Voltage and Temperature-Aware SSTA Using Neural Network Delay Model

With the emergence of voltage scaling as one of the most powerful power reduction techniques, it has been important to support voltage scalable statistical static timing analysis (SSTA) in deep submicrometer process nodes. In this paper, we propose a single delay model of logic gate using neural network which comprehensively captures process, voltage, and temperature variation along with input slew and output load. The number of simulation programs with integrated circuit emphasis (SPICE) required to create this model over a large voltage and temperature range is found to be modest and 4x less than that required for a conventional table-based approach with comparable accuracy. We show how the model can be used to derive sensitivities required for linear SSTA for an arbitrary voltage and temperature. Our experimentation on ISCAS 85 benchmarks across a voltage range of 0.9-1.1V shows that the average error in mean delay is less than 1.08% and average error in standard deviation is less than 2.85%. The errors in predicting the 99% and 1% probability point are 1.31% and 1%, respectively, with respect to SPICE. The two potential applications of voltage-aware SSTA have been presented, i.e., one for improving the accuracy of timing analysis by considering instance-specific voltage drops in power grids and the other for determining optimum supply voltage for target yield for dynamic voltage scaling applications.

Dynamic and thermodynamic anomalies of water at low temperatures: from bulk water to reverse micelles and DNA hydration layer

Liquid water is known to exhibit remarkable thermodynamic and dynamic anomalies, ranging from solvation properties in supercritical state to an apparent divergence of the linear response functions at a low temperature. Anomalies in various dynamic properties of water have also been observed in the hydration layer of proteins, DNA grooves and inside the nanocavity, such as reverse micelles and nanotubes. Here we report studies on the molecular origin of these anomalies in supercooled water, in the grooves of DNA double helix and reverse micelles. The anomalies have been discussed in terms of growing correlation length and intermittent population fluctuation of 4- and 5-coordinated species. We establish correlation between thermodynamic response functions and mean squared species number fluctuation. Lifetime analysis of 4- and 5-coordinated species reveals interesting differences between the role of the two species in supercooled and constrained water. The nature and manifestations of the apparent and much discussed liquid-liquid transition under confinement are found to be markedly different from that in the bulk. We find an interesting `faster than bulk' relaxation in reverse micelles which we attribute to frustration effects created by competition between the correlations imposed by surface interactions and that imposed by hydrogen bond network of water.

Dynamic Multiscaling in Two-Dimensional Fluid Turbulence

We obtain, by extensive direct numerical simulations, time-dependent and equal-time structure functions for the vorticity, in both quasi-Lagrangian and Eulerian frames, for the direct-cascade regime in two-dimensional fluid turbulence with air-drag-induced friction. We show that different ways of extracting time scales from these time-dependent structure functions lead to different dynamic-multiscaling exponents, which are related to equal-time multiscaling exponents by different classes of bridge relations; for a representative value of the friction we verify that, given our error bars, these bridge relations hold.

Aerodynamic Load Measurements at Hypersonic Speeds Using Internally Mounted Fiber-Optic Balance System

This paper describes the measurement of aerodynamic loads using fiber-optic strain gauge sensors and associated signal processors at hypersonic speeds in the 300mm hypersonic wind tunnel. at the Department of Aerospace Engineering, Indian Institute of Science. Fiber-optic sensors have been developed in USA since 1990, for variety of applications in experimental stress analysis, skin friction measurement in fluid flows, smart structures, smart materials, sensing of acoustic emission and more recently in the development of compact devices for measurement of displacement, stress/strain, pressure, temperature, acceleration etc. Our group at llSc has been playing a lead role in the use of these fiber - optic sensors for successful measurement of aerodynamic loads in wind tunnels and the first ever six-component wind tunnel strain gauge balance in the world based on fiber optic sensors was built at the Indian Institute of Science in the year 1999. We report here the results of our efforts in the development of an internal strain gauge balance for high-speed wind tunnel applications.

Improving Superscalar Instruction Dispatch And Issue By Exploiting Dynamic Code Sequences

Superscalar processors currently have the potential to fetch multiple basic blocks per cycle by employing one of several recently proposed instruction fetch mechanisms. However, this increased fetch bandwidth cannot be exploited unless pipeline stages further downstream correspondingly improve. In particular,register renaming a large number of instructions per cycle is diDcult. A large instruction window, needed to receive multiple basic blocks per cycle, will slow down dependence resolution and instruction issue. This paper addresses these and related issues by proposing (i) partitioning of the instruction window into multiple blocks, each holding a dynamic code sequence; (ii) logical partitioning of the registerjle into a global file and several local jles, the latter holding registers local to a dynamic code sequence; (iii) the dynamic recording and reuse of register renaming information for registers local to a dynamic code sequence. Performance studies show these mechanisms improve performance over traditional superscalar processors by factors ranging from 1.5 to a little over 3 for the SPEC Integer programs. Next, it is observed that several of the loops in the benchmarks display vector-like behavior during execution, even if the static loop bodies are likely complex for compile-time vectorization. A dynamic loop vectorization mechanism that builds on top of the above mechanisms is briefly outlined. The mechanism vectorizes up to 60% of the dynamic instructions for some programs, albeit the average number of iterations per loop is quite small.

Decentralized dynamic compensators for large multivariable systems

In this paper, we consider the synthesis of decentralized dynamic compensators for large systems. The eliminant approach is used to obtain sufficient conditions for the existence of proper, stable, decentralized observer-controllers for stabilizing a large system. An illustrative example is given.

