@inproceedings{07e3a157de894d6c83c8ecb5b1353512,
title = "A codesign framework for online data analysis and reduction",
abstract = "In this paper we discuss our design of a toolset for automating performance studies of composed HPC applications that perform online data reduction and analysis. We describe Cheetah, a new framework for performing parametric studies on coupled applications. Cheetah facilitates understanding the impact of various factors such as process placement, synchronicity of algorithms, and storage vs. compute requirements for online analysis of large data. Ultimately, we aim to create a catalog of performance results that can help scientists understand tradeoffs when designing next-generation simulations that make use of online processing techniques. We illustrate the design choices of Cheetah by using a reaction-diffusion simulation (Gray-Scott) paired with an analysis application to demonstrate initial results of fine-grained process placement on Summit, a pre-exascale supercomputer at Oak Ridge National Laboratory.",
keywords = "Cheetah, Codar, Codesign, Exascale, In situ, Online, Reduction, Savanna, Summit, Workflows",
author = "Kshitij Mehta and Ian Foster and Scott Klasky and Bryce Allen and Matthew Wolf and Jeremy Logan and Eric Suchyta and Jong Choi and Keichi Takahashi and Igor Yakushin and Todd Munson",
note = "Funding Information: This research was supported in part by the Exascale Computing Project (17-SC-20-SC) of the U.S. Department of Energy (DOE), and by DOE{\textquoteright}s Advanced Scientific Research Office (ASCR) under contract DE-AC02-06CH11357. Additionally, this research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory and of the National Energy Research Scientific Computing Center, which are supported by the Office of Science of the U.S. Department of Energy under Contract Numbers DE-AC05-00OR22725 and DE-AC02-05CH11231, respectively. Publisher Copyright: {\textcopyright} 2019 IEEE.; 14th IEEE/ACM Workshop on Workflows in Support of Large-Scale Science, WORKS 2019 ; Conference date: 17-11-2019",
year = "2019",
month = nov,
doi = "10.1109/WORKS49585.2019.00007",
language = "English",
series = "Proceedings of WORKS 2019: 14th Workshop on Workflows in Support of Large-Scale Science - Held in conjunction with SC 2019: The International Conference for High Performance Computing, Networking, Storage and Analysis",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "11--20",
booktitle = "Proceedings of WORKS 2019",
}