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Detection and correction of silent data corruption for large-scale high-performance computing.
| Content Provider | CiteSeerX |
|---|---|
| Author | Fiala, David Mueller, Frank Engelmann, Christian |
| Abstract | Abstract—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, we study the best suited protocols for detecting and correcting corrupted MPI messages. Using our fault injector, we observe that even a single error can have profound effects on applications by causing a cascading pattern of corruption which in most cases spreads to all other processes. Results indicate that our consistency protocols can successfully protect applications experiencing even high rates of silent data corruption. I. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Silent Data Corruption Large-scale High-performance Computing Soft Error Mpi Message Mpi Message-passing Application Cascading Pattern Single Error Mpi Application Fault Injector High Rate Abstract Fault Transparent Mpi Redundancy Silent Error Incorrect Result Suited Protocol Case Spread Profound Effect Application Data Manifest Paper Study Consistency Protocol Model Wherein Corruption |
| Content Type | Text |
| Resource Type | Article |
