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Approximate partitioned method of snapshots for POD
[摘要] The proper orthogonal decomposition (POD) method has been widely used to construct efficient numerical surrogate models for computationally intensive applications,in control and optimization. An inherent challenge with this method is that POD basis generation can be computationally expensive due to the huge size of the input snapshot data obtained from typical high-fidelity, large-scale dynamic system simulations. However, if the process can be distributed into much smaller tasks over multiple processors in parallel, computational time can be drastically reduced. In this paper, we put forth a novel partitioned method for generating the POD basis from snapshot data. This method preserves the distributed nature of the data and takes advantage of parallelism for computation. Additionally, it greatly reduces subtask communication volume. Two numerical examples are presented that demonstrate the effectiveness of the new method. Published by Elsevier B.V.
[发布日期] 2016-12-01 [发布机构] 
[效力级别]  Proceedings Paper [学科分类] 
[关键词] Proper orthogonal decomposition;Domain decomposition;Partitioned singular value decomposition;Partitioned method of snapshots [时效性] 
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