An Area-Efficient Noise-Adaptive Neural Amplifier in 130 nm CMOS Technology

Chronic recording of neural signals is indispensable in designing efficient brain–machine interfaces and to elucidate human neurophysiology. The advent of multichannel micro-electrode arrays has driven the need for electronics to record neural signals from many neurons. The dynamic range of the system can vary over time due to change in electrode–neuron distance and background noise. We propose a neural amplifier in UMC 130 nm, 1P8M complementary metal–oxide–semiconductor (CMOS) technology. It can be biased adaptively from 200 nA to 2 $mu{rm A}$, modulating input referred noise from 9.92 $mu{rm V}$ to 3.9 $mu{rm V}$. We also describe a low noise design technique which minimizes the noise contribution of the load circuitry. Optimum sizing of the input transistors minimizes the accentuation of the input referred noise of the amplifier and obviates the need of large input capacitance. The amplifier achieves a noise efficiency factor of 2.58. The amplifier can pass signal from 5 Hz to 7 kHz and the bandwidth of the amplifier can be tuned for rejecting low field potentials (LFP) and power line interference. The amplifier achieves a mid-band voltage gain of 37 dB. In vitro experiments are performed to validate the applicability of the neural low noise amplifier in neural recording systems.

High voltage DC power supply topology for pulsed load applications with converter switching synchronized to load pulses

High voltage power supplies for radar applications are investigated, which are subjected to pulsed load (125 kHz and 10% duty cycle) with stringent specifications (<0.01% regulation, efficiency>85%, droop<0.5 V/micro-sec.). As good regulation and stable operation requires the converter to be switched at much higher frequency than the pulse load frequency, transformer poses serious problems of insulation failure and higher losses. This paper proposes a methodology to tackle the problems associated with this type of application. Synchronization of converter switching with load pulses enables the converter to switch at half the load switching frequency. Low switching frequency helps in ensuring safety of HV transformer insulation and reduction of losses due to skin and proximity effect. Phase-modulated series resonant converter with ZVS is used as the power converter.

Input voltage modulated high voltage DC power supply topology for pulsed load applications

High voltage power supplies for radar applications are investigated which are subjected to pulsed load with stringent specifications. In the proposed solution, power conversion is done in two stages. A low power-high frequency converter modulates the input voltage of a high power-low frequency converter. This method satisfies all the performance specifications and takes care of the critical aspects of HV transformer.

Optimum Load Shedding Through Programming Techniques

This paper obtains a new accurate model for sensitivity in power systems and uses it in conjunction with linear programming for the solution of load-shedding problems with a minimum loss of loads. For cases where the error in the sensitivity model increases, other linear programming and quadratic programming models have been developed, assuming currents at load buses as variables and not load powers. A weighted error criterion has been used to take priority schedule into account; it can be either a linear or a quadratic function of the errors, and depending upon the function appropriate programming techniques are to be employed.

Digital Simulation of Field-Oriented Control of Induction Motor

This paper describes the simulation of a control scheme using the principle of field orientation for the control of a voltage source inverter-fed induction motor. The control principle is explained, followed by an algorithm to simulate various components of the system in the digital computer. The dynamic response of the system for the load disturbance and set-point variations have been studied. Also, the results of the simulation showing the behavior of field coordinates for such disturbances are given.

Temperature-pressure-induced solid-solid < 100 > to < 110 > reorientation in FCC metallic nanowire: a molecular dynamic study

Atomistic simulation of initial < 100 > oriented FCC Cu nanowires shows a novel coupled temperature-pressure dependent reorientation from < 100 > to < 110 > phase. A temperature-pressure-induced solid-solid < 100 > to < 110 > reorientation diagram is generated for Cu nanowire with varying cross-sectional sizes. A critical pressure is reported for Cu nanowires with varying cross-sectional sizes, above which an initial < 100 > oriented nanowire shows temperature independent reorientation into the < 110 > phase. The effect of surface stresses on the < 100 > to < 110 > reorientation is also studied. The results indicate that above a critical cross-sectional size for a given temperature-pressure, < 100 > to < 110 > reorientation is not possible. It is also reported here that for a given applied pressure, an increase in temperature is required for the < 100 > to < 110 > reorientation with increasing cross-sectional size of the nanowire. The temperature-pressure-induced solid-solid < 100 > to < 110 > reorientation diagram reported in the present paper could further be used as guidelines for controlling the reorientations/shape memory in nano-scale applications of FCC metallic nanowires.

Softening and dynamic recrystallization in magnesium single crystals during c-axis compression

Commercial purity (99.8%) magnesium single crystals were subjected to plane strain compression (PSC) along the c-axis at 200 and 370 degrees C and a constant strain rate of 10(-3) s(-1). Extension was confined to the < 1 1 (2) over bar 0 > direction and the specimens were strained up to a logarithmic true strain of -1. The initial rapid increase in flow stress was followed by significant work softening at different stresses and comparable strains of about -0.05 related to macroscopic twinning events. The microstructure of the specimen after PSC at 200 degrees C was characterized by a high density of {1 0 (1) over bar 1} and {1 0 (1) over bar 3} compression twins, some of which were recrystallized. After PSC at 370 degrees C, completely recrystallized twin bands were the major feature of the observed microstructure. All new grains in these bands retained the same c-axis orientation of their compression twin hosts. The basal plane in these grains was randomly rotated around the c-axis, forming a fiber texture component. The obtained results are discussed with respect to the mechanism of recrystallization, the specific character of the boundaries between new grains and the initial matrix, and the importance of the dynamically recrystallized bands for strain accommodation in these deformed magnesium single crystals. (C) 2011 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.