@inproceedings{Gamell:2013:EPB:2503210.2503303,
 author = {Gamell, Marc and Rodero, Ivan and Parashar, Manish and Bennett, Janine C. and Kolla, Hemanth and Chen, Jacqueline and Bremer, Peer-Timo and Landge, Aaditya G. and Gyulassy, Attila and McCormick, Patrick and Pakin, Scott and Pascucci, Valerio and Klasky, Scott},
 title = {Exploring Power Behaviors and Trade-offs of In-situ Data Analytics},
 booktitle = {Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis},
 series = {SC '13},
 year = {2013},
 isbn = {978-1-4503-2378-9},
 location = {Denver, Colorado},
 pages = {77:1--77:12},
 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 in-situ 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 trade-offs on current as well as emerging systems.},
 articleno = {77},
 numpages = {12},
 url = {papers/a77-gamell.pdf},
 doi = {10.1145/2503210.2503303},
 acmid = {2503303},
 publisher = {ACM},
 address = {New York, NY, USA},
}

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