Existing data grid scheduling systems handle huge data I/O via replica location services coupled with simple staging, decoupled from scheduling of computing tasks. However, when th...
The applications in many scientific fields, like bioinformatics and high-energy physics etc, increasingly demand the computing infrastructures can provide more computing power and...
Xiaohui Wei, Zhaohui Ding, Wilfred W. Li, Osamu Ta...
One of the first motivations of using grids comes from applications managing large data sets in field such as high energy physics or life sciences. To improve the global throughput...
Modern scientific computing involves organizing, moving, visualizing, and analyzing massive amounts of data from around the world, as well as employing large-scale computation. The...
Brian Tierney, William E. Johnston, Jason Lee, Mar...
This paper studies five real-world data intensive workflow applications in the fields of natural language processing, astronomy image analysis, and web data analysis. Data intensiv...