employing cluster of different characterization methods probing various length and time scales. The TTSP remarkably aids in explicit identification of the extent of the roles of solvent dynamics and ion-ion interactions on the effective conductivity of the orientationally disordered plastic crystalline ion conductors.

Evaluation of dynamic voltage and frequency scaling for stream programs

Dynamic Voltage and Frequency Scaling (DVFS) offers a huge potential for designing trade-offs involving energy, power, temperature and performance of computing systems. In this paper, we evaluate three different DVFS schemes - our enhancement of a Petri net performance model based DVFS method for sequential programs to stream programs, a simple profile based Linear Scaling method, and an existing hardware based DVFS method for multithreaded applications - using multithreaded stream applications, in a full system Chip Multiprocessor (CMP) simulator. From our evaluation, we find that the software based methods achieve significant Energy/Throughput2(ET−2) improvements. The hardware based scheme degrades performance heavily and suffers ET−2 loss. Our results indicate that the simple profile based scheme achieves the benefits of the complex Petri net based scheme for stream programs, and present a strong case for the need for independent voltage/frequency control for different cores of CMPs, which is lacking in most of the state-of-the-art CMPs. This is in contrast to the conclusions of a recent evaluation of per-core DVFS schemes for multithreaded applications for CMPs.

Nonparametric distributed sequential detection via universal source coding

We consider nonparametric or universal sequential hypothesis testing when the distribution under the null hypothesis is fully known but the alternate hypothesis corresponds to some other unknown distribution. These algorithms are primarily motivated from spectrum sensing in Cognitive Radios and intruder detection in wireless sensor networks. We use easily implementable universal lossless source codes to propose simple algorithms for such a setup. The algorithms are first proposed for discrete alphabet. Their performance and asymptotic properties are studied theoretically. Later these are extended to continuous alphabets. Their performance with two well known universal source codes, Lempel-Ziv code and KT-estimator with Arithmetic Encoder are compared. These algorithms are also compared with the tests using various other nonparametric estimators. Finally a decentralized version utilizing spatial diversity is also proposed and analysed.