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Active Flash: Towards Energy-Efficient, In-Situ Data Analytics on Extreme-Scale Machines
Devesh Tiwari, North Carolina State University; Simona Boboila, Northeastern University; Sudharshan Vazhkudai and Youngjae Kim, Oak Ridge National Laboratory; Xiaosong Ma, North Carolina State University; Peter Desnoyers, Northeastern University; Yan Solihin, North Carolina State University
Modern scientific discovery is increasingly driven by large-scale supercomputing simulations, followed by data analysis tasks. These data analyses are either performed offline, on smaller-scale clusters, or on the supercomputer itself. Unfortunately, these techniques suffer from performance and energy inefficiencies due to increased data movement between the compute and storage subsystems. Therefore, we propose Active Flash, an insitu scientific data analysis approach, wherein data analysis is conducted on the solid-state device (SSD), wherethe data already resides. Our performance and energy models show that Active Flash has the potential to address many of the aforementioned concerns without degrading HPC simulation performance. In addition, we demonstrate an Active Flash prototype built on a commercial SSD controller, which further reaffirms the viability of our proposal.
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author = {Devesh Tiwari and Simona Boboila and Sudharshan Vazhkudai and Youngjae Kim and Xiaosong Ma and Peter Desnoyers and Yan Solihin},
title = {Active Flash: Towards {Energy-Efficient}, {In-Situ} Data Analytics on {Extreme-Scale} Machines},
booktitle = {11th USENIX Conference on File and Storage Technologies (FAST 13)},
year = {2013},
isbn = {978-1-931971-99-7},
address = {San Jose, CA},
pages = {119--132},
url = {https://www.usenix.org/conference/fast13/technical-sessions/presentation/tiwari},
publisher = {USENIX Association},
month = feb
}
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