TY - JOUR
T1 - Exascale Storage Systems the SIRIUS Way
AU - Klasky, S. A.
AU - Abbasi, H.
AU - Ainsworth, M.
AU - Choi, J.
AU - Curry, M.
AU - Kurc, T.
AU - Liu, Q.
AU - Lofstead, J.
AU - Maltzahn, C.
AU - Parashar, M.
AU - Podhorszki, N.
AU - Suchyta, E.
AU - Wang, F.
AU - Wolf, M.
AU - Chang, C. S.
AU - Churchill, M.
AU - Ethier, S.
N1 - Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2016/11/11
Y1 - 2016/11/11
N2 - As the exascale computing age emerges, data related issues are becoming critical factors that determine how and where we do computing. Popular approaches used by traditional I/O solution and storage libraries become increasingly bottlenecked due to their assumptions about data movement, re-organization, and storage. While, new technologies, such as "burst buffers", can help address some of the short-term performance issues, it is essential that we reexamine the underlying storage and I/O infrastructure to effectively support requirements and challenges at exascale and beyond. In this paper we present a new approach to the exascale Storage System and I/O (SSIO), which is based on allowing users to inject application knowledge into the system and leverage this knowledge to better manage, store, and access large data volumes so as to minimize the time to scientific insights. Central to our approach is the distinction between the data, metadata, and the knowledge contained therein, transferred from the user to the system by describing "utility" of data as it ages.
AB - As the exascale computing age emerges, data related issues are becoming critical factors that determine how and where we do computing. Popular approaches used by traditional I/O solution and storage libraries become increasingly bottlenecked due to their assumptions about data movement, re-organization, and storage. While, new technologies, such as "burst buffers", can help address some of the short-term performance issues, it is essential that we reexamine the underlying storage and I/O infrastructure to effectively support requirements and challenges at exascale and beyond. In this paper we present a new approach to the exascale Storage System and I/O (SSIO), which is based on allowing users to inject application knowledge into the system and leverage this knowledge to better manage, store, and access large data volumes so as to minimize the time to scientific insights. Central to our approach is the distinction between the data, metadata, and the knowledge contained therein, transferred from the user to the system by describing "utility" of data as it ages.
UR - http://www.scopus.com/inward/record.url?scp=85002376207&partnerID=8YFLogxK
U2 - 10.1088/1742-6596/759/1/012095
DO - 10.1088/1742-6596/759/1/012095
M3 - Conference article
AN - SCOPUS:85002376207
SN - 1742-6588
VL - 759
JO - Journal of Physics: Conference Series
JF - Journal of Physics: Conference Series
IS - 1
M1 - 012095
T2 - 27th IUPAP Conference on Computational Physics, CCP 2015
Y2 - 2 December 2015 through 5 December 2015
ER -