Tag Archives: Justin

GPU-TRIDENT: Efficient Modeling of Error Propagation in GPU Programs

Posted on June 30, 2020 | Comments Off on GPU-TRIDENT: Efficient Modeling of Error Propagation in GPU Programs

Abdul Rehman Anwer, Guanpeng Li, Karthik Pattabiraman, Michael Sullivan, Timothy Tsai and Siva Hari, To appear in the ACM International Conference on High-Performance Computing, Networking, Storage, and Analyzis (SC), 2020 (Acceptance Rate: TBD) [PDF (coming soon) | Talk] (Code)
Continue reading →

Comments Off on GPU-TRIDENT: Efficient Modeling of Error Propagation in GPU Programs

Posted in papers

Tagged , , , , ,

Improving the Accuracy of IR-Level Fault Injection

Posted on April 4, 2020 | Comments Off on 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)
Continue reading →

Comments Off on Improving the Accuracy of IR-Level Fault Injection

Posted in papers

Tagged , , , , , ,

A Tale of Two Injectors: End-to-End Comparison of IR-level and Assembly-Level Fault Injection

Posted on July 21, 2019 | Comments Off on 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)
Continue reading →

Comments Off on A Tale of Two Injectors: End-to-End Comparison of IR-level and Assembly-Level Fault Injection

Posted in papers

Tagged , , , , , ,

BinFI: An Efficient Fault Injector for Safety-Critical Machine Learning Systems

Posted on June 16, 2019 | Comments Off on 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))
Continue reading →

Comments Off on BinFI: An Efficient Fault Injector for Safety-Critical Machine Learning Systems

Posted in papers

Tagged , , , , ,

TensorFI: A Configurable Fault Injector for TensorFlow Applications

Posted on October 15, 2018 | Comments Off on 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)
Continue reading →

Comments Off on TensorFI: A Configurable Fault Injector for TensorFlow Applications

Posted in papers

Tagged , , , ,

Modeling Soft-Error Propagation in Programs

Posted on March 4, 2018 | Comments Off on 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)
Continue reading →

Comments Off on Modeling Soft-Error Propagation in Programs

Posted in papers

Tagged , , , ,

Modeling Input Dependent Error Propagation in Programs

Posted on March 4, 2018 | Comments Off on Modeling Input Dependent Error Propagation in Programs

Guanpeng Li and Karthik Pattabiraman, IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), 2018. (Acceptance Rate for Regular Papers: 25%) [PDF | Talk] (Link to Code)
Continue reading →

Comments Off on Modeling Input Dependent Error Propagation in Programs

Posted in papers

Tagged , , , ,

Understanding Error Propagation in Deep-Learning Neural Networks (DNN) Accelerators and Applications

Posted on June 15, 2017 | Comments Off on Understanding Error Propagation in Deep-Learning Neural Networks (DNN) Accelerators and Applications

Guanpeng Li, Siva Hari, Michael Sullivan, Timothy Tsai, Karthik Pattabiraman, Joel Emer, Stephen Keckler, International Conference for High-Performance Computing, Networking, Storage and Analysis (SC), 2017. (Acceptance Rate: 19%) [PDF | Talk] (Injector code)
Continue reading →

Comments Off on Understanding Error Propagation in Deep-Learning Neural Networks (DNN) Accelerators and Applications

Posted in papers

Tagged , , , ,

Configurable Detection of SDC-Causing Errors in Programs

Posted on November 3, 2016 | Comments Off on Configurable Detection of SDC-Causing Errors in Programs

Qining Lu, Guanpeng Li, Karthik Pattabiraman, Meeta Gupta and Jude Rivers, To appear in the ACM Transactions on Embedded Computing Systems (TECS). [ PDF ]
Continue reading →

Comments Off on Configurable Detection of SDC-Causing Errors in Programs

Posted in papers

Tagged , , , , ,

Understanding Error Propagation in GPGPU Applications

Posted on June 20, 2016 | Comments Off on Understanding Error Propagation in GPGPU Applications

Guanpeng Li, Karthik Pattabiraman, Chen-Yong Cher and Pradip Bose, International Conference for High-Performance Computing, Storage and Networking (SC), 2016. (Acceptance Rate: 18%) [PDF | Talk ] (Link to LLFI-GPU) Continue reading →

Comments Off on Understanding Error Propagation in GPGPU Applications

Posted in papers

Tagged , , , ,