Name
Abstract | ||
|---|---|---|
Application resilience is a key challenge that has to be addressed to realize the exascale vision. Online recovery, even when it involves all processes, can dramatically reduce the overhead of failures as compared to the more traditional approach where the job is terminated and restarted from the last checkpoint. In this paper we explore how local recovery can be used for certain classes of applications to further reduce overheads due to resilience. Specifically we develop programming support and scalable runtime mechanisms to enable online and transparent local recovery for stencil-based parallel applications on current leadership class systems. We also show how multiple independent failures can be masked to effectively reduce the impact on the total time to solution. We integrate these mechanisms with the S3D combustion simulation, and experimentally demonstrate (using the Titan Cray-XK7 system at ORNL) the ability to tolerate high failure rates (i.e., node failures every 5 seconds) with low overhead while sustaining performance, at scales up to 262144 cores. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1145/2807591.2807672 | International Conference for High Performance Computing, Networking, Storage, and Analysis |
Keywords | Field | DocType |
Fault-Tolerance, Performance Modeling, Scalable Methods | Psychological resilience,Masking (art),Computer science,Stencil,Parallel computing,Fault tolerance,Overhead (business),Distributed computing,Scalability | Conference |
ISBN | Citations | PageRank |
978-1-5090-0273-3 | 12 | 0.54 |
References | Authors | |
25 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marc Gamell | 1 | 92 | 5.70 |
| Keita Teranishi | 2 | 49 | 6.30 |
| Michael A. Heroux | 3 | 974 | 69.20 |
| Jackson Mayo | 4 | 43 | 7.97 |
| Hemanth Kolla | 5 | 250 | 17.13 |
| Jacqueline Chen | 6 | 240 | 13.69 |
| Manish Parashar | 7 | 3876 | 343.30 |