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I/O Containers: Managing the Data Analytics and Visualization Pipelines of High End Codes
2013
2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum
Lack of I/O scalability is known to cause measurable slowdowns for large-scale scientific applications running on high end machines. This is prompting researchers to devise 'I/O staging' methods in which outputs are processed via online analysis and visualization methods to support desired science outcomes. Organized as online workflows and carried out in I/O pipelines, these analysis components run concurrently with science simulations, often using a smaller set of nodes on the high end
doi:10.1109/ipdpsw.2013.198
dblp:conf/ipps/DayalCESWZAKPL13
fatcat:pk2jnw4dkvhghkacrcue5kdmdm