Sources of Variation in Error Sensitivity Measurements, Significant or Not?
Paper in proceedings, 2018

Measuring the error sensitivity by fault injection is an important method for assessing the dependability of computer systems. In this paper, we define error sensitivity as the conditional probability that a hardware-related error causes a silent data corruption. When measuring the error sensitivity it is important to consider how the experimental setup and the workload characteristics affect the estimated error sensitivity. We consider five such potential sources of variation (PSVs) in this paper. Three of these are related to the workload: i) input profile, ii) source code implementation, and, iii) use of compiler optimization. Two are related to the experimental setup: i) single vs. double bit-flips, and ii) inject-on-read vs. inject-on-write. The paper discusses the applicability of different statistical tests for assessing whether a PSV has a significant impact on error sensitivity.

fault injection

soft errors

Statistical inference

error sensitivity

Sources of variation

Author

Fatemeh Ayatolahi

Chalmers, Computer Science and Engineering (Chalmers), Computer Engineering (Chalmers), Real-time and Computer Graphics Systems

Johan Karlsson

Chalmers, Computer Science and Engineering (Chalmers)

Proceedings - 48th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops, DSN-W 2018

71-72 8416220

48th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops, DSN-W 2018
Luxembourg City, Luxembourg,

Subject Categories

Medical Laboratory and Measurements Technologies

Signal Processing

Other Electrical Engineering, Electronic Engineering, Information Engineering

DOI

10.1109/DSN-W.2018.00035

More information

Latest update

12/27/2018