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This paper considers the architecture of clusters and related message-passing (MP) software algorithms and their effect on performance (speedup and efficiency) of cluster computing (CC). We present new architectures for multi-segm...
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This paper considers the architecture of clusters and related message-passing (MP) software algorithms and their effect on performance (speedup and efficiency) of cluster computing (CC). We present new architectures for multi-segment Ethernet clusters and new MP algorithms which fit these architectures. The multiple segments (e.g. commodity hubs) connect com- modity processor nodes so as to allow MP to be highly parallelized by avoiding network contention and collisions in many applications where the all-gather and other collective op- erations are central. We analyze all-gather in some detail. and present new network topologies and new MP algorithms to minimize latency. The new topologies are based on a design, called two-by-four nets (2 × 4 nets), by Compbionics. An integrated MP software system, called Reduced Overhead Cluster Communication (ROCC), which embodies the MP algorithms is also described. In brief, 2 × 4 nets are networks of “supernodes”, called 2 × 4's, each having 4 processors on 2 segments and segments usually being Ethernet hubs. The supernodes are typically connected to form rings or tori of supernodes. We present actual test results and supporting analyses to demonstrate that 2 × 4 nets with the ROCC MP software are faster than many existing clusters and generally less costly.
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Carbon fiber (CF) reinforced bulk metallic glass matrix composites (BMGMCs) have received widespread attention due to their light weight, but subsequent development is facing urgent challenges of uncontrollable interface reaction ...
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Carbon fiber (CF) reinforced bulk metallic glass matrix composites (BMGMCs) have received widespread attention due to their light weight, but subsequent development is facing urgent challenges of uncontrollable interface reaction and poor plasticity. Here, we report a three-dimensional CF-reinforced Mg-based BMGMC, which significantly improves the microstructure and compressive plasticity by adjusting the pressure infiltration parameters. It has been found that the electroless copper plating improves the wettability of the CF and the melt without inducing the crystallization of the matrix, in spite of the partially dissolving and diffusing of the coating to the matrix. Under a similar infiltration pressure difference, high vacuum conditions are beneficial to reduce the capillary resistance of the porous CF preform, thereby improving the formability of BMGMC. Compression test results prove that the introduction of three-dimensional CF effectively improves the plasticity of the composite material and reduces its brittleness tendency. It can be attributed to the fact that the carbon fibers distributed in different directions effectively bridge the multi-directional cracks and prevent the early rapid shear band propagation. The present work provides meaningful enlightenment for the development of CF-reinforced BMGMC materials.
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Visualizing 3D time-varying fluid datasets is difficult because of the immense amount of data to be processed and understood. These datasets contain many evolving amorphous regions, and it is difficult to observe patterns and visu...
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Visualizing 3D time-varying fluid datasets is difficult because of the immense amount of data to be processed and understood. These datasets contain many evolving amorphous regions, and it is difficult to observe patterns and visually follow regions of interest. In this paper, we present a technique which isolates and tracks full-volume representations of regions of interest from 3D regular and curvilinear computational fluid dynamics datasets. Connected voxel regions ("features") are extracted from each time step and matched to features in subsequent time steps. Spatial overlap is used to determine the matching. The features from each time step are stored in octree forests to speed up the matching process. Once the features have been identified and tracked, the properties of the features and their evolutionary history can be computed. This information can be used to enhance isosurface visualization and volume rendering by color coding individual regions. We demonstrate the algorithm on four 3D time-varying simulations from ongoing research in computational fluid dynamics and show how tracking can significantly improve and facilitate the processing of massive datasets.
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This paper deals with error estimation of the boundary element method (BEM) and the h adaptive boundary elements. The various error sources in the BEM are discussed, and the upper bound of the BEM solution error is derived by mean...
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This paper deals with error estimation of the boundary element method (BEM) and the h adaptive boundary elements. The various error sources in the BEM are discussed, and the upper bound of the BEM solution error is derived by means of the interpolation error of the BE solution. A new error estimator is presented in the paper by using post-processing data from the standard BEM solutions. Two adaptive algorithms, the standard h adaptive and the h-hierarchical adaptive, are implemented based on direct boundary element method for two-dimensional elasticity problems. A few numerical examples are used to compare the accuracy of the proposed adaptive algorithm, as well as the error estimator. The stability of the BEM system matrix, which may deteriorate due to the introduction of h-hierarchical interpolation functions, has also been studied.
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Reservoir characterization refers to the process of quantitatively assigning reservoir properties using all available field data. Artificial neural networks (ANN) have recently been introduced to solve reservoir characterization p...
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Reservoir characterization refers to the process of quantitatively assigning reservoir properties using all available field data. Artificial neural networks (ANN) have recently been introduced to solve reservoir characterization problems dealing with the complex underlying relationships inherent in well log data. Despite the utility of ANNs, the current limitation is that most existing applications simply focus on directly implementing existing ANN models instead of improving/customizing them to fit the specific reservoir characterization tasks at hand. In this paper, we propose a novel intelligent framework that integrates fuzzy ranking (FR) and multilayer perceptron (MLP) neural networks for reservoir characterization. FR can automatically identify a minimum subset of well log data as neural inputs, and the MLP is trained to learn the complex correlations from the selected well log data to a target reservoir property. FR guarantees the selection of the optimal subset of representative data from the overall well log data set for the characterization of a specific reservoir property; and, this implicitly improves the modeling and predication accuracy of the MLP. In addition, a growing number of industrial agencies are implementing geographic information systems (CIS) in field data management; and, we have designed the GFAR solution (CIS-based FR ANN Reservoir characterization solution) system, which integrates the proposed framework into a GIS system that provides an efficient characterization solution. Three separate petroleum wells from southwestern Alberta, Canada, were used in the presented case study of reservoir porosity characterization. Our experiments demonstrate that our method can generate reliable results.
