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Erschienen in:
2007 | OriginalPaper | Buchkapitel
Data Transfer in Advance on Cluster
verfasst von : Nilton Cézar de Paula, Gisele da Silva Craveiro, Liria Matsumoto Sato
Erschienen in: Parallel Computing Technologies
Verlag: Springer Berlin Heidelberg
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Scientific applications are increasingly challenging computational platforms and software tools. In this scenario of improving performance demand, computer cluster users require for mechanisms that could reduce data transfer delay. To contribute to this question, we proposed a data transfer in advance mechanism that improved overall system performance by diminishing data-intensive job wait. We also designed and implemented the Integrated Scheduling System (ISS) to analyze and evaluate our proposal. This system automates the preparation, submission and tracking of job executions in a cluster. The mechanism is also combined with an I/O file operation and computation overlapping idea that results in significant improvement of performance rates, confirmed by some experiments.