CLC number: TP333
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2012-10-12
Cited: 0
Clicked: 7890
Yang Liu, Jian-zhong Huang, Xiao-dong Shi, Qiang Cao, Chang-sheng Xie. Strip-oriented asynchronous prefetching for parallel disk systems[J]. Journal of Zhejiang University Science C, 2012, 13(11): 799-815.
@article{title="Strip-oriented asynchronous prefetching for parallel disk systems",
author="Yang Liu, Jian-zhong Huang, Xiao-dong Shi, Qiang Cao, Chang-sheng Xie",
journal="Journal of Zhejiang University Science C",
volume="13",
number="11",
pages="799-815",
year="2012",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.C1200085"
}
%0 Journal Article
%T Strip-oriented asynchronous prefetching for parallel disk systems
%A Yang Liu
%A Jian-zhong Huang
%A Xiao-dong Shi
%A Qiang Cao
%A Chang-sheng Xie
%J Journal of Zhejiang University SCIENCE C
%V 13
%N 11
%P 799-815
%@ 1869-1951
%D 2012
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.C1200085
TY - JOUR
T1 - Strip-oriented asynchronous prefetching for parallel disk systems
A1 - Yang Liu
A1 - Jian-zhong Huang
A1 - Xiao-dong Shi
A1 - Qiang Cao
A1 - Chang-sheng Xie
J0 - Journal of Zhejiang University Science C
VL - 13
IS - 11
SP - 799
EP - 815
%@ 1869-1951
Y1 - 2012
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.C1200085
Abstract: sequential prefetching schemes are widely employed in storage servers to mask disk latency and improve system throughput. However, existing schemes cannot benefit parallel disk systems as expected due to the fact that they ignore the distinct internal characteristics of the parallel disk system, in particular, data striping. Moreover, their aggressive prefetching pattern suffers from premature evictions and prolonged request latencies. In this paper, we propose a strip-oriented asynchronous prefetching (SoAP) technique, which is dedicated to the parallel disk system. It settles the above-mentioned problems by providing multiple novel features, e.g., enhanced prediction accuracy, adaptive prefetching strength, physical data layout awareness, and timely prefetching. To validate SoAP, we implement a prototype by modifying the software redundant arrays of inexpensive disks (RAID) under Linux. Experimental results demonstrate that SoAP can consistently offer improved average response time and throughput to the parallel disk system under non-random workloads compared with STEP, SP, ASP, and Linux-like SEQPs.
[1]Baek, S.H., Park, K.H., 2008. Prefetching with Adaptive Cache Culling for Striped Disk Arrays. USENIX ATC, p.363-376.
[2]Bhatia, S., Varki, E., Merchant, A., 2010. Sequential Prefetch Cache Sizing for Maximal Hit Rate. MASCOTS, p.89-98.
[3]Bovet, D., Cesati, M., Oram, A., 2005. Understanding the Linux Kernel. O’Reilly, Sebastopol, CA, USA.
[4]Bowman, I.T., Salem, K., 2005. Optimization of query streams using semantic prefetching. ACM Trans. Database Syst., 30(4):1056-1101.
[5]Cao, P., Felten, E.W., Karlin, A.R., Li, K., 1996. Implementation and performance of integrated application-controlled file caching, prefetching, and disk scheduling. ACM Trans. Comput. Syst., 14(4):311-343.
[6]Chang, F., Gibson, G.A., 1999. Automatic I/O Hint Generation Through Speculative Execution. OSDI, p.1-14.
[7]Gill, B.S., Modha, D.S., 2005. SARC: Sequential Prefetching in Adaptive Replacement Cache. USENIX ATC, p.293-308.
[8]Gill, B.S., Angel, L., Bathen, D., 2007. AMP: Adaptive Multi-stream Prefetching in a Shared Cache. FAST, p.185-198.
[9]Hartung, M., 2003. IBM total storage enterprise storage server: a designer’s view. IBM Syst. J., 42(2):383-396.
[10]Hsu, W.W., Smith, A.J., Young, H.C., 2001. I/O reference behavior of production database workloads and the TPC benchmarks—an analysis at the logical level. ACM Trans. Database Syst., 26(1):96-143.
[11]Kamruzzaman, M., Swanson, S., Tullsen, D.M., 2011. Inter-Core Prefetching for Multicore Processors Using Migrating Helper Threads. ASPLOS, p.393-404.
[12]Li, C., Shen, K., 2005. Managing Prefetch Memory for Data-Intensive Online Servers. FAST, p.253-266.
[13]Li, M.J., Varki, E., Bhatia, S., Merchant, A., 2008. TAP: Table-Based Prefetching for Storage Caches. FAST, p.1-16.
[14]Li, Z.M., Chen, Z.F., Srinivasan, S.M., Zhou, Y.Y., 2004. C-Miner: Mining Block Correlations in Storage Systems. FAST, p.173-186.
[15]Liang, S., Jiang, S., Zhang, X.D., 2007. STEP: Sequentiality and Thrashing Detection Based Prefetching to Improve Performance of Networked Storage Servers. ICDCS, p.64-73.
[16]Lymberopoulos, D., Riva, O., Strauss, K., Mittal, A., Ntoulas, A., 2012. Pocketweb: Instant Web Browsing for Mobile Devices. ASPLOS, p.1-12.
[17]RAID Advisory Board, 1999. The Raidbook: a Source Book for RAID Technology (6th Ed.). Lino Lakes, MN.
[18]Storage Performance Council, 2011. SPC Benchmark 2/Energy (SPC-2/E), SPC Benchmark 2C/Energy (SPC-2C/E) Benchmark Extensions Address Energy Use in Sequential Applications. Available from http://www.storageperformance.org/press/SPC_2E_2CE_PR_final.pdf [Accessed on Jan. 13, 2012].
[19]Tian, L., Feng, D., Jiang, H., Zhou, K., Zeng, L.F., Chen, J.X., Wang, Z.K., Song, Z.L., 2007. PRO: a Popularity-Based Multi-threaded Reconstruction Optimization for RAID-Structured Storage Systems. FAST, p.277-290.
[20]Zhang, Z., Kulkarni, A., Ma, X.S., Zhou, Y.Y., 2009. Memory Resource Allocation for File System Prefetching: from a Supply Chain Management Perspective. EuroSys, p.75-88.
Open peer comments: Debate/Discuss/Question/Opinion
<1>