Publications After 2020
† My advisee
2023
A Feature-Driven Fixed-Ratio Lossy Compression Framework for Real-World Scientific Datasets
Md Hasanur Rahman†, Sheng Di, Kai Zhao, Robert Underwood, Guanpeng Li, Franck Cappello
[ICDE'23]: IEEE International Conference on Data Engineering
2022
SALUS: A Novel Data-Driven Approach for Enabling Real-Time Safety of Autonomous Vehicles
Bohan Zhang†, Yafan Huang†, Guanpeng Li
[QRS'22]: IEEE International Conference on Software Quality, Reliability, and Security
Characterizing Deep Learning Neural Network Failures between Algorithmic Inaccuracy and Transient Hardware Faults
Sabuj Laskar†, Md Hasanur Rahman†, Bohan Zhang†, Guanpeng Li
[PRDC'22]: IEEE Pacific Rim International Symposium on Dependable Computing
Mitigating Silent Data Corruptions in HPC Applications across Multiple Program Inputs
Yafan Huang†, Shengjian Guo, Sheng Di, Guanpeng Li, Franck Cappello
[SC'22]: International Conference for High-Performance Computing, Networking, Storage and Analysis
Best Paper Award Finalist; Best Student Paper Award Finalist Fault Injection for TensorFlow Applications
Niranjhana Narayanany, Zitao Chen, Bo Fang, Guanpeng Li, Karthik Pattabiraman, Nathan DeBardeleben
[TDSC]: IEEE Transactions on Dependable and Secure Computing COMET: A Novel Memory-Efficient Deep Learning Training Framework by Using Error-Bounded Lossy Compression
Sian Jin, Chengming Zhang, Jiannan Tian, Yunhe Feng, Hui Guan, Guanpeng Li, Shuaiwen Leon Song, Dingwen Tao
[VLDB'22]: International Conference on Very Large Data Bases
2021
Peppa-X: Finding Program Test Inputs to Bound Silent Data Corruption Vulnerability in HPC Applications
Md Hasanur Rahman†, Aabid Shamji†, Shengjian Guo, Guanpeng Li
[SC'21]: International Conference for High-Performance Computing, Networking, Storage and Analysis (Acceptance rate: 23.6%) A Low-cost Fault Corrector for Deep Neural Networks through Range Restriction
Zitao Chen, Guanpeng Li, and Karthik Pattabiraman
[DSN'21]: IEEE/IFIP International Conference on Dependable Systems and Networks (Acceptance rate: 16.5%)
Best Paper Award Runner-Up PID-Piper: Recovering Robotic Vehicles from Physical Attacks
Pritam Dash, Guanpeng Li, Zitao Chen, Mehdi Karimibiuki, and Karthik Pattabiraman
[DSN'21]: IEEE/IFIP International Conference on Dependable Systems and Networks (Acceptance rate: 16.5%)
Best Paper Award
Publications Before 2020
GPU-TRIDENT: Efficient Modeling of Error Propagation in GPU Programs
Abdul Rehman Anwer, Guanpeng Li, Karthik Pattabiraman, Michael Sullivan, Timothy Tsai and Siva Hari
[SC'20]: International Conference for High-Performance Computing, Networking, Storage and Analysis (SC), 2020 (Acceptance rate: 25%) TensorFI: A Flexible Fault Injection Framework for TensorFlow Applications.
Zitao Chen, Niranjhana Narayanan, Bo Fang, Guanpeng Li, Karthik Pattabiraman, and Nathan DeBardeleben
[ISSRE'20]: Proceedings of IEEE International Symposium on Software Reliability Engineering (ISSRE), 2020 (Acceptance Rate: 25%) AV-Fuzzer: Finding Safety Violations in Autonomous Driving Systems.
Guanpeng Li, Yiran Li, Saurabh Jha, Tim Tsai, Mike Sullivan, Siva Hari, Zbigniew Kalbarczyk and Ravi Iyer
[ISSRE'20]: Proceedings of IEEE International Symposium on Software Reliability Engineering (ISSRE), 2020 (Acceptance Rate: 25%)
Best Paper Award
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
[ISSRE'19]: IEEE International Conference on Software Reliability Engineering (Acceptance Rate: 31%)
BinFI: An Efficient Fault Injector for Safety-Critical Machine Learning Systems
Zitao Chen, Guanpeng Li, Karthik Pattabiraman, and Nathan DeBardeleben
[SC'19]: International Conference for High-Performance Computing, Networking, Storage and Analysis (Acceptance Rate: 21%) Improving the Accuracy of IR-Level Fault Injection
Lucas Palazzi, Guanpeng Li, Bo Fang, and Karthik Pattabiraman
[TDSC]: IEEE Transactions on Dependable and Secure Computing, 2019 Modeling Soft-Error Propagation in Programs
Guanpeng Li, Karthik Pattabiraman, Siva Hari, Mike Sullivan, and Tim Tsai
[DSN'18]: IEEE/IFIP International Conference on Dependable Systems and Networks (Acceptance Rate: 25%)
Best Paper Award Runner-Up Modeling Input-Dependent Error Propagation in Programs
Guanpeng Li and Karthik Pattabiraman
[DSN'18]: IEEE/IFIP International Conference on Dependable Systems and Networks (Acceptance Rate: 25%) Understanding Error Propagation in Deep-Learning Neural Network (DNN) Accelerators and Applications
Guanpeng Li, Siva Hari, Mike Sullivan, Tim Tsai, Karthik Pattabiraman, Joel Emer, and Steve Keckler
[SC'17]: International Conference for High-Performance Computing, Networking, Storage and Analysis (Acceptance Rate: 19%)
Understanding Error Propagation in GPGPU Applications
Guanpeng Li, Karthik Pattabiraman, Chen-Yong Cher, and Pradip Bose
[SC'16]: International Conference for High-Performance Computing, Networking, Storage and Analysis (Acceptance Rate: 18%) Configurable Detection of SDC-Causing Errors in Programs
Qining Lu, Guanpeng Li, Karthik Pattabiraman, Meeta S. Gupta and Jude A. Rivers
[TECS'16]: ACM Transactions on Embedded Computing Systems (TECS), 2016 Experience Report: An Application-specific Checkpointing Technique for Minimizing Checkpoint Corruption
Guanpeng Li, Karthik Pattabiraman, Chen-Yong Cher, and Pradip Bose
[ISSRE'15]: IEEE International Conference on Software Reliability Engineering (Acceptance Rate: 32%) Fined-grained Characterization of Long Latency Causing Crashes in Programs
Guanpeng Li, Qining Lu, and Karthik Pattabiraman
[DSN'15]: IEEE/IFIP International Conference on Dependable Systems and Networks (Acceptance Rate: 22%) AutoFLox: An Automatic Fault Localizer for Client-Side JavaScript
Frolin Ocariza, Guanpeng Li, Karthik Pattabiraman and Ali Mesbah
[STVR'15]: IEEE Software Testing, Verification and Reliability (STVR), 2015 Quantifying the Accuracy of High-Level Fault Injection Techniques for Hardware Faults
Jiesheng Wei, Anna Thomas, Guanpeng Li, and Karthik Pattabiraman
[DSN'14]: IEEE/IFIP International Conference on Dependable Systems and Networks (Acceptance Rate: 30%)
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