Within-Die Gate Delay Variability Measurement using Re-configurable Ring Oscillator

We report a circuit technique to measure the on-chip delay of an individual logic gate (both inverting and non-inverting) in its unmodified form using digitally reconfigurable ring oscillator (RO). Solving a system of linear equations with different configuration setting of the RO gives delay of an individual gate. Experimental results from a test chip in 65nm process node show the feasibility of measuring the delay of an individual inverter to within 1pS accuracy. Delay measurements of different nominally identical inverters in close physical proximity show variations of up to 26% indicating the large impact of local or within-die variations.

Paired electromagnetically induced transparency with dual mode laser: A step towards EIT-Comb

Coupled electromagnetically induced transparency (EIT) has been observed with a dual mode control laser. The technique can be used for generating EIT-comb from optical frequency comb.

Microarchitecture sensitive empirical models for compiler optimizations.

This paper proposes the use of empirical modeling techniques for building microarchitecture sensitive models for compiler optimizations. The models we build relate program performance to settings of compiler optimization flags, associated heuristics and key microarchitectural parameters. Unlike traditional analytical modeling methods, this relationship is learned entirely from data obtained by measuring performance at a small number of carefully selected compiler/microarchitecture configurations. We evaluate three different learning techniques in this context viz. linear regression, adaptive regression splines and radial basis function networks. We use the generated models to a) predict program performance at arbitrary compiler/microarchitecture configurations, b) quantify the significance of complex interactions between optimizations and the microarchitecture, and c) efficiently search for'optimal' settings of optimization flags and heuristics for any given microarchitectural configuration. Our evaluation using benchmarks from the SPEC CPU2000 suits suggests that accurate models (< 5% average error in prediction) can be generated using a reasonable number of simulations. We also find that using compiler settings prescribed by a model-based search can improve program performance by as much as 19% (with an average of 9.5%) over highly optimized binaries.

Real-time image denoising algorithm in teleradiology systems - art.no.606304

Denoising of medical images in wavelet domain has potential application in transmission technologies such as teleradiology. This technique becomes all the more attractive when we consider the progressive transmission in a teleradiology system. The transmitted images are corrupted mainly due to noisy channels. In this paper, we present a new real time image denoising scheme based on limited restoration of bit-planes of wavelet coefficients. The proposed scheme exploits the fundamental property of wavelet transform - its ability to analyze the image at different resolution levels and the edge information associated with each sub-band. The desired bit-rate control is achieved by applying the restoration on a limited number of bit-planes subject to the optimal smoothing. The proposed method adapts itself to the preference of the medical expert; a single parameter can be used to balance the preservation of (expert-dependent) relevant details against the degree of noise reduction. The proposed scheme relies on the fact that noise commonly manifests itself as a fine-grained structure in image and wavelet transform allows the restoration strategy to adapt itself according to directional features of edges. The proposed approach shows promising results when compared with unrestored case, in context of error reduction. It also has capability to adapt to situations where noise level in the image varies and with the changing requirements of medical-experts. The applicability of the proposed approach has implications in restoration of medical images in teleradiology systems. The proposed scheme is computationally efficient.

Design issues and caching strategies for CD-ROM based multimedia storage

CD-ROMs have proliferated as a distribution media for desktop machines for a large variety of multimedia applications (targeted for a single-user environment) like encyclopedias, magazines and games. With CD-ROM capacities up to 3 GB being available in the near future, they will form an integral part of Video on Demand (VoD) servers to store full-length movies and multimedia. In the first section of this paper we look at issues related to the single- user desktop environment. Since these multimedia applications are highly interactive in nature, we take a pragmatic approach, and have made a detailed study of the multimedia application behavior in terms of the I/O request patterns generated to the CD-ROM subsystem by tracing these patterns. We discuss prefetch buffer design and seek time characteristics in the context of the analysis of these traces. We also propose an adaptive main-memory hosted cache that receives caching hints from the application to reduce the latency when the user moves from one node of the hyper graph to another. In the second section we look at the use of CD-ROM in a VoD server and discuss the problem of scheduling multiple request streams and buffer management in this scenario. We adapt the C-SCAN (Circular SCAN) algorithm to suit the CD-ROM drive characteristics and prove that it is optimal in terms of buffer size management. We provide computationally inexpensive relations by which this algorithm can be implemented. We then propose an admission control algorithm which admits new request streams without disrupting the continuity of playback of the previous request streams. The algorithm also supports operations such as fast forward and replay. Finally, we discuss the problem of optimal placement of MPEG streams on CD-ROMs in the third section.

Video coding mode decision as a classification problem

In this paper, we show that it is possible to reduce the complexity of Intra MB coding in H.264/AVC based on a novel chance constrained classifier. Using the pairs of simple mean-variances values, our technique is able to reduce the complexity of Intra MB coding process with a negligible loss in PSNR. We present an alternate approach to address the classification problem which is equivalent to machine learning. Implementation results show that the proposed method reduces encoding time to about 20% of the reference implementation with average loss of 0.05 dB in PSNR.