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Monolayer films of nucleic acids on solid supports are encountered in a
range of diagnostic and bioanalytical applications. These applications often rely on
elevated temperatures to improve performance; moreover, studies at elevat...
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Monolayer films of nucleic acids on solid supports are encountered in a
range of diagnostic and bioanalytical applications. These applications often rely on
elevated temperatures to improve performance; moreover, studies at elevated
temperatures can provide fundamental information on layer organization and
functionality. To support such applications, this study compares thermostability of
oligonucleotide monolayers immobilized to gold by first coating the gold with a
nanometer-thick film (an “anchor layer”) of a polymercaptosiloxane, to which DNA
oligonucleotides are subsequently tethered through maleimide−thiol conjugation, with thermostability of monolayers formed via
widely used attachment through a terminal thiol moiety on the DNA. The temperature range covered is from 25 to 90 °C. After
confirming stability of immobilization and, more importantly, retention of hybridization activity even under the harshest
conditions investigated, these thermostable films are used to demonstrate measurements of (1) reversible surface melting
transitions and (2) temperature dependence of competitive hybridization, when fully matched and mismatched sequences
compete for binding to immobilized DNA oligonucleotides. The competitive hybridization experiments reveal a pronounced
impact of temperature on rates of approach to equilibrium, with kinetic freezing into nonequilibrium states close to room
temperature and rapid approach to equilibrium at elevated temperatures. Modeling of competitive surface hybridization equilibria
using thermodynamic parameters derived from surface melting transitions of the individual sequences is also discussed.
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Troponin T (TnT) is a striated muscle-specific protein and an abundant component of the myofilaments. Nonmyofilament-associated TnT is rapidly degraded in myocytes, implying an importance in the maintenance of the cellular environ...
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Troponin T (TnT) is a striated muscle-specific protein and an abundant component of the myofilaments. Nonmyofilament-associated TnT is rapidly degraded in myocytes, implying an importance in the maintenance of the cellular environment. However, if the level of nonmyofilament-associated TnT or TnT fragments exceeds the degradation capacity, it may cause cytotoxicity. To investigate this hypothesis, we constructed bicistronic vectors to express different portions of TnT polypeptide chain, together with nonfusion green fluorescent protein as a tracer for the transfection. Cytotoxicity of the TnT fragments was studied through forced expression in C_2C_(12) myoblasts and human embryonic kidney-293 nonmuscle cells and examination of the viability of the transfected cells. The results demonstrated that, in the absence of myofilaments, the conserved COOH-terminal and middle fragments of TnT were highly effective on inducing cell death via apoptosis, whereas the NH2-terminal variable region was not. As combined effects, nonmyofilament-associated intact cardiac TnT and a COOH-terminal truncated slow TnT fragment found in Amish nemaline myopathy exhibited intermediate cytotoxicity. A particular significance of this finding is that peak releases of TnT or TnT fragments from decomposition of a large number of myofibrils in acute myocardial infarction may breach the cellular protection of proteolytic degradation and result in apoptosis as a potential cause for the loss of cardiomyocytes.
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Thermal performance of two phase change material (PCM) composites, mixed type PCM-gypsum and shape-stabilized PCM plates, has been numerically evaluated in a passive solar building in Beijing with an enthalpy model. Effects of the...
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Thermal performance of two phase change material (PCM) composites, mixed type PCM-gypsum and shape-stabilized PCM plates, has been numerically evaluated in a passive solar building in Beijing with an enthalpy model. Effects of the melting temperature and phase transition zone of the PCM are analyzed and a comparison between the two types of PCM composites is performed. The results show that: (1) for the present conditions, the optimal melting temperature is about 21 °℃; (2) PCM composites with a narrow phase transition zone provide better thermal performance; (3) both mixed type PCM-gypsum and shape-stabilized PCM plates effectively shave the indoor temperature swing by 46% and 56%, respectively; (4) the shape-stabilized phase change material (SSPCM) plates respond more rapidly than the mixed type PCM-gypsum and prove to be thermally more effective in terms of utilizing the latent heat.
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In the past years, we have developed neural control strategies and relevant image processing methods. Neural control by a neurocomputer has been used in the mobile vehicle control system. The hardware neurocomputer RN-2000 is the ...
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In the past years, we have developed neural control strategies and relevant image processing methods. Neural control by a neurocomputer has been used in the mobile vehicle control system. The hardware neurocomputer RN-2000 is the kernel part of the system. The purpose of this paper is to solve the problem of how to realize the hardware neurocomputer by back-propagation (BP) neural network learning on-line. The strategy presented in this paper is based on modifying the past patterns and adjusting the content of the driving patterns by a new algorithm proposed. Learning happens during the driving procedure of the mobile vehicle. This research shows the possibility of the neurocomputer whose the BP neural network is inside to learn human knowledge on-line by the aid of software.
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Visualizing 3D continuum or time-varying simulation (scalar) datasets is difficult because of the immense amount of data to be processed and understood. Furthermore, these datasets may contain many evolving amorphous regions, maki...
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Visualizing 3D continuum or time-varying simulation (scalar) datasets is difficult because of the immense amount of data to be processed and understood. Furthermore, these datasets may contain many evolving amorphous regions, making it difficult to visually follow features of interest. In this paper, we present a process for analyzing continuum datasets and review some of our previous work on feature tracking. We show how the tracking information can be used to enhance standard rendering and enable new visualizations. The tracking is demonstrated on different application domains including turbulence, weather and inlet design.
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