Compiling Techniques for Coarse Grained Runtime Reconfigurable Architectures

In this paper we develop compilation techniques for the realization of applications described in a High Level Language (HLL) onto a Runtime Reconfigurable Architecture. The compiler determines Hyper Operations (HyperOps) that are subgraphs of a data flow graph (of an application) and comprise elementary operations that have strong producer-consumer relationship. These HyperOps are hosted on computation structures that are provisioned on demand at runtime. We also report compiler optimizations that collectively reduce the overheads of data-driven computations in runtime reconfigurable architectures. On an average, HyperOps offer a 44% reduction in total execution time and a 18% reduction in management overheads as compared to using basic blocks as coarse grained operations. We show that HyperOps formed using our compiler are suitable to support data flow software pipelining.

Transversely isotropic infinite cylindrical shell subjected to a radial axisymmetric line load

The problem of an infinite transversely isotropic circular cylindrical shell subjected to an axisymmetric radial external line load is investigated using elasticity theory, classical shell theory and shear deformation theory. The results obtained by these methods are compared for two ratios of inner to outer shell radius and for varying degrees of anisotropy. Some typical results are given here to show the effect of anisotropy and the thickness of the shell on the distribution of stresses and displacements.

Transversely isotropic infinite cylindrical shell subjected to a radial axisymmetric line load

The problem of an infinite transversely isotropic circular cylindrical shell subjected to an axisymmetric radial external line load is investigated using elasticity theory, classical shell theory and shear deformation theory. The results obtained by these methods are compared for two ratios of inner to outer shell radius and for varying degrees of anisotropy. Some typical results are given here to show the effect of anisotropy and the thickness of the shell on the distribution of stresses and displacements.

Stress analysis of a thick plate having a circular hole under axisymmetric radial load

In this paper a solution for the determination of stresses and displacements in a thick plate having a cylindrical hole subjected to localised hydrostatic loading has been given. Detail numerical results have been presented and compared with the results of an infinite hole subjected to localised hydrostatic load and a semiinfinite hole subjected to localised end load. It has been shown that for certain ratio of thickness of the pate to the radius of the hole and loading, the results could be obtained by using the solution of infinite or semiinfinite hole subjected to the same hydrostatic loading.

Improvement in the voltage grading (axial and radial) of the generator column of a Van de Graaf generator by the use of a resistor chain

It is well known that the use of a series of resistors, connected between the equipotential rings of a Van de Graaff generator, improves the axial voltage grading of the generator. The work reported in this paper shows how the resistor chain also improves the radial voltage gradient. The electrolytic field mapping technique was adopted in the present work.

Rational design of 3D dendritic TiO2 nanostructures with favorable architectures

Controlling the morphology and size of titanium dioxide (TiO2) nanostructures is crucial to obtain superior photocatalytic, photovoltaic, and electrochemical properties. However, the synthetic techniques for preparing such structures, especially those with complex configurations, still remain a challenge because of the rapid hydrolysis of Ti-containing polymer precursors in aqueous solution. Herein, we report a completely novel approach-three- dimensional (3D) TiO2 nanostructures with favorable dendritic architectures-through a simple hydrothermal synthesis. The size of the 3D TiO2 dendrites and the morphology of the constituent nano-units, in the form of nanorods, nanoribbons, and nanowires, are controlled by adjusting the precursor hydrolysis rate and the surfactant aggregation. These novel configurations of TiO2 nanostructures possess higher surface area and superior electrochemical properties compared to nanoparticles with smooth surfaces. Our findings provide an effective solution for the synthesis of complex TiO2 nano-architectures, which can pave the way to further improve the energy storage and energy conversion efficiency of TiO 2-based devices.

Compiler-assisted instruction decoder energy optimization for clustered VLIW architectures

Traditionally, an instruction decoder is designed as a monolithic structure that inhibit the leakage energy optimization. In this paper, we consider a split instruction decoder that enable the leakage energy optimization. We also propose a compiler scheduling algorithm that exploits instruction slack to increase the simultaneous active and idle duration in instruction decoder. The proposed compiler-assisted scheme obtains a further 14.5% reduction of energy consumption of instruction decoder over a hardware-only scheme for a VLIW architecture. The benefits are 17.3% and 18.7% in the context of a 2-clustered and a 4-clustered VLIW architecture respectively.

Privacy architectures in social networks’ state-of-the-art survey

The use of social networking has exploded, with millions of people using various web- and mobile-based services around the world. This increase in social networking use has led to user anxiety related to privacy and the unauthorised exposure of personal information. Large-scale sharing in virtual spaces means that researchers, designers and developers now need to re-consider the issues and challenges of maintaining privacy when using social networking services. This paper provides a comprehensive survey of the current state-of-the-art privacy in social networks for both desktop and mobile uses and devices from various architectural vantage points. The survey will assist researchers and analysts in academia and industry to move towards mitigating many of the privacy issues in social networks.

Rotorcraft parameter estimation using radial basis function neural network

Increased emphasis on rotorcraft performance and perational capabilities has resulted in accurate computation of aerodynamic stability and control parameters. System identification is one such tool in which the model structure and parameters such as aerodynamic stability and control derivatives are derived. In the present work, the rotorcraft aerodynamic parameters are computed using radial basis function neural networks (RBFN) in the presence of both state and measurement noise. The effect of presence of outliers in the data is also considered. RBFN is found to give superior results compared to finite difference derivatives for noisy data. (C) 2010 Elsevier Inc. All rights reserved.

High-Throughput Flexible Constraint Length Viterbi Decoders on De Bruijn, Shuffle-Exchange and Butterfly Connected Architectures

Flexible constraint length channel decoders are required for software defined radios. This paper presents a novel scalable scheme for realizing flexible constraint length Viterbi decoders on a de Bruijn interconnection network. Architectures for flexible decoders using the flattened butterfly and shuffle-exchange networks are also described. It is shown that these networks provide favourable substrates for realizing flexible convolutional decoders. Synthesis results for the three networks are provided and a comparison is performed. An architecture based on a 2D-mesh, which is a topology having a nominally lesser silicon area requirement, is also considered as a fourth point for comparison. It is found that of all the networks considered, the de Bruijn network offers the best tradeoff in terms of area versus throughput.

Analysis of network architectures for zigbee sensor clusters

We provide a comparative performance analysis of network architectures for beacon enabled Zigbee sensor clusters using the CSMA/CA MAC defined in the IEEE 802.15.4 standard, and organised as (i) a star topology, and (ii) a two-hop topology. We provide analytical models for obtaining performance measures such as mean network delay, and mean node lifetime. We find that the star topology is substantially superior both in delay performance and lifetime performance than the two-hop topology.

On the investigation of singular stress field around radial cracks in annulii subjected to diametrical tension

Results of photoelastic investigation conducted on annulii containing a radial crack at inner edge and subjected to diametrical tension are reported. The cracks are oriented at 90°, 60° and 45° to the loading direction. The Stress-Intensity Factors (SIFs) were determined by analysing the crack-tip stress fields. Smith and Smith's method [Engng Fracture Mech.4, 357–366 (1972)] and a modified method developed earlier by the authors (to be published) were adopted in the evaluation of SIFs.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications.