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Data Sharing Options for Scientific Workflows on Amazon EC2
2010
2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis
Efficient data management is a key component in achieving good performance for scientific workflows in distributed environments. Workflow applications typically communicate data between tasks using files. When tasks are distributed, these files are either transferred from one computational node to another, or accessed through a shared storage system. In grids and clusters, workflow data is often stored on network and parallel file systems. In this paper we investigate some of the ways in which
doi:10.1109/sc.2010.17
dblp:conf/sc/JuveDVMBBM10
fatcat:iye43g47xzcqnhzyb44nirsibq