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.

Automatic road extraction using high resolution satellite images based on Level Set and Mean Shift methods

Analysis of high resolution satellite images has been an important research topic for urban analysis. One of the important features of urban areas in urban analysis is the automatic road network extraction. Two approaches for road extraction based on Level Set and Mean Shift methods are proposed. From an original image it is difficult and computationally expensive to extract roads due to presences of other road-like features with straight edges. The image is preprocessed to improve the tolerance by reducing the noise (the buildings, parking lots, vegetation regions and other open spaces) and roads are first extracted as elongated regions, nonlinear noise segments are removed using a median filter (based on the fact that road networks constitute large number of small linear structures). Then road extraction is performed using Level Set and Mean Shift method. Finally the accuracy for the road extracted images is evaluated based on quality measures. The 1m resolution IKONOS data has been used for the experiment.

Spectral zero-crossings: localization properties and application to epoch extraction in speech signals

We analyze the spectral zero-crossing rate (SZCR) properties of transient signals and show that SZCR contains accurate localization information about the transient. For a train of pulses containing transient events, the SZCR computed on a sliding window basis is useful in locating the impulse locations accurately. We present the properties of SZCR on standard stylized signal models and then show how it may be used to estimate the epochs in speech signals. We also present comparisons with some state-of-the-art techniques that are based on the group-delay function. Experiments on real speech show that the proposed SZCR technique is better than other group-delay-based epoch detectors. In the presence of noise, a comparison with the zero-frequency filtering technique (ZFF) and Dynamic programming projected Phase-Slope Algorithm (DYPSA) showed that performance of the SZCR technique is better than DYPSA and inferior to that of ZFF. For highpass-filtered speech, where ZFF performance suffers drastically, the identification rates of SZCR are better than those of DYPSA.

Scalar field visualization via extraction of symmetric structures

Identifying symmetry in scalar fields is a recent area of research in scientific visualization and computer graphics communities. Symmetry detection techniques based on abstract representations of the scalar field use only limited geometric information in their analysis. Hence they may not be suited for applications that study the geometric properties of the regions in the domain. On the other hand, methods that accumulate local evidence of symmetry through a voting procedure have been successfully used for detecting geometric symmetry in shapes. We extend such a technique to scalar fields and use it to detect geometrically symmetric regions in synthetic as well as real-world datasets. Identifying symmetry in the scalar field can significantly improve visualization and interactive exploration of the data. We demonstrate different applications of the symmetry detection method to scientific visualization: query-based exploration of scalar fields, linked selection in symmetric regions for interactive visualization, and classification of geometrically symmetric regions and its application to anomaly detection.

Integration of speckle de-noising and image segmentation using synthetic aperture radar image for flood extent extraction

Flood is one of the detrimental hydro-meteorological threats to mankind. This compels very efficient flood assessment models. In this paper, we propose remote sensing based flood assessment using Synthetic Aperture Radar (SAR) image because of its imperviousness to unfavourable weather conditions. However, they suffer from the speckle noise. Hence, the processing of SAR image is applied in two stages: speckle removal filters and image segmentation methods for flood mapping. The speckle noise has been reduced with the help of Lee, Frost and Gamma MAP filters. A performance comparison of these speckle removal filters is presented. From the results obtained, we deduce that the Gamma MAP is reliable. The selected Gamma MAP filtered image is segmented using Gray Level Co-occurrence Matrix (GLCM) and Mean Shift Segmentation (MSS). The GLCM is a texture analysis method that separates the image pixels into water and non-water groups based on their spectral feature whereas MSS is a gradient ascent method, here segmentation is carried out using spectral and spatial information. As test case, Kosi river flood is considered in our study. From the segmentation result of both these methods are comprehensively analysed and concluded that the MSS is efficient for flood mapping.

Synergistic effect of reactor chemistry and compressive stress on dislocation bending during GaN growth

The synergistic effect of compressive growth stresses and reactor chemistry, silane presence, on dislocation bending at the very early stages of GaN growth has been studied using in-situ stress measurements and cross-sectional transmission electron microscopy. A single 100 nm Si-doped GaN layer is found to be more effective than a 1 mu m linearly graded AlGaN buffer layer in reducing dislocation density and preventing the subsequent layer from transitioning to a tensile stress. 1 mu m crack-free GaN layers with a dislocation density of 7 x 10(8)/cm(2), with 0.13 nm surface roughness and no enhancement in n-type background are demonstrated over 2 inch substrates using this simple transition scheme. (C) 2013 AIP Publishing LLC.

