MOARD: Modeling Application Resilience to Transient Faults on Data Objects

TL;DR

This paper introduces MOARD, a novel method and tool for modeling and quantifying application resilience to transient hardware faults on data objects, addressing limitations of traditional fault injection methods.

Contribution

The paper presents MOARD, a systematic approach to measure application resilience considering data semantics, enabling targeted fault tolerance strategies.

Findings

MOARD effectively quantifies error masking events.

Using MOARD guides efficient fault tolerance mechanisms.

Application semantics significantly influence error tolerance.

Abstract

Understanding application resilience (or error tolerance) in the presence of hardware transient faults on data objects is critical to ensure computing integrity and enable efficient application-level fault tolerance mechanisms. However, we lack a method and a tool to quantify application resilience to transient faults on data objects. The traditional method, random fault injection, cannot help, because of losing data semantics and insufficient information on how and where errors are tolerated. In this paper, we introduce a method and a tool (called MOARD) to model and quantify application resilience to transient faults on data objects. Our method is based on systematically quantifying error masking events caused by application-inherent semantics and program constructs. We use MOARD to study how and why errors in data objects can be tolerated by the application. We demonstrate tangible benefits of using MOARD to direct a fault tolerance mechanism to protect data objects.