Averting biodiversity collapse in tropical forest protected areas

The rapid disruption of tropical forests probably imperils global biodiversity more than any other contemporary phenomenon(1-3). With deforestation advancing quickly, protected areas are increasingly becoming final refuges for threatened species and natural ecosystem processes. However, many protected areas in the tropics are themselves vulnerable to human encroachment and other environmental stresses(4-9). As pressures mount, it is vital to know whether existing reserves can sustain their biodiversity. A critical constraint in addressing this question has been that data describing a broad array of biodiversity groups have been unavailable for a sufficiently large and representative sample of reserves. Here we present a uniquely comprehensive data set on changes over the past 20 to 30 years in 31 functional groups of species and 21 potential drivers of environmental change, for 60 protected areas stratified across the world's major tropical regions. Our analysis reveals great variation in reserve `health': about half of all reserves have been effective or performed passably, but the rest are experiencing an erosion of biodiversity that is often alarmingly widespread taxonomically and functionally. Habitat disruption, hunting and forest-product exploitation were the strongest predictors of declining reserve health. Crucially, environmental changes immediately outside reserves seemed nearly as important as those inside in determining their ecological fate, with changes inside reserves strongly mirroring those occurring around them. These findings suggest that tropical protected areas are often intimately linked ecologically to their surrounding habitats, and that a failure to stem broad-scale loss and degradation of such habitats could sharply increase the likelihood of serious biodiversity declines.

Automatic compilation of MATLAB programs for synergistic execution on heterogeneous processors

MATLAB is an array language, initially popular for rapid prototyping, but is now being increasingly used to develop production code for numerical and scientific applications. Typical MATLAB programs have abundant data parallelism. These programs also have control flow dominated scalar regions that have an impact on the program's execution time. Today's computer systems have tremendous computing power in the form of traditional CPU cores and throughput oriented accelerators such as graphics processing units(GPUs). Thus, an approach that maps the control flow dominated regions to the CPU and the data parallel regions to the GPU can significantly improve program performance. In this paper, we present the design and implementation of MEGHA, a compiler that automatically compiles MATLAB programs to enable synergistic execution on heterogeneous processors. Our solution is fully automated and does not require programmer input for identifying data parallel regions. We propose a set of compiler optimizations tailored for MATLAB. Our compiler identifies data parallel regions of the program and composes them into kernels. The problem of combining statements into kernels is formulated as a constrained graph clustering problem. Heuristics are presented to map identified kernels to either the CPU or GPU so that kernel execution on the CPU and the GPU happens synergistically and the amount of data transfer needed is minimized. In order to ensure required data movement for dependencies across basic blocks, we propose a data flow analysis and edge splitting strategy. Thus our compiler automatically handles composition of kernels, mapping of kernels to CPU and GPU, scheduling and insertion of required data transfer. The proposed compiler was implemented and experimental evaluation using a set of MATLAB benchmarks shows that our approach achieves a geometric mean speedup of 19.8X for data parallel benchmarks over native execution of MATLAB.

Fully complex-valued ELM classifiers for human action recognition

In this paper, we present a fast learning neural network classifier for human action recognition. The proposed classifier is a fully complex-valued neural network with a single hidden layer. The neurons in the hidden layer employ the fully complex-valued hyperbolic secant as an activation function. The parameters of the hidden layer are chosen randomly and the output weights are estimated analytically as a minimum norm least square solution to a set of linear equations. The fast leaning fully complex-valued neural classifier is used for recognizing human actions accurately. Optical flow-based features extracted from the video sequences are utilized to recognize 10 different human actions. The feature vectors are computationally simple first order statistics of the optical flow vectors, obtained from coarse to fine rectangular patches centered around the object. The results indicate the superior performance of the complex-valued neural classifier for action recognition. The superior performance of the complex neural network for action recognition stems from the fact that motion, by nature, consists of two components, one along each of the axes.

Assessing the critical concentration of NH2 terminal groups on the surface of MWNTs towards chain scission of PC in PC/SAN blends: effect on dispersion, electrical conductivity and EMI shielding

The localization and dispersion quality of as received NH2 terminated multiwall carbon nanotubes (MWNT-I) and ethylene diamine (EDA) functionalized MWNTs in melt mixed blends of polycarbonate ( PC) and poly(styrene-co-acrylonitrile) (SAN) were assessed in this study using rheo-electrical and electromagnetic interference (EMI) shielding measurements. In order to improve the dispersion quality and also to selectively localize MWNTs in the PC phase of the blends, EDA was grafted onto MWNTs by two different strategies like diazonium reaction of the para-substituted benzene ring of MWNTs with EDA ( referred to as MWNT-II) and acylation of carboxyl functionalized MWNTs with thionyl chloride ( referred to as MWNT-III). By this approach we could systematically vary the concentration of NH2 functional groups on the surface of MWNTs at a fixed concentration (1 wt%) in PC/SAN blends. XPS was carried to evaluate the % concentration of N in different MWNTs and was observed to be highest for MWNT-III manifesting in a large surface coverage of EDA on the surface of MWNTs. Viscoelastic properties and melt electrical conductivities were measured to assess the dispersion quality of MWNTs using a rheo-electrical set-up both in the quiescent as well as under steady shear conditions. Rheological properties revealed chain scission of PC in the presence of MWNT-III which is due to specific interactions between EDA and PC leading to smaller PC grafts on the surface of MWNTs. The observed viscoelastic properties in the blends were further correlated with the phase morphologies under quiescent and annealed conditions. Electromagnetic interference (EMI) shielding effectiveness in X and K-u-band frequencies were measured to explore these composites for EMI shielding applications. Interestingly, MWNT-II showed the highest electrical conductivity and EMI shielding in the blends.

