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Grid computing has reached the stage where deployments are mature and many collaborations run in production mode. Mature Grid deployments offer the opportunity for revisiting and perhaps updating traditional beliefs related to workload models, which in turn leads to the re-evaluation of traditional resource management techniques. This paper analyzes usage patterns in a typical Grid community, a large-scale data-intensive scientific collaboration in high-energy physics. The focus mainly on data usage, since data is the major resource for this class of applications.
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