Translating the grid: How a translational approach shaped the development of grid computing

Journal Article · 01 May 2021 · Journal of Computational Science

DOI: https://doi.org/10.1016/j.jocs.2020.101214 · OSTI ID:1659367

Foster, Ian  ^[1]; Kesselman, Carl  ^[2]

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1. Univ. of Illinois, Chicago, IL (United States); Argonne National Lab. (ANL), Argonne, IL (United States)
2. Information Sciences Institute, Marina del Rey, CA (United States); Univ. of Southern California, Los Angeles, CA (United States)

A growing gap between progress in biological knowledge and improved health outcomes inspired the new discipline of translational medicine, in which the application of new knowledge is an explicit part of a research plan. Abramson and Parashar argue that a similar gap between complex computational technologies and evermore-challenging applications demands an analogous discipline of translational computer science, in which the deliberate movement of research results into large-scale practice becomes a central research focus rather than an afterthought. We revisit from this perspective the development and application of grid computing from the mid-1990s onwards, and find that a translational framing is useful for understanding the technology's development and impact. We discuss how the development of grid computing infrastructure, and the Globus Toolkit, in particular, benefited from a translational approach. We identify lessons learned that can be applied to other translational computer science initiatives.

• Research Organization: Argonne National Laboratory (ANL), Argonne, IL (United States)
• Sponsoring Organization: USDOE Office of Science (SC)
• Grant/Contract Number: AC02-06CH11357
• OSTI ID: 1659367
• Alternate ID(s): OSTI ID: 1824200
• Journal Information: Journal of Computational Science, Vol. 52; ISSN 1877-7503
• Publisher: ElsevierCopyright Statement
• Country of Publication: United States
• Language: English