@inproceedings{adaptiveio:sc10
 author = {Lofstead, J. and Zheng, F. and Liu, Q. and Klasky, S. and Oldfield, R. and Kordenbrock, T. and Schwan, K. and Wolf, M.},
 title = {Managing Variability in the IO Performance of Petascale Storage Systems},
 abstract = {Significant challenges exist for achieving
peak or even consistent levels of performance when
using IO systems at scale. They stem from sharing IO
system resources across the processes of single largescale
applications and/or multiple simultaneous programs
causing internal and external interference, which in turn,
causes substantial reductions in IO performance. This
paper presents interference effects measurements for two
different file systems at multiple supercomputing sites.
These measurements motivate developing a `managed'
IO approach using adaptive algorithms varying the IO
system workload based on current levels and use areas.
An implementation of these methods deployed for the
shared, general scratch storage system on Oak Ridge
National Laboratory machines achieves higher overall
performance and less variability in both a typical usage
environment and with artificially introduced levels
of `noise'. The latter serving to clearly delineate and
illustrate potential problems arising from shared system
usage and the advantages derived from actively managing
it.},
 booktitle = {SC '10: Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis},
 year = {2010},
 location = {New Orleans, Louisana},
 publisher = {ACM},
 address = {New York, NY, USA},
 }