Modeling resource-coupled computations
Proceedings of the 2009 Workshop on Ultrascale Visualization
Proceedings of the 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis
An image compositing solution at scale
Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis
Parallel in situ coupling of simulation with a fully featured visualization system
EG PGV'11 Proceedings of the 11th Eurographics conference on Parallel Graphics and Visualization
Visualization for the Physical Sciences
Computer Graphics Forum
Steering and in-situ visualization for simulation of seismic wave propagation on graphics cards
PARA'12 Proceedings of the 11th international conference on Applied Parallel and Scientific Computing
Scalable in situ scientific data encoding for analytical query processing
Proceedings of the 22nd international symposium on High-performance parallel and distributed computing
SC '13 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
A generic high-performance method for deinterleaving scientific data
Euro-Par'13 Proceedings of the 19th international conference on Parallel Processing
Transactions on Edutainment IX
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Scientific computing at the petascale level enables us to answer many difficult scientific questions, but the resulting data are too large to store and study directly with conventional postprocessing visualization tools. This problem will only become more severe as we reach exascale computing. A plausible, attractive solution involves processing data in situ with the simulation to reduce the data that must be transferred over networks and stored and to prepare the data for more cost-effective postprocessing visualization. The data could be reduced with compression, feature extraction, and visualization methods. This article discusses critical issues in realizing in situ visualization and data reduction and suggests important research directions.