Classification, representation, and automatic extraction of deformation features in sheet metal parts

This paper presents classification, representation and extraction of deformation features in sheet-metal parts. The thickness is constant for these shape features and hence these are also referred to as constant thickness features. The deformation feature is represented as a set of faces with a characteristic arrangement among the faces. Deformation of the base-sheet or forming of material creates Bends and Walls with respect to a base-sheet or a reference plane. These are referred to as Basic Deformation Features (BDFs). Compound deformation features having two or more BDFs are defined as characteristic combinations of Bends and Walls and represented as a graph called Basic Deformation Features Graph (BDFG). The graph, therefore, represents a compound deformation feature uniquely. The characteristic arrangement of the faces and type of bends belonging to the feature decide the type and nature of the deformation feature. Algorithms have been developed to extract and identify deformation features from a CAD model of sheet-metal parts. The proposed algorithm does not require folding and unfolding of the part as intermediate steps to recognize deformation features. Representations of typical features are illustrated and results of extracting these deformation features from typical sheet metal parts are presented and discussed. (C) 2013 Elsevier Ltd. All rights reserved.

Employing synergistic interactions between few-layer WS2 and reduced graphene oxide to improve lithium storage, cyclability and rate capability of Li-ion batteries

The aim of the contribution is to introduce a high performance anode alternative to graphite for lithium-ion batteries (LiBs). A simple process was employed to synthesize uniform graphene-like few-layer tungsten sulfide (WS2) supported on reduced graphene oxide (RGO) through a hydrothermal synthesis route. The WS2-RGO (80:20 and 70:30) composites exhibited good enhanced electrochemical performance and excellent rate capability performance when used as anode materials for lithium-ion batteries. The specific capacity of the WS2-RGO composite delivered a capacity of 400-450 mAh g(-1) after 50 cycles when cycled at a current density of 100 mA g(-1). At 4000 mA g(-1), the composites showed a stable capacity of approximately 180-240 mAh g(-1), respectively. The noteworthy electrochemical performance of the composite is not additive, rather it is synergistic in the sense that the electrochemical performance is much superior compared to both WS2 and RGO. As the observed lithiation/delithiation for WS2-RGO is at a voltage 1.0 V (approximate to 0.1 V for graphite, Li* /Li), the lithium-ion battery with WS2-RGO is expected to possess high interface stability, safety and management of electrical energy is expected to be more efficient and economic. (C) 2013 Elsevier Ltd. All rights reserved.

Synergistic Lewis base and anion-binding catalysis for the enantioselective vinylogous addition of deconjugated butenolides to allenoates

An enantioselective vinylogous umpolung addition of deconjugated butenolides to allenoates has been developed for the first time with the help of synergistic combination of an achiral phosphine and a chiral squaramide, and represents the first example of a catalytic enantioselective C gamma-C gamma bond formation between two different carbonyl partners.

Epoch extraction based on integrated linear prediction residual using plosion index

Epoch is defined as the instant of significant excitation within a pitch period of voiced speech. Epoch extraction continues to attract the interest of researchers because of its significance in speech analysis. Existing high performance epoch extraction algorithms require either dynamic programming techniques or a priori information of the average pitch period. An algorithm without such requirements is proposed based on integrated linear prediction residual (ILPR) which resembles the voice source signal. Half wave rectified and negated ILPR (or Hilbert transform of ILPR) is used as the pre-processed signal. A new non-linear temporal measure named the plosion index (PI) has been proposed for detecting `transients' in speech signal. An extension of PI, called the dynamic plosion index (DPI) is applied on pre-processed signal to estimate the epochs. The proposed DPI algorithm is validated using six large databases which provide simultaneous EGG recordings. Creaky and singing voice samples are also analyzed. The algorithm has been tested for its robustness in the presence of additive white and babble noise and on simulated telephone quality speech. The performance of the DPI algorithm is found to be comparable or better than five state-of-the-art techniques for the experiments considered.

Assimilation of endmember variability in spectral for urban land cover extraction mixture analysis

Variable Endmember Constrained Least Square (VECLS) technique is proposed to account endmember variability in the linear mixture model by incorporating the variance for each class, the signals of which varies from pixel to pixel due to change in urban land cover (LC) structures. VECLS is first tested with a computer simulated three class endmember considering four bands having small, medium and large variability with three different spatial resolutions. The technique is next validated with real datasets of IKONOS, Landsat ETM+ and MODIS. The results show that correlation between actual and estimated proportion is higher by an average of 0.25 for the artificial datasets compared to a situation where variability is not considered. With IKONOS, Landsat ETM+ and MODIS data, the average correlation increased by 0.15 for 2 and 3 classes and by 0.19 for 4 classes, when compared to single endmember per class. (C) 2013 COSPAR. Published by Elsevier Ltd. All rights reserved.

