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A Case for Soft Error Detection and Correction in Computational Chemistry
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/jcc.540161010openalex-snapshot
Approaches to large‐scale parallel self‐consistent field calculations
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The influence of polarization functions on molecular orbital hydrogenation energies
inferredcites →https://doi.org/10.1021/ct100439uopenalex-snapshot
Designing a Scalable Fault Tolerance Model for High Performance Computational Chemistry: A Case Study with Coupled Cluster Perturbative Triples
inferredcites →https://doi.org/10.1063/1.1677527openalex-snapshot
Self—Consistent Molecular Orbital Methods. XII. Further Extensions of Gaussian—Type Basis Sets for Use in Molecular Orbital Studies of Organic Molecules
inferredcites →https://doi.org/10.1109/ipdps.2007.370626openalex-snapshot
Automatic Path Migration over InfiniBand: Early Experiences
inferredcites →https://doi.org/10.1145/1375527.1375552openalex-snapshot
Soft error vulnerability of iterative linear algebra methods
inferredcites →https://doi.org/10.1145/2304576.2304611openalex-snapshot
An analysis of computational workloads for the ORNL Jaguar system
inferredcites →https://doi.org/10.1177/1094342009347766openalex-snapshot
IESP Exascale Challenge: Co-Design of Architectures and Algorithms
inferredcites →https://doi.org/10.17487/rfc6151openalex-snapshot
Updated Security Considerations for the MD5 Message-Digest and the HMAC-MD5 Algorithms
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Handling Silent Data Corruption with the Sparse Grid Combination Technique
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Scalable Algorithmic Detection of Silent Data Corruption for High-Dimensional PDEs
inferred← citeshttps://doi.org/10.1007/s11227-016-1752-5openalex-snapshot
Rolex: resilience-oriented language extensions for extreme-scale systems
inferred← citeshttps://doi.org/10.1021/acs.chemrev.0c00998openalex-snapshot
From NWChem to NWChemEx: Evolving with the Computational Chemistry Landscape
inferred← citeshttps://doi.org/10.1109/hipc.2016.012openalex-snapshot
Fault Tolerant Frequent Pattern Mining
inferred← citeshttps://doi.org/10.1109/hpec.2015.7322460openalex-snapshot
Enabling application resilience through programming model based fault amelioration
inferred← citeshttps://doi.org/10.1109/ipdps.2014.128openalex-snapshot
F-SEFI: A Fine-Grained Soft Error Fault Injection Tool for Profiling Application Vulnerability
inferred← citeshttps://doi.org/10.1109/ipdps.2016.111openalex-snapshot
Fault Modeling of Extreme Scale Applications Using Machine Learning
inferred← citeshttps://doi.org/10.1145/3624062.3624256openalex-snapshot
Asynchronous Multi-Level Checkpointing: An Enabler of Reproducibility using Checkpoint History Analytics
inferred← citeshttps://doi.org/10.1177/1094342014532297openalex-snapshot
Silent error detection in numerical time-stepping schemes
inferred← citeshttps://doi.org/10.12794/metadc499993openalex-snapshot
Autonomic Failure Identification and Diagnosis for Building Dependable Cloud Computing Systems
inferred← citeshttps://doi.org/10.2172/1338552openalex-snapshot
Resilience Design Patterns - A Structured Approach to Resilience at Extreme Scale (version 1.0)
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inferred← citeshttps://doi.org/10.2172/1922296openalex-snapshot
Resilience Design Patterns: A Structured Approach to Resilience at Extreme Scale (V.2.0)
inferred← citeshttps://doi.org/10.3390/catal7010002openalex-snapshot
Strengths, Weaknesses, Opportunities and Threats: Computational Studies of Mn- and Fe-Catalyzed Epoxidations
inferred← citeshttps://doi.org/10.4018/978-1-5225-0287-6.ch011openalex-snapshot
Analyzing the Robustness of HPC Applications Using a Fine-Grained Soft Error Fault Injection Tool
inferred← citeshttps://doi.org/10.48550/arxiv.1401.3013openalex-snapshot
Resilience in Numerical Methods: A Position on Fault Models and Methodologies
inferred← citeshttps://doi.org/10.48550/arxiv.1605.01994openalex-snapshot
Rolex: Resilience-Oriented Language Extensions for Extreme-Scale Systems
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