Parallel maximum-likelihood inversion for estimating wavenumber-ordered spectra in emission spectroscopy

H. El-Sayed, M. Salit, J. Travis, J. Devaney, W. George
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Abstract

We introduce a parallelization of the maximum likelihood cosine transform. This transform consists of a computationally intensive iterative fitting process, but is readily decomposed for parallel processing. The parallel implementation is not only scalable, but has also brought the execution time of this previously intractable problem to feasible levels using contemporary and cost-efficient high-performance computers, including an SGI Origin 2000, an SGI Onyx, and a cluster of Intel-based PCs.
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发射光谱学中估计波数有序光谱的并行最大似然反演
我们引入了最大似然余弦变换的并行化。该变换包含一个计算量大的迭代拟合过程,但易于分解以进行并行处理。并行实现不仅具有可伸缩性,而且还将这个以前难以解决的问题的执行时间降低到使用现代和经济高效的高性能计算机(包括SGI Origin 2000、SGI Onyx和基于英特尔的pc集群)的可行水平。
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