Abstract | ||
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The ever-increasing size of High Performance Computing (HPC) systems inevitably causes an unwanted decrease of Mean Time Between Failures (MTBF). For this reason, over the last decade, much work has been done on the topic of fault tolerance for supercomputers. In particular, as large-scale linear algebra applications permeate many scientific fields, important efforts have been focused on the performance enhancements that could be provided by HPC infrastructures if reliable fault tolerant solutions are adopted. This article explores a popular topic of linear algebra (i.e., linear equation system resolution) and proposes an efficient, error-resilient approach based on an existing technique called Inhibition Method (IMe). Initially conceived to analyse complex electric circuits and later extended to solve linear systems, the original method is here enhanced with a simple, yet effective strategy to provide tolerance to single fail-stop recurring to neither checkpointing, nor rollbacks. Experimental results on a medium-scale HPC architecture show negligible overheads and promising performance improvements when compared with a popular fault-tolerant solving technique. |
Year | DOI | Venue |
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2019 | 10.1109/SRDS47363.2019.00022 | 2019 38th Symposium on Reliable Distributed Systems (SRDS) |
Keywords | DocType | ISSN |
fault tolerance, High Performance Computing, algebraic linear systems, Inhibition Method | Conference | 1060-9857 |
ISBN | Citations | PageRank |
978-1-7281-4223-4 | 1 | 0.35 |
References | Authors | |
28 | 3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Marcello Artioli | 1 | 1 | 0.35 |
Daniela Loreti | 2 | 28 | 6.55 |
A. Ciampolini | 3 | 3 | 1.74 |