Active flash: towards energy-efficient, in-situ data analytics on extreme-scale machines

  • Authors:
  • Devesh Tiwari;Simona Boboila;Sudharshan S. Vazhkudai;Youngjae Kim;Xiaosong Ma;Peter J. Desnoyers;Yan Solihin

  • Affiliations:
  • North Carolina State University;Northeastern University;Oak Ridge National Laboratory;Oak Ridge National Laboratory;North Carolina State University;Northeastern University;North Carolina State University

  • Venue:
  • FAST'13 Proceedings of the 11th USENIX conference on File and Storage Technologies
  • Year:
  • 2013

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Abstract

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), where the 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.