Using Java for distributed computing in the Gaia satellite data processing

TL;DR

This paper discusses the adoption and implementation of Java for high-performance distributed computing in the Gaia satellite data processing, highlighting its advantages, architecture, and real-world application since 2005.

Contribution

It presents a detailed case study of using Java for complex, distributed astronomical data processing in the Gaia mission, including architecture and performance insights.

Findings

Java enabled scalable distributed processing for Gaia

Successful deployment of Java-based Gaia simulator since 2005

Insights into Java's advantages and challenges in scientific computing

Abstract

In recent years Java has matured to a stable easy-to-use language with the flexibility of an interpreter (for reflection etc.) but the performance and type checking of a compiled language. When we started using Java for astronomical applications around 1999 they were the first of their kind in astronomy. Now a great deal of astronomy software is written in Java as are many business applications. We discuss the current environment and trends concerning the language and present an actual example of scientific use of Java for high-performance distributed computing: ESA's mission Gaia. The Gaia scanning satellite will perform a galactic census of about 1000 million objects in our galaxy. The Gaia community has chosen to write its processing software in Java. We explore the manifold reasons for choosing Java for this large science collaboration. Gaia processing is numerically complex but highly distributable, some parts being embarrassingly parallel. We describe the Gaia processing architecture and its realisation in Java. We delve into the astrometric solution which is the most advanced and most complex part of the processing. The Gaia simulator is also written in Java and is the most mature code in the system. This has been successfully running since about 2005 on the supercomputer "Marenostrum" in Barcelona. We relate experiences of using Java on a large shared machine. Finally we discuss Java, including some of its problems, for scientific computing.