Tag Archives: Justin

Fault Injection for TensorFlow Applications

Niranjhana Narayanan, Zitao Chen, Bo Fang, Guanpeng Li, Karthik Pattabiraman, and Nathan DeBardeleben, IEEE Transactions on Dependable and Secure Computing (TDSC). Acceptance Date: May 2022. [ PDF ] (code1, code2)
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PID-Piper: Recovering Robotic Vehicles from Physical Attacks

Pritam Dash, Guanpeng Li, Zitao Chen, Mehdi Karimibiuki, and Karthik Pattabiraman, IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), 2021. (Acceptance Rate: 16.5%). [ PDF | Talk, Talk Video ] (Code, PID-Piper Videos) Best Paper Award (1 of nearly 300 submissions).
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A Low-cost Fault Corrector for Deep Neural Networks through Range Restriction

Zitao Chen, Guanpeng Li, and Karthik Pattabiraman, IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), 2021. (Acceptance Rate: 16.5%). [ PDF | Talk , Video] (arXIV, code) Best Paper Award Runner up (1 of 2 among nearly 300 submissions). Incorporated into Intel’s OpenVino2 Framework (More details, Documentation).
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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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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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TensorFI: A Configurable Fault Injector for TensorFlow Applications

Guanpeng Li, Karthik Pattabiraman, and Nathan DeBardeleben, Workshop on Software Certification (WoSoCER), 2018, co-located with the IEEE International Symposium on Software Reliability Engineering (ISSRE). 2018. [ PDF | Talk Slides ] (Code)
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Modeling Soft-Error Propagation in Programs

Guanpeng Li, Karthik Pattabiraman, Siva Kumar Sastry Hari, Michael Sullivan, and Timothy Tsai. IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), 2018. (Acceptance Rate for Regular Papers: 25%) [ PDF | Talk ] (Link to Code) (Best Paper Runner up)
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