Ganga: a tool for computational-task management and easy access to Grid resources

TL;DR

Ganga is a versatile tool that simplifies managing computational tasks across diverse distributed resources, enabling scientists to seamlessly develop and execute analyses on local and Grid systems with minimal effort.

Contribution

It introduces a unified, extensible platform for task management that abstracts heterogeneous computing environments, facilitating scientific workflows across multiple domains.

Findings

Supports transparent transition from local to Grid computing

Provides a flexible API for various interfaces

Demonstrated effective use in High Energy Physics

Abstract

In this paper, we present the computational task-management tool Ganga, which allows for the specification, submission, bookkeeping and post-processing of computational tasks on a wide set of distributed resources. Ganga has been developed to solve a problem increasingly common in scientific projects, which is that researchers must regularly switch between different processing systems, each with its own command set, to complete their computational tasks. Ganga provides a homogeneous environment for processing data on heterogeneous resources. We give examples from High Energy Physics, demonstrating how an analysis can be developed on a local system and then transparently moved to a Grid system for processing of all available data. Ganga has an API that can be used via an interactive interface, in scripts, or through a GUI. Specific knowledge about types of tasks or computational resources is provided at run-time through a plugin system, making new developments easy to integrate. We give an overview of the Ganga architecture, give examples of current use, and demonstrate how Ganga can be used in many different areas of science.