A parallel surface meshing algorithm is proposed by exploiting the parallelism within the meshing process of a surface, which is more efficient than the conventional scheme that meshes surfaces individually. One integ...
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A parallel surface meshing algorithm is proposed by exploiting the parallelism within the meshing process of a surface, which is more efficient than the conventional scheme that meshes surfaces individually. One integral part is the domain decomposition approach adopted, which ensures no small inter-domain angles;therefore, the parallel meshing procedure can fix the inter-domain boundary without compromising mesh quality. Combining the parallel surface mesher with the parallel tetrahedral mesher and improver developed previously, a parallel preprocessing pipeline for large-scale simulations is set up. It only consumes minutes to prepare a mesh containing hundreds of millions of elements. (C) 2015 Elsevier Ltd. All rights reserved.
An efficient two-level domain decomposition parallel algorithm is suggested to solve large-DOF structural problems with nonlinear material models generating unsymmetric tangent matrices, such as a group of plastic-dam...
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An efficient two-level domain decomposition parallel algorithm is suggested to solve large-DOF structural problems with nonlinear material models generating unsymmetric tangent matrices, such as a group of plastic-damage material models. The parallel version of the stabilized bi-conjugate gradient method is developed to solve unsymmetric coarse problems iteratively. In the present approach the coarse DOF system is solved parallelly on each processor rather than the whole system equation to minimize the data communication between processors, which is appropriate to maintain the computing performance on a non-supercomputer level cluster system. The performance test results show that the suggested algorithm provides scalability on computing performance and an efficient approach to solve large-DOF nonlinear structural problems on a cluster system.
A unified parallel algorithm for grid adaptation by local refinement/coarsening is presented. It is designed to be independent from the type of the grid. This is achieved by employing a generic data template that can ...
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A unified parallel algorithm for grid adaptation by local refinement/coarsening is presented. It is designed to be independent from the type of the grid. This is achieved by employing a generic data template that can be configured to capture the data structures for any computational grid regardless of structure and dimensionality. Furthermore, the algorithm itself is specified in terms of generic parallel primitives that are completely independent of the underlying parallel architecture. The unified parallel algorithm is employed for dynamic adaptation of three-dimensional unstructured tetrahedral grids on a partitioned memory multiple-instruction multiple-data architecture. Performance results are presented for the Intel iPSC/860.
In this paper, we consider the minimum partial dominating set problem in unit disk graphs (MinPDS-UD). Given a set of points V on the plane with vertical bar V vertical bar = n, two points in V are adjacent in the uni...
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ISBN:
(纸本)9783030926816;9783030926809
In this paper, we consider the minimum partial dominating set problem in unit disk graphs (MinPDS-UD). Given a set of points V on the plane with vertical bar V vertical bar = n, two points in V are adjacent in the unit disk graph if their Euclidean distance is no larger than one unit length. A point dominates itself and all its neighboring points. For an integer k <= n, the goal of MinPDS-UD is to find a minimum subset of points D subset of V such that at least k points are dominated by D. We present the first parallel algorithm for MinPDS-UD. It runs in O(log n) rounds on O(n) machines, and achieves a constant approximation ratio.
Automated guided vehicles are widely used in various applications, especially in manufacturing. In this paper, we present a novel parallel algorithm for multi-AGV systems. The overall structure is composed of three pa...
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Automated guided vehicles are widely used in various applications, especially in manufacturing. In this paper, we present a novel parallel algorithm for multi-AGV systems. The overall structure is composed of three parts: task assignment, path planning, and vehicle navigation. According to the priorities of AGVs, a greedy method is introduced to assign jobs. For path planning, a mixed-integer programming model of a multi-AGV system is formulated, which can be transformed into a series of sub-problems under certain conditions. Then, an improved routing method with a penalty item is adopted to generate the optimal paths of AGVs. To avoid collisions between vehicles, a simple and effective control method based on resource locking is proposed under the premise of parallelization. Furthermore, we design the experiments according to the warehousing systems. Various practical simulations are performed to illustrate the efficiency and robustness of the new algorithm.
Numerical Manifold Method (NMM) has gained widespread application in engineering practice due to its capacity to effectively address both continuous and discontinuous problems in a unified framework. With the advancem...
