F_Radish: Enhancing Silent Data Corruption Detection for Aerospace-Based Computing
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Lightweight and Accurate Silent Data Corruption Detection in Ordinary Di erential Equation Solvers
Silent data corruptions (SDCs) are errors that corrupt the system or falsify results while remaining unnoticed by firmware or operating systems. In numerical integration solvers, SDCs that impact the accuracy of the solver are considered significant. Detecting SDCs in high-perfor
Lightweight and Accurate Silent Data Corruption Detection in Ordinary Differential Equation Solvers
Silent data corruptions (SDCs) are errors that corrupt the system or falsify results while remaining unnoticed by firmwares or operating systems. In numerical integration solvers, SDCs that impact the accuracy of the solver are considered significant. Detecting SDCs in high-perfo
Exploring Partial Replication to Improve Lightweight Silent Data Corruption Detection for HPC Applications
Silent data corruption (SDC) poses a great challenge for high-performance computing (HPC) applications as we move to extremescale systems. If not dealt with properly, SDC has the potential to influence important scientific results, leading scientists to wrong conclusions. In prev
Detecting Silent Data Corruptions in Aerospace-Based Computing Using Program Invariants
Toward General Software Level Silent Data Corruption Detection for Parallel Applications
Sirius: Probabilistic data assertions for detecting silent data corruption in parallel programs
The size and complexity of supercomputing clusters are rapidly increasing to cater to the needs of complex scientific applications. At the same time, the feature size and operating voltage level of the internal components are decreasing. This dual trend makes these machines extre