A study of self-similarity in parallel I/O workloads

Abstract

A challenging issue in performance evaluation of parallel storage systems through trace-driven simulation is to accurately characterize and emulate I/O behaviors in real applications. The correlation study of inter-arrival times between I/O requests, with an emphasis on I/O-intensive scientific applications, shows the necessity to further study the self-similarity of parallel I/O arrivals. This paper analyzes several I/O traces collected in large-scale supercomputers and concludes that parallel I/Os exhibit statistically self-similar like behavior. Instead of Markov model, a new stochastic model is proposed and validated in this paper to accurately model parallel I/O burstiness. This model can be used to predicting I/O workloads in real systems and generate reliable synthetic I/O sequences in simulation studies.