A new approach for analyzing I/O in parallel scienti

Abstract

The e cient use of high performance computing is usually focused on the use of computational resources. However, scienti c appli- cations currently produce a large volume of information. Therefore, the Input/Output (I/O) subsystem also should be used e ciently. In order to do so, it is necessary to know the application I/O patterns and establish a relationship between these patterns and the I/O susbsystem con g- uration. To analyze the I/O behavior of applications, we propose use a library of the PAS2P (Application Signature for Performance Prediction) tool. Parallel applications typically have repetitive behavior, and the I/O patterns of parallel applications also have that behavior. We propose to identify the portions (I/O phases) where the application does I/O. From these I/O phases, we extract an application model that can be used to evaluate it in di erent I/O subsystems considering the I/O phases and compute-communication phases. In this paper, we present the concepts used in the PAS2P methodology, which have been adapted for MPI-IO applications. We have extracted the I/O model of applications. This ap- proach was used to estimate the I/O time of an application in di erent subsystems. The results show a relative error of estimation lower than 10%.