Resilience is a major challenge for large-scale systems. It is particularly important for
iterative linear solvers, since they take much of the time of many scientific applications. We …

Energy increasingly constrains modern computer hardware, yet protecting computations and
data against errors costs energy. This holds at all scales, but especially for the largest …

Future extreme-scale computer systems may expose incorrect behavior to applications, in
order to save energy or increase performance. However, resilience research struggles to …

This paper presents a method to protect iterative solvers from Detected and Uncorrected
Errors (DUE) relying on error detection techniques already available in commodity …

We present a fault model designed to bring out the" worst" in iterative solvers based on
mathematical properties. Our model introduces substantially higher overhead, but smaller …

Current trends and projections show that faults in computer systems become increasingly
common. Such errors may be detected, and possibly corrected transparently, eg, by Error …

The increasing scale and complexity of today's high-performance computing (HPC) systems
demand a renewed focus on enhancing the resilience of long-running scientific applications …

Soft errors are a significant concern for highperformance computing systems in the exascale
time frame. We apply our group's Global View Resilience (GVR) library to a preconditioned …

The advent of extreme scale machines will require the use of parallel resources at an
unprecedented scale, probably leading to a high rate of hardware faults. High Performance …

On future large-scale systems, the mean time between failures (MTBF) of the system is
expected to decrease so that many faults could occur during the solution of large problems …