Modeling Parallel Scientific Applications through their Input/Output Phases

The increase in computational power in processing units and the complexity of scientific applications that use high performance computing require more efficient Input/Output (I/O) systems. To use the I/O systems more efficiently it is necessary to know its performance capacity to determine if it fulfills applications' I/O requirements. Evaluating the I/O system performance capacity is difficult due to the diversity of I/O architectures and the complexity of its I/O software stack. Furthermore, parallel scientific applications have different behavior depending on their access patterns. Then, it is necessary to have some method to evaluate the I/O subsystem capacity taking into account the applications access patterns without executing the application in each I/O subsystem. Here, we propose a methodology to evaluate the I/O subsystem performance capacity through an I/O model of the parallel application independent of the I/O subsystem. This I/O model is composed of I/O phases representing "where" and "when" the I/O operations are performed into application logic. This approach encompasses the I/O subsystem evaluation at I/O library level for the application I/O model. The I/O phases are replicated by benchmark IOR which is executed in the target subsystem. This approach was used to estimate the I/O time of an application in different subsystems. The results show an relative error of estimation lower than 10%. This approach was also utilized to select the I/O subsystem that provide less I/O time for the application.