From detection to optimization: impact of soft errors on high-performance computing applications

As high-performance computing (HPC) continues to progress, constraints on HPC system design forces the handling of errors to higher levels in the software stack. Of the types of errors facing HPC, soft errors that silently corrupt system or application state are among the most severe. The behavior of HPC applications in the presence of soft errors is critical to gain insight for effective utilization of HPC systems. The need to understand this behavior can be used in developing algorithm-based error detection guided by application characteristics from fault injection and error propagation studies. Furthermore, the realization that applications are tolerant to small errors allows optimizations such as lossy compression on high-cost data transfers. Lossy compression adds small user controllable amounts of error when compressing data, to reduce data size before expensive data transfers saving time. This dissertation investigates and improves the resiliency of HPC applications to soft errors, and explores lossy compression as a new form of optimization for expensive, time-consuming data transfers.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2017

Author dc:creator

• Calhoun, Jon Cameron

Contributors dc:contributor

• Snir, Marc
• Olson, Luke N.
• Gropp, William
• Cappello, Franck

• High-performance computing
• Fault tolerance
• Silent data corruption
• Soft errors
• Error detection
• Error recovery
• Fault injection
• Error propagation
• Lossy compression
• Checkpoint-restart

Statement dc:rights

• Copyright 2017 Jon Cameron Calhoun

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/98379

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/98379