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Title: FailAmp: Relativization Transformation for Soft Error Detection in Structured Address Generation

Abstract

We present FailAmp, a novel LLVM program transformation algorithm that makes programs employing structured index calculations more robust against soft-errors. Without FailAmp, an offset error can go undetected; with FailAmp, all subsequent offsets are relativized, building on the faulty one. FailAmp can exploit ISAs such as ARM to further reduce overheads. We verify correctness properties of FailAMP using an SMT solver, and present a thorough evaluation using many HPC benchmarks under a fault injection campaign. FailAmp provides full soft-error detection for address calculation while incurring an average overhead of around 5%.

Authors:
 [1];  [1];  [1];  [2];  [3];  [1];  [1]
+ Show Author Affiliations
  1. Univ. of Utah, Salt Lake City, UT (United States)
  2. Microsoft Corporation, Redmond, WA (United States)
  3. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1599993
Report Number(s):
PNNL-SA-148816
Journal ID: ISSN 1544-3566
Grant/Contract Number:  
AC05-76RL01830
Resource Type:
Accepted Manuscript
Journal Name:
ACM Transactions on Architecture and Code Optimization
Additional Journal Information:
Journal Volume: 16; Journal Issue: 4; Journal ID: ISSN 1544-3566
Publisher:
Association for Computing Machinery
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; Soft error detection; failure amplification; structured address generation; LLVM transformation

Citation Formats

Briggs, Ian, Das, Arnab, Baranowski, Mark, Sharma, Vishal, Krishnamoorthy, Sriram, Rakamaric, Zvonimir, and Gopalakrishnan, Ganesh. FailAmp: Relativization Transformation for Soft Error Detection in Structured Address Generation. United States: N. p., 2019. Web. doi:10.1145/3369381.
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Briggs, Ian, Das, Arnab, Baranowski, Mark, Sharma, Vishal, Krishnamoorthy, Sriram, Rakamaric, Zvonimir, & Gopalakrishnan, Ganesh. FailAmp: Relativization Transformation for Soft Error Detection in Structured Address Generation. United States. https://doi.org/10.1145/3369381
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Briggs, Ian, Das, Arnab, Baranowski, Mark, Sharma, Vishal, Krishnamoorthy, Sriram, Rakamaric, Zvonimir, and Gopalakrishnan, Ganesh. Wed . "FailAmp: Relativization Transformation for Soft Error Detection in Structured Address Generation". United States. https://doi.org/10.1145/3369381. https://www.osti.gov/servlets/purl/1599993.
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@article{osti_1599993,
title = {FailAmp: Relativization Transformation for Soft Error Detection in Structured Address Generation},
author = {Briggs, Ian and Das, Arnab and Baranowski, Mark and Sharma, Vishal and Krishnamoorthy, Sriram and Rakamaric, Zvonimir and Gopalakrishnan, Ganesh},
abstractNote = {We present FailAmp, a novel LLVM program transformation algorithm that makes programs employing structured index calculations more robust against soft-errors. Without FailAmp, an offset error can go undetected; with FailAmp, all subsequent offsets are relativized, building on the faulty one. FailAmp can exploit ISAs such as ARM to further reduce overheads. We verify correctness properties of FailAMP using an SMT solver, and present a thorough evaluation using many HPC benchmarks under a fault injection campaign. FailAmp provides full soft-error detection for address calculation while incurring an average overhead of around 5%.},
doi = {10.1145/3369381},
journal = {ACM Transactions on Architecture and Code Optimization},
number = 4,
volume = 16,
place = {United States},
year = {Wed Dec 18 00:00:00 EST 2019},
month = {Wed Dec 18 00:00:00 EST 2019}
}
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Publisher's Version of Record
https://doi.org/10.1145/3369381
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