Paper Info
Title
Elzar: Triple Modular Redundancy using Intel Advanced Vector Extensions (technical report).
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 exhibits higher overhead than ILR in many applications we tested. We study the sources of overheads and discuss possible improvements to Intel AVX that would lead to better performance.
Year
Venue
Field
2016
arXiv: Distributed, Parallel, and Cluster Computing
Computer science,Vectorization (mathematics),SIMD,Real-time computing,Redundancy (engineering),Majority rule,Technical report,Distributed computing,Overhead (business),Parallel computing,Triple modular redundancy,Compiler,Embedded system
DocType
Volume
Citations 
Journal
abs/1604.00500
2
PageRank 
References 
Authors
0.37
22
5
Name
Order
Citations
PageRank
Dmitrii Kuvaiskii1586.42
Oleksii Oleksenko2413.50
Pramod Bhatotia341428.94
Pascal Felber42432178.76
Christof Fetzer52429172.89