TY - GEN
T1 - Dynamic active storage for high performance I/O
AU - Chen, Chao
AU - Chen, Yong
PY - 2012
Y1 - 2012
N2 - Many high-end computing applications in critical areas of science and technology are becoming more and more data intensive. These applications transfer large amounts of data from storage nodes to compute nodes for processing, which is costly and bandwidth consuming. The data movement often dominates the applications' run time. Active storage provides a promising solution for these applications by moving appropriate computations from compute nodes to storage nodes. The prior research has achieved considerable progress and developed several active storage models. However, the existing studies have neglected the influence of data dependence on the performance of active storage systems. This study shows that the data dependence has a critical impact on active storage, and the ignorance of dependence can lead to waste of the precious bandwidth. To address this issue in active storage, this paper also presents a new Dynamic Active Storage (DAS) architecture that analyzes the bandwidth requirement of operations, determines the applicability for active storage requests, and optimizes data layout on servers to minimize the bandwidth requirement. Experimental tests have been conducted, and the results have confirmed that the proposed DAS architecture outperforms existing active storage systems. The DAS architecture reduces the data movement caused by data dependence and improves applications' performance over existing schemes. It holds a promise for high performance I/O system in high-end computing.
AB - Many high-end computing applications in critical areas of science and technology are becoming more and more data intensive. These applications transfer large amounts of data from storage nodes to compute nodes for processing, which is costly and bandwidth consuming. The data movement often dominates the applications' run time. Active storage provides a promising solution for these applications by moving appropriate computations from compute nodes to storage nodes. The prior research has achieved considerable progress and developed several active storage models. However, the existing studies have neglected the influence of data dependence on the performance of active storage systems. This study shows that the data dependence has a critical impact on active storage, and the ignorance of dependence can lead to waste of the precious bandwidth. To address this issue in active storage, this paper also presents a new Dynamic Active Storage (DAS) architecture that analyzes the bandwidth requirement of operations, determines the applicability for active storage requests, and optimizes data layout on servers to minimize the bandwidth requirement. Experimental tests have been conducted, and the results have confirmed that the proposed DAS architecture outperforms existing active storage systems. The DAS architecture reduces the data movement caused by data dependence and improves applications' performance over existing schemes. It holds a promise for high performance I/O system in high-end computing.
KW - active storage
KW - data intensive computing
KW - dynamic active storage
KW - high end computing
KW - parallel I/O
KW - parallel file systems
UR - http://www.scopus.com/inward/record.url?scp=84871178404&partnerID=8YFLogxK
U2 - 10.1109/ICPP.2012.22
DO - 10.1109/ICPP.2012.22
M3 - Conference contribution
AN - SCOPUS:84871178404
SN - 9780769547961
T3 - Proceedings of the International Conference on Parallel Processing
SP - 379
EP - 388
BT - Proceedings - 41st International Conference on Parallel Processing, ICPP 2012
T2 - 41st International Conference on Parallel Processing, ICPP 2012
Y2 - 10 September 2012 through 13 September 2012
ER -