ELZAR: Triple Modular Redundancy Using Intel AVX (Practical Experience Report)

D. Kuvaiskii, O. Oleksenko, P. Bhatotia, P. Felber, C. Fetzer

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Instruction-Level Redundancy (ILR) is a well-known approach to tolerate transient CPU faults. It replicates instructions in a program and inserts periodic checks to detect and correct CPU faults using majority voting, which essentially requires three copies of each instruction and leads to high performance overheads. As SIMD technology can operate simultaneously on several copies of the data, it appears to be a good candidate for decreasing these overheads. To verify this hypothesis, we propose ELZAR, a compiler framework that transforms unmodified multithreaded applications to support triple modular redundancy using Intel AVX extensions for vectorization. Our experience with several benchmark suites and real-world case-studies yields mixed results: while SIMD may be beneficial for some workloads, e.g., CPU-intensive ones with many floating-point operations, it exposes higher overhead than ILR in many applications we tested.
Original languageEnglish
Title of host publicationDependable Systems and Networks (DSN), 2016 46th Annual IEEE/IFIP International Conference on
Place of PublicationToulouse, France
PublisherInstitute of Electrical and Electronics Engineers
Pages646-653
Number of pages8
ISBN (Electronic)978-1-4673-8892-4
ISBN (Print)978-1-4673-8891-7
DOIs
Publication statusPublished - 3 Oct 2016
Event46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks - Toulouse, France
Duration: 28 Jun 20161 Jul 2016
https://dsn-2016.sciencesconf.org/

Conference

Conference46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks
Abbreviated titleDSN 2016
Country/TerritoryFrance
CityToulouse
Period28/06/161/07/16
Internet address

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