Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ClusterW.2012.37 | Cluster Computing Workshops |
Keywords | Field | DocType |
o subsystem capacity,o operation,o architecture,o time,o requirement,o subsystem,o phase,o software,o library level,parallel scientific applications,output phases,o model,parallel processing,computational complexity | I/O scheduling,Supercomputer,Computer science,Parallel processing,Parallel computing,Real-time computing,Input/output,Software,Application logic,Approximation error,Computational complexity theory | Conference |
ISBN | Citations | PageRank |
978-1-4673-2893-7 | 5 | 0.47 |
References | Authors | |
8 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sandra Mendez | 1 | 7 | 2.24 |
| Dolores Rexachs | 2 | 195 | 43.20 |
| Emilio Luque | 3 | 1097 | 176.18 |