@inproceedings{19b066d9a1d64b58a6e30bd905070f96,
title = "Exploring power behaviors and trade-offs of in-situ data analytics",
abstract = "As scientific applications target exascale, challenges related to data and energy are becoming dominating concerns. For example, coupled simulation workflows are increasingly adopting in-situ data processing and analysis techniques to address costs and overheads due to data movement and I/O. However it is also critical to understand these overheads and associated trade-offs from an energy perspective. The goal of this paper is exploring data-related energy/performance trade-offs for end-to-end simulation workflows running at scale on current high-end computing systems. Specifically, this paper presents: (1) an analysis of the data-related behaviors of a combustion simulation workflow with an insitu data analytics pipeline, running on the Titan system at ORNL; (2) a power model based on system power and data exchange patterns, which is empirically validated; and (3) the use of the model to characterize the energy behavior of the workflow and to explore energy/performance tradeoffs on current as well as emerging systems.",
author = "Marc Gamell and Ivan Rodero and Manish Parashar and Bennett, {Janine C.} and Hemanth Kolla and Jacqueline Chen and Bremer, {Peer Timo} and Landge, {Aaditya G.} and Attila Gyulassy and Patrick McCormick and Scott Pakin and Valerio Pascucci and Scott Klasky",
year = "2013",
doi = "10.1145/2503210.2503303",
language = "English",
isbn = "9781450323789",
series = "International Conference for High Performance Computing, Networking, Storage and Analysis, SC",
publisher = "IEEE Computer Society",
booktitle = "Proceedings of SC 2013",
note = "2013 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2013 ; Conference date: 17-11-2013 Through 22-11-2013",
}