Lithospheric deformation in the western United States is one of the best examples of diffuse continental tectonics that deviate from the plate tectonics paradigm. Conceptually, diffuse continental deformation is known...
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Lithospheric deformation in the western United States is one of the best examples of diffuse continental tectonics that deviate from the plate tectonics paradigm. Conceptually, diffuse continental deformation is known to result from (1) weak and heterogeneous rheology of continents and (2) driving forces that arise from plate boundaries as well as within the continental lithosphere. However, the dynamic interplay of continental rheology and driving forces, hence the geodynamics of continental tectonics, remains poorly understood. The heterogeneous rheology and multiple driving forces cause continents to deform over different spatiotemporal scales with different physical processes, yet most geodynamic models for continental tectonic avoid dealing with such multiphysics partly because of (1) the limited observational constraints of lithospheric structure and deformation, and (2) high demands on computing alaorithms and resources. These constraints, however, have relaxed significantly in recent years to permit exploration of some of the multi-scale physics governing continental tectonics. Here we present preliminary results of modeling multi-scale tectonics in the western United States using parallel finite element computation. In a 3D subcontinental-scale model, we used fine numerical meshes to incorporate all major tectonic boundaries and rheological heterogeneities in the model to explore their interplay with tectonic driving forces in controlling active tectonics in the western US. In another model for the entire San Andreas Fault system, we explored strain localization and simulated fault behavior at multi-timescales ranging from rupture in seconds to secular fault creep in tens of thousands of years. These models can help to integrate data grids with distributed high-performance computing resources in the emerging geosciences cyberinfrastructure. (c) 2007 Elsevier B.V. All rights reserved.
We developed a parallel computing method of the magnetic field for rotating machines by using the 3-D finite element method (FEM) with edge elements. In this paper, we describe the outline of the developed method and ...
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We developed a parallel computing method of the magnetic field for rotating machines by using the 3-D finite element method (FEM) with edge elements. In this paper, we describe the outline of the developed method and an optimization of the method for the Earth simulator, which is a vector-type parallel supercomputer in Japan. Moreover, the performance of the proposed method running on the Earth simulator is quantitatively clarified.
We discuss the use of parallel computing in Asian option pricing and evaluate the efficiency of various algorithms. We only focus on "backward-starting fixed strike" Asian options that are continuously avera...
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We discuss the use of parallel computing in Asian option pricing and evaluate the efficiency of various algorithms. We only focus on "backward-starting fixed strike" Asian options that are continuously averaged. We implement a partial differential equation (PDE) approach that involves a single state variable to price the Asian option, and implement the same methodology to price a standard European option to check for accuracy. A parabolic PDE is solved by using both explicit and Crank-Nicolson's implicit finite-difference methods. In particular, we look for algorithms designed for implementing the computations in massively parallel processors (MPP). We evaluate the performance of the algorithms by comparing the numerical results with respect to accuracy and wall-clock time of code executions. Codes are executed on a Linux PC cluster. (c) 2006 Elsevier B.V. All rights reserved.
Railway wheel-rail contact simulations are the most important and time-consuming tasks when simulating the system dynamics of vehicles. parallel computing is a good approach for improving the numerical computing speed...
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Railway wheel-rail contact simulations are the most important and time-consuming tasks when simulating the system dynamics of vehicles. parallel computing is a good approach for improving the numerical computing speed. This paper reports the advances in parallel computing of the wheel-rail contact simulations. The proposed method uses OpenMP to parallelise the multiple contact points of all the wheel-rail interfaces of a locomotive model. The method has been implemented in the vehicle system dynamics simulation package GENSYS. Simulations were conducted using two numerical solvers (4th Runge-Kutta and HeunC) and a maximum of four computer cores. Simulation cases have shown exactly the same numerical results using serial computing and parallel computing, which prove the effectiveness of the parallel computing method. The HeunC solver achieved the same simulation results and is 3.5 times faster than the 4th Runge-Kutta method. Simulation results obtained from both numerical solvers show that parallel computing using 2, 3 and 4 computer cores can improve the simulation speeds by roughly 29, 39 and 41%, respectively. There is an apparent diminishing of the rate of improvement due to the increase of the communication resource overhead when more computer cores are used. Using up to four computer cores does not require revision of the GENSYS code, and simulations can be executed using personal computers.
