Detection and Correction of Silent Data Corruption for Large-Scale High-Performance Computing

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Provided by: Institute of Electrical & Electronic Engineers
Topic: Big Data
Format: PDF
Faults have become the norm rather than the exception for high-end computing clusters. Exacerbating this situation, some of these faults remain undetected, manifesting themselves as silent errors that allow applications to compute incorrect results. This paper studies the potential for redundancy to detect and correct soft errors in MPI message-passing applications while investigating the challenges inherent to detecting soft errors within MPI applications by providing transparent MPI redundancy. By assuming a model wherein corruption in application data manifests itself by producing differing MPI messages between replicas, the authors study the best suited protocols for detecting and correcting corrupted MPI messages.
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