10. In Situ Summarization with VTK-m¶
David Thompson, Sebastien Jourdain, Andrew Bauer, Berk Geveci, Robert Maynard, Ranga Raju Vatsavai, and Patrick O’Leary
10.1. Full Text¶
Link to the full text PDF.
10.1.1. Abstract¶
Summarization and compression at current and future scales requires a framework for developing and benchmarking algorithms. We present a framework created by integrating existing, production- ready projects and provide timings of two particular algorithms that serve as exemplars for summarization: a wavelet-based data reduction filter and a generator for creating image-like databases of extracted features (isocontours in this case). Both support browser-based, post-hoc, interactive visualization of the summary for decision- making. A study of their weak-scaling on a distributed multi-GPU system is included.