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Numerical Manifold Method (NMM) has gained widespread application in engineering practice due to its capacity to effectively address both continuous and discontinuous problems in a unified framework. With the advancement of 3D-NMM, there remains a deficiency in ready-made preprocessing tools. Hence, the generation of 3D manifold elements (MEs) is the primary prerequisite for 3D-NMM. In this study, a parallel algorithm to generate the MEs is proposed. Firstly, a novel 3D block identification algorithm is developed to improve the modeling efficiency. Then, 3D joint networks are simulated using the geological statistical results. Thirdly, the mathematical cover system is constructed using uniformly regular hexahedral meshes. Subsequently, the physical domain is cut using the Boolean algorithm to generate the related manifold blocks (MBs) and the Union -Find algorithm is used to determine the relationship of MBs with mathematical patches (MPs) and physical patches (PPs). The proposed program incorporates the OpenMP parallel library for CPU parallelization to enhance its efficiency and the OpenGL library is used to build a real-time visualization program. Finally, the proposed program is validated using several representative examples, and the obtained results demonstrate its efficient capability in generating MEs.
This paper proposes a parallel algorithm, called KDOP (K-DimensionalOptimal parallel algorithm), to solve a general class of recurrence equations efficiently. The KDOP algorithm partitions the computation into a serie...
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This paper proposes a parallel algorithm, called KDOP (K-DimensionalOptimal parallel algorithm), to solve a general class of recurrence equations efficiently. The KDOP algorithm partitions the computation into a series of sub-computations, each of which is executed in the fashion that all the processors work simultaneously with each one executing an optimal sequential algorithm to solve a subcomputation task. The algorithm solves the equations in O(N/p)steps in EREW PRAM model (Exclusive Read Exclusive Write parallel Ran-dom Access Machine model) using palgorithm (itsspeedup is O(p)) in the case of palgorithm can be implemented on machines with multiple processing elements or pipelined vector machines with parallel memory systems.
This work is concerned with the convergence/stability analysis of a parallel algorithm which is used to solve the incompressible Navier-Stokes problem. This relies on a splitting of the main differential operator, tha...
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This work is concerned with the convergence/stability analysis of a parallel algorithm which is used to solve the incompressible Navier-Stokes problem. This relies on a splitting of the main differential operator, thanks to which the most important difficulties (nonlinearity and incompressibility) can be considered independently. Thus, one is led to the formulation of subproblems of two kinds which can be solved simultaneously by two different processors. We prove conditional stability and convergence;this can serve to justify the accuracy of previous numerical results.
In cognitive radar network, a parallel algorithm can allocate idle spectrum to cognitive radars, but it often ignores the user's requirement. According to the graph theory, the topology of the network is divided i...
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In cognitive radar network, a parallel algorithm can allocate idle spectrum to cognitive radars, but it often ignores the user's requirement. According to the graph theory, the topology of the network is divided into two different groups. In the process of distributing spectrum, each group summarizes the distributed information after completing a distribution. When a user's demand is satisfied, every group is informed to not allocate the spectrum for the user anymore and deletes it from the topology at the same time. As a result, by deleting the node which the user's requirement has already been met, the other nodes which are interfered with the node on the same channel can participate into spectrum allocation. The improved algorithm can ensure high spectrum utilization taking a little time that is spent on the spectrum allocation. The simulation result shows that the spectrum utilization of the improved algorithm is higher than that of the traditional parallel algorithm, and the user's satisfaction increases greatly. Therefore, this paper aims to attempt to explore an improved parallel algorithm to resolve the problem by considering user's requirement.
The fixpoints of Galois connections induced by binary relational data are called formal con-cepts in formal concept analysis (FCA). Computing formal concepts is one of the most important issues in FCA, while Close-by-...
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The fixpoints of Galois connections induced by binary relational data are called formal con-cepts in formal concept analysis (FCA). Computing formal concepts is one of the most important issues in FCA, while Close-by-One (CbO) and its variants are usually considered as the most efficient serial algorithms for this task. Current approaches to parallelization of CbO-type algorithms such as PCbO (parallel CbO) usually enter the parallel stage after a serial stage which could be a possible bottleneck. In this paper, we propose a new parallel algorithm for computing formal concepts, which is composed of two parallel phases. The new algorithmparallelizes both the computations of the top L recursion levels and the workload distribution, which decouples worker threads from the main thread. We describe the algorithm and present an experimental evaluation of its performance and comparison with PCbO on various datasets. Results indicate that our algorithm performs better, espe-cially when a dataset is dense or has a large size.(c) 2021 Elsevier Inc. All rights reserved.
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