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- research-articleJanuary 2022
Characterizing and Exploiting Soft Error Vulnerability Phase Behavior in GPU Applications
IEEE Transactions on Dependable and Secure Computing (TDSC), Volume 19, Issue 1Pages 288–300https://doi.org/10.1109/TDSC.2020.2991136System reliability has become a first-class design constraint. As the use of Graphics Processing Units (GPU) continues to increase in compute applications, including High Performance Computing (HPC) and safety-critical applications, so do the number of ...
- research-articleMay 2020
ArmorAll: Compiler-based Resilience Targeting GPU Applications
ACM Transactions on Architecture and Code Optimization (TACO), Volume 17, Issue 2Article No.: 9, Pages 1–24https://doi.org/10.1145/3382132The vulnerability of GPUs to soft errors has become a first-class design concern as they are increasingly being used in accuracy-sensitive and safety-critical domains. Existing solutions used to enhance the reliability of GPUs come with significant ...
PRISM: predicting resilience of GPU applications using statistical methods
SC '18: Proceedings of the International Conference for High Performance Computing, Networking, Storage, and AnalysisArticle No.: 69, Pages 1–14https://doi.org/10.1109/SC.2018.00072As Graphics Processing Units (GPUs) become more pervasive in High Performance Computing (HPC) and safety-critical domains, ensuring that GPU applications can be protected from data corruption grows in importance. Despite prior efforts to mitigate errors,...
PRISM: predicting resilience of GPU applications using statistical methods
SC '18: Proceedings of the International Conference for High Performance Computing, Networking, Storage, and AnalysisArticle No.: 69, Pages 1–14As Graphics Processing Units (GPUs) become more pervasive in High Performance Computing (HPC) and safety-critical domains, ensuring that GPU applications can be protected from data corruption grows in importance. Despite prior efforts to mitigate errors,...
- research-articleJanuary 2015
NUPAR: A Benchmark Suite for Modern GPU Architectures
- Yash Ukidave,
- Fanny Nina Paravecino,
- Leiming Yu,
- Charu Kalra,
- Amir Momeni,
- Zhongliang Chen,
- Nick Materise,
- Brett Daley,
- Perhaad Mistry,
- David Kaeli
ICPE '15: Proceedings of the 6th ACM/SPEC International Conference on Performance EngineeringPages 253–264https://doi.org/10.1145/2668930.2688046Heterogeneous systems consisting of multi-core CPUs, Graphics Processing Units (GPUs) and many-core accelerators have gained widespread use by application developers and data-center platform developers. Modern day heterogeneous systems have evolved to ...
- ArticleOctober 2014
Runtime Support for Adaptive Spatial Partitioning and Inter-Kernel Communication on GPUs
SBAC-PAD '14: Proceedings of the 2014 IEEE 26th International Symposium on Computer Architecture and High Performance ComputingPages 168–175https://doi.org/10.1109/SBAC-PAD.2014.43GPUs have gained tremendous popularity in a broad range of application domains. These applications possess varying grains of parallelism and place high demands on compute resources--many times imposing real-time constraints, requiring flexible work ...