Abstract
One of the hallmarks of current science experiments is the large volume of data that must be managed. For example, next generation particle physics experiments will generate petabytes of data per year. These data sets form important community resources, so not only must be manage to store and process this data, but we must be able to share it as well. In this talk, I will introduce the concept of data grids, a distributed grid infrastructure for sharing and managing large data sets. Using several examples, I will present a data grid architecture and illustrate how it can be used to address a number of current applications.
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© 2001 Springer-Verlag Berlin Heidelberg
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Kesselman, C. (2001). Data Grids for Next Generation Problems in Science and Engineering. In: Sørevik, T., Manne, F., Gebremedhin, A.H., Moe, R. (eds) Applied Parallel Computing. New Paradigms for HPC in Industry and Academia. PARA 2000. Lecture Notes in Computer Science, vol 1947. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-70734-4_2
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DOI: https://doi.org/10.1007/3-540-70734-4_2
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