Sustaining the Montage Image Mosaic Engine Since 2002

TL;DR

This paper details the long-term sustainability and adaptability of the Montage image mosaic engine, highlighting its design, cross-platform support, and broad applicability in modern astronomical data processing and cyber-infrastructure.

Contribution

It presents how Montage's modular, ANSI-C design has enabled its longevity, scalability, and integration into diverse workflows and platforms over two decades.

Findings

Supports multiple platforms including Windows, JavaScript, and Python

Enables complex workflows and pipeline processing

Supports observation planning for JWST

Abstract

This paper describes how we have sustained the Montage image mosaic engine (http://montage.ipac.caltech.edu) first released in 2002, to support the ever-growing scale and complexity of modern data sets. The key to its longevity has been its design as a toolkit written in ANSI-C, with each tool performing one distinct task, for easy integration into scripts, pipelines and workflows. The same code base now supports Windows, JavaScript and Python by taking advantage of recent advances in compilers. The design has led to applicability of Montage far beyond what was anticipated when Montage was first built, such as supporting observation planning for the JWST. Moreover, Montage is highly scalable and is in wide use within the IT community to develop advanced, fault-tolerant cyber-infrastructure, such as job schedulers for grids, workflow orchestration, and restructuring techniques for processing complex workflows and pipelines.