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Image processing at scale is a powerful tool for creating new data sets andintegrating them with existing data sets and performing analysis and qualityassurance investigations. Workflow managers offer advantages in this type ofprocessing, which involves multiple data access and processing steps.Generally, they enable automation of the workflow by locating data andresources, recovery from failures, and monitoring of performance. In this focusdemo we demonstrate how the Pegasus Workflow Manager Python API manages imageprocessing to create mosaics with the Montage Image Mosaic engine. Since 2001,Pegasus has been developed and maintained at USC/ISI. Montage was in fact oneof the first applications used to design Pegasus and optimize its performance.Pegasus has since found application in many areas of science. LIGO exploited itin making discoveries of black holes. The Vera C. Rubin Observatory used it tocompare the cost and performance of processing images on cloud platforms. Whilethese are examples of projects at large scale, small team investigations onlocal clusters of machines can benefit from Pegasus as well.

Astronomical Image Processing at Scale With Pegasus and Montage