Flexibility in Food Extraction Techniques in Urban Free-Ranging Bonnet Macaques, Macaca radiata

Non-human primate populations, other than responding appropriately to naturally occurring challenges, also need to cope with anthropogenic factors such as environmental pollution, resource depletion, and habitat destruction. Populations and individuals are likely to show considerable variations in food extraction abilities, with some populations and individuals more efficient than others at exploiting a set of resources. In this study, we examined among urban free-ranging bonnet macaques, Macaca radiata (a) local differences in food extraction abilities, (b) between-individual variation and within-individual consistency in problem-solving success and the underlying problem-solving characteristics, and (c) behavioral patterns associated with higher efficiency in food extraction. When presented with novel food extraction tasks, the urban macaques having more frequent exposure to novel physical objects in their surroundings, extracted food material from PET bottles and also solved another food extraction task (i.e., extracting an orange from a wire mesh box), more often than those living under more natural conditions. Adults solved the tasks more frequently than juveniles, and females more frequently than males. Both solution-technique and problem-solving characteristics varied across individuals but remained consistent within each individual across the successive presentations of PET bottles. The macaques that solved the tasks showed lesser within-individual variation in their food extraction behavior as compared to those that failed to solve the tasks. A few macaques appropriately modified their problem-solving behavior in accordance with the task requirements and solved the modified versions of the tasks without trial-and-error learning. These observations are ecologically relevant - they demonstrate considerable local differences in food extraction abilities, between-individual variation and within-individual consistency in food extraction techniques among free-ranging bonnet macaques, possibly affecting the species' local adaptability and resilience to environmental changes.

Synergistic effect of static magnetic field and HA-Fe3O4 magnetic composites on viability of S. aureus and E. coli bacteria

In addressing the issue of prosthetic infection, this work demonstrated the synergistic effect of the application of static magnetic field (SMF) and ferrimagnetic substrate properties on the bactericidal property in vitro. This aspect was studied using hydroxyapatite (HA)-xFe(3)O(4) (x=10, 20, and 40 wt.%) substrates, which have different saturation magnetization properties. During bacteria culture experiments, 100 mT SMF was applied to growth medium (with HA-xFe(3)O(4) substrate) in vitro for 30, 120, and 240 min. A combination of MTT assay, membrane rupture assays, live/dead assay, and fluorescence microscopic analysis showed that the bactericidal effect of SMF increases with the exposure duration as well as increasing Fe3O4 content in biomaterial substrates. Importantly, the synergistic bactericidal effect was found to be independent of bacterial cell type, as similar qualitative trend is measured with both gram negative Escherichia coli (E. coli) and gram positive Staphylococcus aureus (S. aureus) strains. The reduction in E. coli viability was 83% higher on HA-40 Wt % Fe3O4 composite after 4 h exposure to SMF as compared to nonexposed control. Interestingly, any statistically significant difference in ROS was not observed in bacterial growth medium after magnetic field exposure, indicating the absence of ROS enhancement due to magnetic field. Overall, this study illustrates significant role being played by magnetic substrate compositions towards bactericidal property than by magnetic field exposure alone. (c) 2013 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 102B: 524-532, 2014.

An oxygen evolution Co-Ac catalyst - the synergistic effect of phosphate ions

Formation of an amorphous cobalt based oxygen evolution catalyst called Co-Pi has been recently reported from a neutral phosphate buffer solution containing Co2+. But the concentration of Co2+ is as low as 0.5 mM due to poor solubility of a cobalt salt in phosphate medium. In the present study, a cobalt acetate based oxygen evolution catalyst (Co-Ac) is prepared from a neutral acetate buffer solution, where the solubility of Co2+ is very high (>100 times in comparison with phosphate buffer solution). The Co-Ac possesses better catalytic activity than the Co-Pi with an additional advantage of easy bulk scale preparation. The comparative studies on the oxygen evolution reaction (OER) activity of Co-Ac and Co-Pi in phosphate and acetate buffer electrolytes reveal that the Co-Ac exhibits enhanced synergistic catalytic activity in phosphate solution, probably due to partial substitution of acetate in the catalyst layer by phosphate, resulting in the formation of a Co-Ac-Pi catalyst.

Synergistic electrochemical activity of titanium carbide and carbon towards fuel cell reactions

Titanium carbide (TiC) is an electrically conducting refractory interstitial compound possessing several unique properties. A cost-effective, efficient and non-Pt electrocatalyst based on TiC is explored and the multi-functionality of TiC towards various electrochemical reactions that are of significant interest in low temperature fuel cells is studied. Ameliorated activities towards oxygen reduction reaction (ORR) and borohydride oxidation are observed with TiC-carbon composites. High sensitivity and selectivity towards ORR have been demonstrated with very good methanol tolerance. The charge transfer interactions between TiC and carbon seem to play a vital role in the improved activity as compared to their individual counterparts. The present study opens up a way to realize completely Pt-free borohydride fuel cell architecture.