  We present a generalized Non-negative factorization (NMF)-based data
reduction pipeline for circumstellar disk and exoplanet detection. By using an
adaptable pre-processing routine that applies algorithmic masks and corrections
to improper data, we are able to easily offload the computationally-intensive
NMF algorithm to a graphics processing unit (GPU), significantly increasing
computational efficiency. NMF has been shown to better preserve disk structural
features compared to other post-processing approaches and has demonstrated
improvements in the analysis of archival data. The adaptive pre-processing
routine of this pipeline, which automatically aligns and applies image
corrections to the raw data, is shown to significantly improve chromatic halo
suppression. Utilizing HST-STIS and JWST-MIRI coronagraphic datasets, we
demonstrate a factor of five increase in real-time computational efficiency by
using GPUs to perform NMF compared to using CPUs. Additionally, we demonstrate
the usefulness of higher numbers of NMF components with SNR and contrast
improvements, which necessitates the use of a more computationally efficient
approach for data reduction.