Application of Qualitative Imaging Methods to Electrical Performance-Aware Package Board Design

Package-board co-design plays a crucial role in determining the performance of high-speed systems. Although there exist several commercial solutions for electromagnetic analysis and verification, lack of Computer Aided Design (CAD) tools for SI aware design and synthesis lead to longer design cycles and non-optimal package-board interconnect geometries. In this work, the functional similarities between package-board design and radio-frequency (RF) imaging are explored. Consequently, qualitative methods common to the imaging community, like Tikhonov Regularization (TR) and Landweber method are applied to solve multi-objective, multi-variable package design problems. In addition, a new hierarchical iterative piecewise linear algorithm is developed as a wrapper over LBP for an efficient solution in the design space.

Efficient Adaptive Mesh Refinement for MoM-based Package-Board 3D Full-wave Extraction

The accurate solution of 3D full-wave Method of Moments (MoM) on an arbitrary mesh of a package-board structure does not guarantee accuracy, since the discretizations may not be fine enough to capture rapid spatial changes in the solution variable. At the same time, uniform over-meshing on the entire structure generates large number of solution variables and therefore requires an unnecessarily large matrix solution. In this work, a suitable refinement criterion for MoM based electromagnetic package-board extraction is proposed and the advantages of the adaptive strategy are demonstrated from both accuracy and speed perspectives.

Electromagnetic interference shielding through MWNT grafted Fe3O4 nanoparticles in PC/SAN blends

In this study, multiwall carbon nanotubes (MWNTs) were chemically grafted onto dopamine anchored iron oxide (Fe3O4) nanoparticles via diazotization reaction to design electromagnetic (EM) shielding materials based on PC (polycarbonate)/SAN poly (styrene-co-acrylonitrile)] blends. A two step mixing protocol was adopted to selectively localize the nanoparticles in a given phase of the blends. In the first step, MWNT-g-Fe3O4 nanoparticles were solution blended with PC, followed by dilution with SAN during melt mixing in the subsequent step. This strategy, besides improving the quality of dispersion of MWNTs in the blends, facilitated enhanced EM interference shielding effectiveness (SE). Both, the MWNTs and the modified MWNTs, selectively localized in the PC phase and led to high electrical conductivity, in striking contrast to PC filled MWNT composites. The SE was measured on toroidal samples over a broad range of frequencies; X-band (8.2-12 GHz) and K-u-band (12-18 GHz). It was observed that the shielding mechanism mostly involved reflection in the blends with MWNTs, whereas absorption dominated in the case of blends with MWNT-g-Fe3O4. To realize the efficacy of this strategy, a few compositions were prepared by physical mixing MWNTs with Fe3O4 nanoparticles. Intriguingly, blends with MWNT-g-Fe3O4 nanoparticles manifested enhanced microwave absorption over physically mixed nanoparticles. An SE of -32.5 dB was observed (at 18 GHz) for MWNT (3 wt%)-g-Fe3O4 (3 vol%) in PC/SAN blends.

Microwave absorbers designed from PVDF/SAN blends containing multiwall carbon nanotubes anchored cobalt ferrite via a pyrene derivative

Lightweight and flexible electromagnetic shielding materials were designed by selectively localizing multiwall carbon nanotubes (MWNTs) anchored magnetic nanoparticles in melt mixed co-continuous blends of polyvinylidene fluoride (PVDF) and poly(styrene-co-acrylonitrile) (SAN). In order to facilitate better dispersion, the MWNTs were modified using pyrenebutyric acid (PBA) via pi-pi stacking. While one of the two-targeted properties, i.e., high electrical conductivity, was achieved by PBA modified MWNTs, high magnetic loss was accomplished by introducing nickel (NF) or cobalt ferrites (CF). Moreover, the attenuation by absorption can be tuned either by using NF (58% absorption) or CF (64% absorption) in combination with PBA-MWNTs. More interestingly, when CF was anchored on to MWNTs via the pyrene derivative, the minimum reflection loss attained was -55 dB in the Ku band (12-18 GHz) frequency and with a large bandwidth. In addition, the EM waves were blocked mostly by absorption (70%). This study opens new avenues in designing flexible and lightweight microwave absorbers.