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Hardware-Based Efficiency Advances in the EXA-DUNE Project Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Handling Silent Data Corruption with the Sparse Grid Combination Technique

Authors : Alfredo Parra Hinojosa, Brendan Harding, Markus Hegland, Hans-Joachim Bungartz

Published in: Software for Exascale Computing - SPPEXA 2013-2015

Publisher: Springer International Publishing

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Abstract

We describe two algorithms to detect and filter silent data corruption (SDC) when solving time-dependent PDEs with the Sparse Grid Combination Technique (SGCT). The SGCT solves a PDE on many regular full grids of different resolutions, which are then combined to obtain a high quality solution. The algorithm can be parallelized and run on large HPC systems. We investigate silent data corruption and show that the SGCT can be used with minor modifications to filter corrupted data and obtain good results. We apply sanity checks before combining the solution fields to make sure that the data is not corrupted. These sanity checks are derived from well-known error bounds of the classical theory of the SGCT and do not rely on checksums or data replication. We apply our algorithms on a 2D advection equation and discuss the main advantages and drawbacks.

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previous chapter Scalable Algorithms for the Solution of Higher-Dimensional PDEs
next chapter Hybrid Parallel Multigrid Methods for Geodynamical Simulations
Footnotes
1
For a detailed discussion on the boundary treatment, see [30].
 
2
The authors in [10] use a factor of 10+150 to cover all possible orders of magnitude, but we choose 10+5 simply to keep the axes of our error plots visible. The results are equally valid for 10+150.
 
3
The assumption that SDC occurs only once in the simulation is explained in [10].
 
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Metadata
Title
Handling Silent Data Corruption with the Sparse Grid Combination Technique
Authors
Alfredo Parra Hinojosa
Brendan Harding
Markus Hegland
Hans-Joachim Bungartz
Copyright Year
2016
Book
Software for Exascale Computing - SPPEXA 2013-2015

Print ISBN: 978-3-319-40526-1

Electronic ISBN: 978-3-319-40528-5

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-40528-5_9

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