In this paper, the three dimensional parallel Realistic Failure Process Analysis (RFPA(3D)-parallel) code based on micromechanical model is employed to investigate the bonding behavior in FRP sheet bonded to concrete ...
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In this paper, the three dimensional parallel Realistic Failure Process Analysis (RFPA(3D)-parallel) code based on micromechanical model is employed to investigate the bonding behavior in FRP sheet bonded to concrete in single shear test. In the model, the heterogeneity of brittle disordered material at a meso-scale was taken into consideration in order to realistically demonstrate the mechanical characteristics of FRP-to-concrete. Modified Mohr-coulomb strength criterion with tension cut-off, where a stressed element can damage in shear or in tension, was adopted and a stiffness degradation approach was used to simulate the initiation, propagation and growth of microcracks in the model. In addition, a Master-Slave parallel operation control technique was adopted to implement the parallel computation of a large numerical model. parallel computational results of debonding of FRP-concrete visually reproduce the spatial and temporal debonding failure progression of microcracks in FRP sheet bonded to concrete, which agrees well with the existing testing results in laboratory. The numerical approach in this study provides a useful tool for enhancing our understanding of cracking and debonding failure process and mechanism of FRP-concrete and our ability to predict mechanical performance and reliability of these FRP sheet bonded to concrete structures.
There is considerable interest in speeding up the dynamic simulation of power systems for on-line security assessment purposes. While software is being developed for automatically detecting parallelism in an otherwise...
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There is considerable interest in speeding up the dynamic simulation of power systems for on-line security assessment purposes. While software is being developed for automatically detecting parallelism in an otherwise serial code, research in developing parallel numerical algorithms is also useful. In this paper we develop a sequential algorithm that can be automatically converted (autotasked) to execute in parallel We have also adapted an explicitly parallel algorithm for simulating the dynamics of a multimachine power system. Both were multistep predictor corrector algorithms and were implemented on a Cray 2 machine with four processors. Simulations were performed on four test systems (3, 10, 17 and 50 machines). While the speedups by both techniques are comparable, it is believed that continued research in numerical algorithms and their practical implementation is warranted. Autotasking may not always ensure the desirable spedups, since it may run into difficulties in certain instances.
This paper presents a new way to compute simplicial and Tukey data depths using Open Multi-Processing parallelization, which makes it practical to compute point depths for tens of thousands of points. The definition o...
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This paper presents a new way to compute simplicial and Tukey data depths using Open Multi-Processing parallelization, which makes it practical to compute point depths for tens of thousands of points. The definition of point depth is the order statistic depth of a single point, here in two dimensions. Using the point depths, the regional depth characteristics of the dataset as a whole can be explored. Using this new methodology, fast parallel computation of both simplicial depth and Tukey depth for a dataset of n points has time complexity O(n(2)logn) with O(n) space, which is practical for n up to 100,000. Obtaining depths for a large number of points in a faster manner by parallel computation supports identifying the central region quickly, because the points of maximum depth are known. The point depth computation identifies the depths of selected spoke segments around each origin point. These spoke depths are used to create new visualizations of depth characteristics and contour depths without adding virtual points.
A parallel computation method has been proposed for the mixing and segregation of granular mixture included in gas and liquid flows. In this method, a three-dimensional (3D) computational volume is decomposed into mul...
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A parallel computation method has been proposed for the mixing and segregation of granular mixture included in gas and liquid flows. In this method, a three-dimensional (3D) computational volume is decomposed into multiple sub-blocks and their geometries are represented by 3D body-fitted coordinates. The fluid-particle interactions are treated by two types of models: a two-way model for liquid-solid flows and a one-way model in case of gas-solid flows. The computations of the particle motions in the multiple sub-blocks are executed simultaneously on the basis of the distinct element method (DEM). Since a graphic process is also executed as one of the parallel jobs, the particle distributions can be visualized during the computations. The computational method was applied to the gas-solid flows consisting of different diameters and densities in the horizontal and inclined cylinders rotating around their axes. From the comparison with the experimental results, nearly uniform mixing and particle segregation are successfully predicted in the oscillating liquid flows. In addition, it has been indicated that the particle pathline is very effective to visualize and understand the flow patterns of the particles with different properties. The result of the computations for the liquid-solid flows demonstrated that the vertical segregation of the non-uniform particles is reasonably reproduced.
A parallel algorithm for solving systems of coupled Lyapunov equations associated with linear jump parameter systems is introduced. The recursive scheme is based on solving independent reduced-order Lyapunov equations...
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A parallel algorithm for solving systems of coupled Lyapunov equations associated with linear jump parameter systems is introduced. The recursive scheme is based on solving independent reduced-order Lyapunov equations. Monotonicity of convergence is established.
This paper discusses the parallel and efficient computation of macroeconomic models, with an emphasis on solving sovereign default models. Our motivation is twofold. First, we aim to streamline complex numerical model...
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This paper discusses the parallel and efficient computation of macroeconomic models, with an emphasis on solving sovereign default models. Our motivation is twofold. First, we aim to streamline complex numerical models in a parallel computation fashion. Second, we want to unleash the power of graphic processing unit but bypass the steep learning and implementation costs of languages like C++ and Compute Unified Device Architecture (CUDA) in economic research. To this end, we propose a framework for efficient parallel computing with the modern language Julia. The paper offers a detailed analysis of parallel computing, Julia-style acceleration techniques, and coding recommendations. The Julia with CUDA benchmark shows a substantial speedup of over 1000 times compared to standard Julia that runs on a CPU. Our Julia with CUDA's implementation is twice as fast as that of the C++ Standard parallel Library. We provide an accompanying GitHub repository with the codes and the benchmarks used in this paper.
Recent technological development has drawn the attention of many researchers in computer science to problems of parallel computation. Three possible generalizations of the rule that no 2 different processors may writ...
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Recent technological development has drawn the attention of many researchers in computer science to problems of parallel computation. Three possible generalizations of the rule that no 2 different processors may write simultaneously into the same memory location are shown: 1. weak conflict-resolution rule, in which simultaneous writing is permitted only to selected memory locations which can contain the numbers 0 or 1 only; 2. equality conflict-resolution rule, in which simultaneous writing into the same memory location is permitted, provided all processors involved store the same value; and 3. priority conflict-resolution rule, where processors are linearly ordered according to their priorities. It is apparent that each of these rules leads, in turn, to the next one. It is demonstrated, at the expense of the number of processors, that the computational power of all of these rules is equal in a certain sense. Five theorems are presented.
For modern public key cryptographic systems, the modular cascade exponentiation [formula omitted] is one of the most important arithmetic fundamentals to ensure security. However, the large computing effort needed by ...
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In this paper we will consider the effect of introducing parallel computers to solve optimisation problems. We briefly highlight four situations where most improvements are likely. We consider the possible interaction...
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A neural network consists of many neurons connected by synapses. It is able to process information and generate a specific pattern of electrical activity. To analyze its interior structure and exterior properties, one...
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ISBN:
(纸本)0780374908
A neural network consists of many neurons connected by synapses. It is able to process information and generate a specific pattern of electrical activity. To analyze its interior structure and exterior properties, one computer simulator was implemented. As the neural network is complicated and the simulation is time consuming, so data structure and computation scheme are critical to simulation process. In this paper, data structure is designed sharable and reusable, and parallel computation is applied to match the data structure. With the data structure and parallel computation, the simulation is made much more efficient and high performance was achieved.
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