Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
New Iterative Alternating Group Explicit (NAGE) is a powerful parallel numerical algorithm for multidimensional temperature prediction. The discretization is based on finite difference method of partial differential equation (PDE) with parabolic type. This paper proposed the NAGE method as a straigh...
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| Main Authors: | , , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2009
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/9918/1/ICCRD2009_Norma_Alias_UTM.pdf http://eprints.utm.my/id/eprint/9918/ http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:100444 |
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| Summary: | New Iterative Alternating Group Explicit (NAGE) is a powerful parallel numerical algorithm for multidimensional temperature prediction. The discretization is based on finite difference method of partial differential equation (PDE) with parabolic type. This paper proposed the NAGE method as a straight forward transformation from sequential to parallel algorithm using domain decomposition and splitting strategies. The processes involving the scheduling of communication, algometric and mapping the sub domain into a number of processors. The critical 3-Dimensional temperature visualization involves large scale of computational complexity. This computational challenge inspiring us to utilize the power of advanced high performance computing resources. By the means of higher performance computing, the computation cannot be relying on just one single set of cluster. Therefore, this research takes the advantage of utilizing multiple set of clusters from geographically different location which is known as grid computing. In realizing this concept, we consider the advantages of data passing between two web services which each are connected with one or multiple set of clusters. For this kind of relationship, we choose service-oriented architecture (SOA) style. Each web services are easily maintainable since there is loose coupling between interacting nodes. The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. As the conclusions, this leading grid-based application platform has a bright potential in managing highly scalable and reliable temperature prediction visualization. The efficiency of this application will be measured based on the results of numerical analysis and parallel performance. |
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