@inproceedings{60e05119ddc74374b788da27fbc31155,
title = "Comparing Time-To-Solution for in Situ Visualization Paradigms at Scale",
abstract = "This short paper considers time-To-solution for two in situ visualization paradigms: in-line and in-Transit. It is a follow-on work to two previous studies. The first study [10] considered time-To-solution (wall clock time) and total cost (total node seconds incurred) for a single visualization algorithm (isosurfacing). The second study [11] considered only total cost and added a second algorithm (volume rendering). This short paper completes the evaluation, considering time-To-solution for both algorithms. In particular, it extends the first study by adding additional insights from including a second algorithm at larger scale and by doing more extended and formal analysis regarding time-To-solution. Further, it complements the second study as the best in situ configuration to choose can vary when considering time-To-solution over cost. It also makes use of the same data corpus used in the second study, although that data corpus has been refactored with time-To-solution in mind.",
keywords = "in line, in situ, in transit, visualization",
author = "James Kress and Matthew Larsen and Jong Choi and Mark Kim and Matthew Wolf and Norbert Podhorszki and Scott Klasky and Hank Childs and David Pugmire",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 10th IEEE Symposium on Large Data Analysis and Visualization, LDAV 2020 ; Conference date: 25-10-2020",
year = "2020",
month = oct,
doi = "10.1109/LDAV51489.2020.00009",
language = "English",
series = "Proceedings - 2020 IEEE 10th Symposium on Large Data Analysis and Visualization, LDAV 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "22--26",
booktitle = "Proceedings - 2020 IEEE 10th Symposium on Large Data Analysis and Visualization, LDAV 2020",
}