"A Novel Model for Synthesizing Parallel I/O Workloads in Scientific Applications", in Proceedings of IEEE 2008 Cluster, Tsukuba, Japan, Sept. 29 - Oct. 1, 2008 (acceptance rate: 28/92 = 30%)
Abstract
One of the challenging issues in performance evaluation of parallel storage systems through synthetic-trace-driven simulation is to accurately characterize the I/O demands of data-intensive scientific applications. This paper analyzes several I/O traces collected from different distributed systems and concludes that correlations in parallel I/O inter-arrival times are inconsistent, either with little correlation or with evident and abundant correlations. Thus conventional Poisson or Markov arrival processes are inappropriate to model I/O arrivals in some applications. Instead, a new and generic model based on the ®-stable process is proposed and validated in this paper to accurately model parallel I/O burstiness in both workloads with little and strong correlations. This model can be used to generate reliable synthetic I/O sequences in simulation studies. Experimental results presented in this paper show that this model can capture the complex I/O behaviors of real storage systems more accurately and faithfully than conventional models, particularly for the burstiness characteristics in the parallel I/O workloads.
BibTeX Entry
	@inproceedings{zhu_cluster08, author = {Dan Feng and Qiang Zou and Hong Jiang and Yifeng Zhu}, title = {A Novel Model for Synthesizing Parallel I/O Workloads in Scientific Applications}, booktitle = {Proceedings of {IEEE} International Conference on Cluster Computing}, year = {2008}, pages = {xxx-xxx}, address = {Tsukuba, Japan}, }
Full Paper
Full paper (pdf)
Last modified on October 16, 2007