Name
Abstract | ||
|---|---|---|
Efficient execution of parallel scientific applications requires high-performance storage systems designed to meet their I/O requirements. Most high-performance I/O intensive applications access multiple layers of the storage stack during their disk operations. A typical I/O request from these applications may include accesses to high-level libraries such as MPI I/O, executing on clustered parallel file systems like PVFS2, which are in turn supported by native file systems like Linux. In order to design and implement parallel applications that exercise this I/O stack, it is important to understand the flow of I/O calls through the entire storage system. Such understanding helps in identifying the potential performance and power bottlenecks in different layers of the storage hierarchy. To trace the execution of the I/O calls and to understand the complex interactions of multiple user-libraries and file systems, we propose an automatic code instrumentation technique, which enables us to collect detailed statistics of the I/O stack. Our proposed I/O tracing tool traces the flow of I/O calls across different layers of an I/O stack, and can be configured to work with different file systems and user-libraries. It also analyzes the collected information to generate output in terms of different user-specified metrics of interest. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-15646-5_8 | EuroMPI |
Keywords | Field | DocType |
high-performance storage system,o intensive applications access,o requirement,native file system,o call,entire storage system,different user-specified metrics,different layer,different file system,o request,storage system | Instrumentation (computer programming),Computer data storage,Computer science,Device file,Input/output,Asynchronous I/O,Hierarchy,Parallel I/O,Tracing,Operating system | Conference |
Volume | ISSN | ISBN |
6305 | 0302-9743 | 3-642-15645-2 |
Citations | PageRank | References |
5 | 0.46 | 16 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Seong Jo Kim | 1 | 17 | 1.81 |
| Yuanrui Zhang | 2 | 180 | 15.48 |
| Seung Woo Son | 3 | 296 | 31.43 |
| Ramya Prabhakar | 4 | 74 | 7.27 |
| Mahmut T. Kandemir | 5 | 7371 | 568.54 |
| Christina Patrick | 6 | 9 | 1.27 |
| Wei-keng Liao | 7 | 1095 | 87.98 |
| Alok N. Choudhary | 8 | 3441 | 326.32 |