Performance Modeling of In Situ Rendering
SessionScientific Data Management and Visualization
Session ChairJanine C. Bennett
Event Type
Paper
Data Analytics
Introductory
Storage
Visualization
TimeTuesday, November 15th2:30pm - 3pm
Location355-D
DescriptionWith the push to exascale, in situ visualization and analysis will continue to play an important role in HPC. Tightly coupling in situ visualization with simulations constrains resources for both, and these constraints force a complex balance of trade-offs. A performance model that provides an a priori answer for the cost of using an in situ approach for a given task would assist in managing the trade-offs between simulation and visualization resources. In this work, we present new statistical performance models, based on algorithmic complexity, that accurately predict the run-time cost of a set of representative rendering algorithms, an essential in situ visualization task. To train and validate the models, we conduct a performance study of an MPI+X rendering infrastructure used in situ with three HPC simulation applications. We then explore feasibility issues using the model for selected in situ rendering questions.
Download PDF
Paper provided by the IEEE Computer SocietyPaper also available from the ACM Digital Library
Authors
Matthew Larsen (presenting)
Cyrus Harrison (presenting)
Dave Pugmire (presenting)
Jeremy Meredith (presenting)
