Modeling and Predicting Disk I/O Time of HPC Applications

Understanding input/output (I/O) performance in high performance computing (HPC) is becoming increasingly important as the gap between the performance of computation and I/O widens. In this paper we propose a methodology to predict an application's disk I/O time while running on High Performance Computing Modernization Program (HPCMP) systems. Our methodology consists of the following steps: 1) Characterize the I/O operations of an application running on a reference system. 2) Using a configurable I/O benchmark, collect statistics on the reference and target systems about the I/O operations that are relevant to the application on the reference and target systems. 3) Calculate a ratio between the measured I/O performance of the application on the reference system, with respect to target systems to predict the application's I/O time on the target systems. Our results show that this methodology can accurately predict the I/O time of relevant HPC applications on HPCMP systems that have reasonably stable I/O performance run to run while systems that have wide variability in I/O performance are more difficult to predict accurately.

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