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An Energy-Oriented Evaluation of Buffer Cache Algorithms Using Parallel I/O Workloads
November 2008 (vol. 19 no. 11)
pp. 1565-1578
ASCII Text
x 
 
Jianhui Yue, Yifeng Zhu, Zhao Cai, "An Energy-Oriented Evaluation of Buffer Cache Algorithms Using Parallel I/O Workloads," IEEE Transactions on Parallel and Distributed Systems, vol. 19, no. 11, pp. 1565-1578, November, 2008.
 
 
BibTex
x
 
@article{ 10.1109/TPDS.2008.109,
author = {Jianhui Yue and Yifeng Zhu and Zhao Cai},
title = {An Energy-Oriented Evaluation of Buffer Cache Algorithms Using Parallel I/O Workloads},
journal ={IEEE Transactions on Parallel and Distributed Systems},
volume = {19},
number = {11},
issn = {1045-9219},
year = {2008},
pages = {1565-1578},
doi = {http://doi.ieeecomputersociety.org/10.1109/TPDS.2008.109},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Parallel and Distributed Systems
TI - An Energy-Oriented Evaluation of Buffer Cache Algorithms Using Parallel I/O Workloads
IS - 11
SN - 1045-9219
SP1565
EP1578
EPD - 1565-1578
A1 - Jianhui Yue,
A1 - Yifeng Zhu,
A1 - Zhao Cai,
PY - 2008
KW - Main memory
KW - Storage Management
KW - Operating Systems
KW - Software/Software Engineering
KW - Storage hierarchies
KW - Parallel I/O
KW - Interconnections (Subsystems)
KW - I/O and Data Communications Hardware
VL - 19
JA - IEEE Transactions on Parallel and Distributed Systems
ER -
 
Jianhui Yue, University of Maine, Orono
Yifeng Zhu, University of Maine, Orono
Zhao Cai, University of Maine, Orono
Power consumption is an important issue for cluster supercomputers as it directly affects running cost and cooling requirements. This paper investigates the memory energy efficiency of high-end data servers used for supercomputers. Emerging memory technologies allow memory devices to dynamically adjust their power states and enable free rides by overlapping multiple DMA transfers from different I/O buses to the same memory device. To achieve maximum energy saving, the memory management on data servers needs to judiciously utilize these energy-aware devices. As we explore different management schemes under five real-world parallel I/O workloads, we find that the memory energy behavior is determined by a complex interaction among four important factors: (1) cache hit rates that may directly translate performance gain into energy saving, (2) cache populating schemes that perform buffer allocation and affect access locality at the chip level, (3) request clustering that aims to temporally align memory transfers from different buses into the same memory chips, and (4) access patterns in workloads that affect the first three factors.

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Index Terms:
Main memory, Storage Management, Operating Systems, Software/Software Engineering, Storage hierarchies, Parallel I/O, Interconnections (Subsystems), I/O and Data Communications Hardware
Citation:
Jianhui Yue, Yifeng Zhu, Zhao Cai, "An Energy-Oriented Evaluation of Buffer Cache Algorithms Using Parallel I/O Workloads," IEEE Transactions on Parallel and Distributed Systems, vol. 19, no. 11, pp. 1565-1578, Nov. 2008, doi:10.1109/TPDS.2008.109
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