Due to the high computing demand of whole-trip train dynamics simulations and the iterative nature of optimizations, whole-trip train dynamics optimizations using sequential computing schemes are practically impossibl...
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Due to the high computing demand of whole-trip train dynamics simulations and the iterative nature of optimizations, whole-trip train dynamics optimizations using sequential computing schemes are practically impossible. This paper reports advancements in whole-trip train dynamics optimizations enabled by using the parallel computing technique. A parallel computing scheme for whole-trip train dynamics optimizations is presented and discussed. Two case studies using parallel multiobjective particle swarm optimization (pMOPSO) and parallel multiobjective genetic algorithm (pMOGA), respectively, were performed to optimize a friction draft gear design. Linear speed-up was achieved by using parallel computing to cut down the computing time from 18 months to just 11 days. Optimized results using pMOPSO and pMOGA were in agreement with each other;Pareto fronts were identified to provide technical evidence for railway manufacturers and operators.
Bioinformatics allows and encourages the application of many different parallel computing approaches. This special issue brings together high-quality state-of-the-art contributions about parallel computing in bioinfor...
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Bioinformatics allows and encourages the application of many different parallel computing approaches. This special issue brings together high-quality state-of-the-art contributions about parallel computing in bioinformatics, from different points of view or perspectives, that is, from high-performance, heterogeneous, and cloud computing. The special issue collects considerably extended and improved versions of the best papers, accepted and presented in PBio 2018 (6th International Workshop on parallelism in Bioinformatics, and part of EuroMPI 2018). The domains and topics covered in these five papers are timely and important, and the authors have done an excellent job of presenting the material.
To make sure system stability and reduce active power loss are two important tasks of voltage/reactive power optimization control. To some extent, the two objectives contradict each other, and it is difficult to asses...
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To make sure system stability and reduce active power loss are two important tasks of voltage/reactive power optimization control. To some extent, the two objectives contradict each other, and it is difficult to assess 'voltage stability considering load changing. A novel time-varied coordinated voltage/reactive power control model based on parallel E-dominatAon multi-objective evolutionary algorithm is presented in this paper. The model calculates load power margin by Primal-dual interior point nonlinear programming, which can assess 'voltage stability completely and provides operators more accurate information. Simulation results of IEEE-1.4 bus, IEEE-30 bus and IEEE-118 bus systems show that this approach is valid and effective.
We developed a parallel computing method for rapid eddy current analyses using the A - phi method. In this paper, the outline of the developed method is described. Moreover, the performance of the proposed method runn...
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We developed a parallel computing method for rapid eddy current analyses using the A - phi method. In this paper, the outline of the developed method is described. Moreover, the performance of the proposed method running on a PC cluster is quantitatively clarified through the analyses of some rotating machines.
This paper deals with the discretization of the problem of mould filling in iron foundry and its numerical solution using a Schwarz domain decomposition method. An adapted technique for domain decomposition methods th...
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This paper deals with the discretization of the problem of mould filling in iron foundry and its numerical solution using a Schwarz domain decomposition method. An adapted technique for domain decomposition methods that suits the discretization in time by the method of characteristics is introduced. Furthermore, the projection method is used to reduce the computation time. Finally, numerical experiments show and validate the effectiveness of the proposed scheme.
Fully discretized models for image reconstruction from projections give rise to huge and sparse nonlinear optimization problems. We study the use of parallel and vector supercomputers for the iterative reconstruction ...
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Fully discretized models for image reconstruction from projections give rise to huge and sparse nonlinear optimization problems. We study the use of parallel and vector supercomputers for the iterative reconstruction of medical images. A block-iterative version of the Multiplicative Algebraic Reconstruction Technique (MART) is implemented on a CRAY X-MP/48. The implementation exploits the block structure of the algorithm which allows us to take advantage both of the vector architecture of the computer and of the multiple processors for parallel computations. Results indicate that block-iterative algorithms are suitable for parallel and vector implementations and can reconstruct with relative efficiency highly discretized images which give rise to very large optimization problems.
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