Name
Abstract | ||
|---|---|---|
In the near future large-scale parallel computers will feature hundreds of thousands of processing nodes. In such systems, fault tolerance is critical as failures will occur very often. Checkpointing and rollback recovery has been extensively studied as an attempt to provide fault tolerance. However, current implementations do not provide the total transparency and full flexibility that are necessary to support the new paradigm of autonomic computing-systems able to self-heal and self-repair. In this paper we provide an in-depth evaluation of incremental checkpointing for scientific computing. The experimental results, obtained on a state-of-the art cluster running several scientific applications, show that efficient, scalable, automatic and user-transparent incremental checkpointing is within reach with current technology. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1109/IPDPS.2004.1302982 | IPDPS |
Keywords | Field | DocType |
parallel computer,scientific computing,fault tolerance,hardware,high performance computing,computer networks,concurrent computing,application software,autonomic computing,fault tolerant | Transparency (graphic),Autonomic computing,System recovery,Computer science,Parallel computing,Implementation,Computational science,Fault tolerance,Rollback recovery,Distributed computing,Scalability | Conference |
Citations | PageRank | References |
25 | 1.64 | 18 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| José Carlos Sancho | 1 | 382 | 29.97 |
| Fabrizio Petrini | 2 | 2050 | 165.82 |
| Greg Johnson | 3 | 25 | 1.64 |
| Juan Fernandez | 4 | 269 | 23.17 |
| Eitan Frachtenberg | 5 | 1060 | 85.08 |