Tag Archives: Resilient

A Low-cost Fault Corrector for Deep Neural Networks through Range Restriction

Zitao Chen, Guanpeng Li, and Karthik Pattabiraman, To appear in the IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), 2021. (Acceptance Rate: 16.5%). [ PDF | Talk ] (arXIV, code)
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An Empirical Study of the Impact of Single and Multiple Bit-Flip Errors in Programs

Behrooz Sangchoolie, Karthik Pattabiraman and Johan Karlsson, To appear in the IEEE Transactions on Dependable and Secure Computing (TDSC). [ PDF ]
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New Wine in an Old Bottle: N-Version Programming for Machine Learning Components

Arpan Gujarati, Sathish Gopalakrishnan, and Karthik Pattabiraman, IEEE International Workshop on Software Certification (WoSoCER), 2020. Held in conjunction with the IEEE International Symposium on Software Reliability Engineering (ISSRE), 2020. [PDF][Talk]
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How Far Have We Come in Detecting Anomalies in Distributed Systems? An Empirical Study with a Statement-level Fault Injection Method

Yong Yang, Yifan Yu, Karthik Pattabiraman, Long Wang, Ying Li, IEEE International Symposium on Software Reliability Engineering (ISSRE), 2020. (Acceptance Rate: 26%). [ PDF | Talk ] (Code)
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TensorFI: A Flexible Fault Injection Framework for TensorFlow Applications

Zitao Chen, Niranjhana Narayanan, Bo Fang, Guanpeng Li, Karthik Pattabiraman, and Nathan DeBardeleben, IEEE International Symposium on Software Reliability Engineering (ISSRE), 2020. (Acceptance Rate: 26%) [ PDF | Talk ] (Code)
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GPU-TRIDENT: Efficient Modeling of Error Propagation in GPU Programs

Abdul Rehman Anwer, Guanpeng Li, Karthik Pattabiraman, Michael Sullivan, Timothy Tsai and Siva Hari, ACM International Conference on High-Performance Computing, Networking, Storage, and Analyzis (SC), 2020 (Acceptance Rate: 25.1%) [PDF | Talk] (Code)
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TraceSanitizer – Eliminating the Effects of Non-determinism on Error Propagation Analysis

Habib Saissi, Stefan Winter, Oliver Schwan, Karthik Pattabiraman, and Neeraj Suri, IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), 2020. (Acceptance Rate: 16.5%). [PDF | Talk] (Code)
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Improving the Accuracy of IR-Level Fault Injection

Lucas Palazzi, Guanpeng Li, Bo Fang, and Karthik Pattabiraman, To appear in the IEEE Transactions on Dependable and Secure Computing (TDSC). (Acceptance date: March 2020). [PDF] (Code)
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A Tale of Two Injectors: End-to-End Comparison of IR-level and Assembly-Level Fault Injection

Lucas Palazzi, Guanpeng Li, Bo Fang, and Karthik Pattabiraman, IEEE International Symposium on Software Reliability Engineering (ISSRE), 2019. (Acceptance Rate: 31.4%) [ PDF | Talk ] (code)
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BinFI: An Efficient Fault Injector for Safety-Critical Machine Learning Systems

Zitao Chen, Guanpeng Li, Karthik Pattabiraman, and Nathan DeBardeleben, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC), 2019. (Acceptance Rate: 21%) [ PDF | Talk ] ( Code Finalist for the SC reproducibility challenge (one of 3 papers))
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