Parallel Processing a Three-Dimensional Free-Lagrange Code: a Case History

Mandell, D.A.; Trease, Harold E.

doi:10.1177/109434208900300206

Cited by 5 publications

(4 citation statements)

References 5 publications

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“…This means that the topology and physical properties are properly updated during the simulation process and the dynamic behavior of the fluid flow is adequately represented. These results are comparable to the ones obtained from the analytical and numerical solution of the Noh problem as well, which can be found in Mandal and Treas (1989), Ghemyr et al (1997), and Campbell and Shashkov (2003). However, it is important to mention that, in those studies, a fixed time-step method is used during the simulation process where all topological relations are reconstructed after each time step.…”

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confidence: 91%

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Toward 3D spatial dynamic field simulation within GIS using kinetic Voronoi diagram and Delaunay tetrahedralization

Beni

Mostafavi

Pouliot

et al. 2011

International Journal of Geographical Information Science

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Geographic information systems (GISs) are widely used for representation, management, and analysis of spatial data in many disciplines. In particular, geoscientists increasingly use these tools for data integration and management purposes in many environmental applications, ranging from water resources management to the study of global warming. Beyond these capabilities, geoscientists need to model and simulate three-dimensional (3D) dynamic fields and readily integrate those results with other relevant spatial information in order to have a better understanding of the environmental problems. However, GISs are very limited for the modeling and simulation of spatial fields, which are mostly 3D and dynamic. These limitations are mainly related to the existing GIS spatial data structures that are static and limited to 2D space. In order to overcome these limitations, we develop and implement a new kinetic 3D spatial data structure based on Delaunay tetrahedralization and a 3D Voronoi diagram to support a 3D dynamic field simulation within GISs. In this article, we describe in detail the different steps from discretization of a 3D continuous field to its numerical integration, based on an eventdriven method. For validation of the proposed spatial data structure itself and its potential for the simulation of a dynamic field, two case studies are presented in the article. According to our observations, during the simulation process, the data structure is maintained and the 3D spatial information is managed adequately. Furthermore, the results obtained from both experiments are very satisfactory and are comparable with the results obtained from other existing methods for the simulation of the same dynamic field. To conclude, we discuss the current challenges related to the development of the 3D kinetic data structure itself and its adaptation to 3D dynamic field simulation and suggest some solutions for its improvement.

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confidence: 91%

“…The new values of field variables are obtained from the discrete form of the governing equations in 3D space. Mandal and Treas (1989) have developed a discrete form of the above governing equations in 3D space for fluid dynamics with a fixed time step as…”

Section: International Journal Of Geographical Information Science 37mentioning

confidence: 99%

Toward 3D spatial dynamic field simulation within GIS using kinetic Voronoi diagram and Delaunay tetrahedralization

Beni

Mostafavi

Pouliot

et al. 2011

International Journal of Geographical Information Science

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“…Porting a large and complex application code from a uniprocessor to a multiprocessor machine is a difficult and timeconsuming task. Vectorizing and multitasking large codes on 'traditional' supercomputers such as the Cray-2 and Cray Y-MP still currently requires a high degree of expertise [52,53]. The implementation on MIMD distributed memory machines, in which data are passed between processors by an explicit message-passing scheme, is at least as difficult.…”

Section: Portability and Software Engineering Issuesmentioning

confidence: 99%

Characterizing the parallel performance of a large‐scale, particle‐in‐cell plasma simulation code

Walker

1990

Concurrency: Pract. Exper.

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The efficient implementation of particle‐in‐cell (PIC) plasma simulation codes on distributed memory concurrent computers is made difficult by the conflicting aims of balancing the computational load and minimizing interprocessor communication. This paper surveys previous work on PIC plasma simulation codes on advanced architecture computers, identifies the main issues in parallelizing such codes, and discusses different decomposition schemes. For MIMD concurrent computers the adaptive Eulerian (AE) decomposition scheme is attractive because it seeks to maintain approximate load balance dynamically while avoiding excessive non‐local communication. The load balance and communication characteristics of a large‐scale AE/PIC code on the hypercube are investigated by simulating the behavior of the parallel code on a Cray‐2. The results show that for the three‐dimensional problems studied, in which the particle distribution is highly inhomogeneous, the communication of data between the particle and mesh decompositions dominates the communication overhead. Performing the load balancing may also make a significant contribution to the concurrent overhead if the grain size is sufficiently small. The advantages of the simulation approach in investigating the behavior of concurrent large‐scale applications are discussed, together with portability and software engineering issues.

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“…The analysis of spatial points has recently been simplified with the development of computer recognition programs and visualization methods that can identify spatial points based on their spatial and temporal characteristics [15][16][17][18][19]. The resulting dataset, which is a set of points distributed in space, is known as a spatial point pattern.…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

Point Cluster Analysis Using a 3D Voronoi Diagram with Applications in Point Cloud Segmentation

Ying

et al. 2015

IJGI

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Three-dimensional (3D) point analysis and visualization is one of the most effective methods of point cluster detection and segmentation in geospatial datasets. However, serious scattering and clotting characteristics interfere with the visual detection of 3D point clusters. To overcome this problem, this study proposes the use of 3D Voronoi diagrams to analyze and visualize 3D points instead of the original data item. The proposed algorithm computes the cluster of 3D points by applying a set of 3D Voronoi cells to describe and quantify 3D points. The decompositions of point cloud of 3D models are guided by the 3D Voronoi cell parameters. The parameter values are mapped from the Voronoi cells to 3D points to show the spatial pattern and relationships; thus, a 3D point cluster pattern can be highlighted and easily recognized. To capture different cluster patterns, continuous progressive clusters and segmentations are tested. The 3D spatial relationship is shown to facilitate cluster detection. Furthermore, the generated segmentations of real 3D data cases are exploited to demonstrate the feasibility of our approach in detecting different spatial clusters for continuous point cloud segmentation.

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Parallel Processing a Three-Dimensional Free-Lagrange Code: a Case History

Cited by 5 publications

References 5 publications

Toward 3D spatial dynamic field simulation within GIS using kinetic Voronoi diagram and Delaunay tetrahedralization

Toward 3D spatial dynamic field simulation within GIS using kinetic Voronoi diagram and Delaunay tetrahedralization

Characterizing the parallel performance of a large‐scale, particle‐in‐cell plasma simulation code

Point Cluster Analysis Using a 3D Voronoi Diagram with Applications in Point Cloud Segmentation

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