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

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.