F-SEFI: A Fine-Grained Soft Error Fault Injection Tool for Profiling Application Vulnerability

2014 ◽  
Author(s):  
Qiang Guan ◽  
Nathan Debardeleben ◽  
Sean Blanchard ◽  
Song Fu
Keyword(s):  
Fault Injection ◽  
Soft Error ◽  
Fine Grained

Analyzing the Robustness of HPC Applications Using a Fine-Grained Soft Error Fault Injection Tool

2016 ◽  
pp. 277-305
Author(s):  
Qiang Guan ◽  
Nathan DeBardeleben ◽  
Sean Blanchard ◽  
Song Fu ◽  
Claude H. Davis IV ◽  
...  
Keyword(s):  
High Performance ◽  
Fault Injection ◽  
Soft Errors ◽  
Small Degree ◽  
Soft Error ◽  
Power Efficient ◽  
Fine Grained ◽  
Different Characteristics ◽  
The Impact ◽  
Performance Computing

As the high performance computing (HPC) community continues to push towards exascale computing, HPC applications of today are only affected by soft errors to a small degree but we expect that this will become a more serious issue as HPC systems grow. We propose F-SEFI, a Fine-grained Soft Error Fault Injector, as a tool for profiling software robustness against soft errors. We utilize soft error injection to mimic the impact of errors on logic circuit behavior. Leveraging the open source virtual machine hypervisor QEMU, F-SEFI enables users to modify emulated machine instructions to introduce soft errors. F-SEFI can control what application, which sub-function, when and how to inject soft errors with different granularities, without interference to other applications that share the same environment. We demonstrate use cases of F-SEFI on several benchmark applications with different characteristics to show how data corruption can propagate to incorrect results. The findings from the fault injection campaign can be used for designing robust software and power-efficient hardware.

FFI4SoC: a Fine-Grained Fault Injection Framework for Assessing Reliability against Soft Error in SoC

2018 ◽  
Vol 34 (1) ◽  
pp. 15-25 ◽  
Author(s):  
Xiaozhi Du ◽  
Dongyang Luo ◽  
Kailun Shi ◽  
Chaohui He ◽  
Shuhuan Liu
Keyword(s):  
Fault Injection ◽  
Soft Error ◽  
Fine Grained

A Fine-Grained Software-Implemented DMA Fault Tolerance for SoC Against Soft Error

2018 ◽  
Vol 34 (6) ◽  
pp. 717-733
Author(s):  
Xiaozhi Du ◽  
Dongyang Luo ◽  
Chaohui He ◽  
Shuhuan Liu
Keyword(s):  
Fault Tolerance ◽  
Soft Error ◽  
Fine Grained

Soft Error Sensitivity Evaluation of Microprocessors by Multilevel Emulation-Based Fault Injection

2012 ◽  
Vol 61 (3) ◽  
pp. 313-322 ◽  
Author(s):  
Luis Entrena ◽  
Mario Garcia-Valderas ◽  
Raul Fernandez-Cardenal ◽  
Almudena Lindoso ◽  
Marta Portela ◽  
...  
Keyword(s):  
Fault Injection ◽  
Soft Error ◽  
Error Sensitivity ◽  
Sensitivity Evaluation

A Program-Aware Fault-Injection Method for Dependability Evaluation Against Soft-Error Using Genetic Algorithm

2018 ◽  
Vol 27 (09) ◽  
pp. 1850144
Author(s):  
Bahman Arasteh
Keyword(s):  
Genetic Algorithm ◽  
Computer System ◽  
Fault Injection ◽  
Soft Errors ◽  
Soft Error ◽  
Injection Method ◽  
Software Failures ◽  
Input Program ◽  
Dependability Evaluation ◽  
Original Size

Decreasing the scale of transistors and exponential increase in the transistor counts has made the soft-errors as one of the major causes of software failures. Fault injection is a powerful method for dependability assessment of a computer system against soft-errors. A considerable number of randomly injected faults in the current methods and tools are effect-less or equivalent. To overcome this problem and reduce the cost of fault injection, this study presents a software based fault-injection method that accurately evaluates the dependability of a computer system with a limited number fault-injection. Using a genetic algorithm (GA) the most vulnerable executable paths of an input program is identified; then only the basic blocs (BBs) into the identified vulnerable paths are considered as the target of fault injection. The results of fault injections on the set of 8 traditional benchmark-programs show that the proposed method reduces about 20% of effect-less faults by avoiding the injection of faults in the error-derating blocks of a program. Furthermore, the number of injected faults is reduced to 60% of its original size in the random injection. Also, the proposed method provides more stable and accurate results than the random injection.

High-Level Decision Diagram Simulation for Diagnosis and Soft-Error Analysis

2011 ◽  
pp. 294-309 ◽  
Author(s):  
Jaan Raik ◽  
Urmas Repinski ◽  
Maksim Jenihhin ◽  
Anton Chepurov
Keyword(s):  
Fault Injection ◽  
Soft Errors ◽  
Soft Error ◽  
Design Representation ◽  
Design Error ◽  
Error Location ◽  
Hardware Description ◽  
Source Level ◽  
High Level ◽  
Diagnosis Approach

This Chapter addresses the above-mentioned challenges by presenting a holistic diagnosis approach for design error location and malicious fault list generation for soft errors. First, a method for locating design errors at the source-level of hardware description language code using the design representation of high-level decision diagrams is explained. Subsequently, this method is reduced to malicious fault list generation at the high-level. A minimized fault list is generated for optimizing the time to be spent on the fault injection run necessary for assessing designs vulnerability to soft-errors.

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