Algorithm based fault tolerance (ABFT) attracts renewed interest for its extremely low overhead and good scalability. However the fault model used to design ABFT has been either abstract, simplistic, or both, leaving a gap between what occurs at the architecture level and what the algorithm expects. As the fault model is the deciding factor in choosing an effective checksum scheme, the resulting ABFT techniques have seen limited impact in practice. In this paper we seek to close the gap by directly using a comprehensive architectural fault model and devise a comprehensive ABFT scheme that can tolerate multiple architectural faults of various kinds. We implement the new ABFT scheme into high performance linpack (HPL) to demonstrate the feasibility in large scale high performance benchmark. We conduct architectural fault injection experiments and large scale experiments to empirically validate its fault tolerance and demonstrate the overhead of error handling, respectively.
P. Wu et al., "Towards Practical Algorithm based Fault Tolerance in Dense Linear Algebra," Proceedings of the 25th ACM International Symposium on High-Performance Parallel and Distributed Computing (2016, Kyoto, Japan), pp. 31-42, Association for Computing Machinery (ACM), May 2016.
The definitive version is available at https://doi.org/10.1145/2907294.2907315
25th ACM International Symposium on High-Performance Parallel and Distributed Computing, HPDC '16 (2016: May 31-Jun. 4, Kyoto, Japan)
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Article - Conference proceedings
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31 May 2016