Scientific applications often involve computation intensive workflows and may generate large amount of derived data. In this paper we consider a life cycle, which starts when the ...
During the past decade, the scientific community has witnessed the rapid accumulation of gene sequence data and data related to physiology and biochemistry of organisms. Bioinform...
Dinanath Sulakhe, Alex Rodriguez, Michael Wilde, I...
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...
As data volumes increase at a high speed in more and more application fields of science, engineering, information services, etc., the challenges posed by data-intensive computing...
Data-intensive parallel applications on clouds need to deploy large data sets from the cloud's storage facility to all compute nodes as fast as possible. Many multicast algori...
Tatsuhiro Chiba, Mathijs den Burger, Thilo Kielman...