Qiang Guan
Cited by
Cited by
Adaptive anomaly identification by exploring metric subspace in cloud computing infrastructures
Q Guan, S Fu
2013 IEEE 32nd International Symposium on Reliable Distributed Systems, 205-214, 2013
Ensemble of Bayesian predictors and decision trees for proactive failure management in cloud computing systems.
Q Guan, Z Zhang, S Fu
J. Commun. 7 (1), 52-61, 2012
F-sefi: A fine-grained soft error fault injection tool for profiling application vulnerability
Q Guan, N Debardeleben, S Blanchard, S Fu
2014 IEEE 28th International Parallel and Distributed Processing Symposium …, 2014
Cda: A cloud dependability analysis framework for characterizing system dependability in cloud computing infrastructures
Q Guan, CC Chiu, S Fu
2012 IEEE 18th Pacific Rim International Symposium on Dependable Computing …, 2012
Proactive failure management by integrated unsupervised and semi-supervised learning for dependable cloud systems
Q Guan, Z Zhang, S Fu
2011 Sixth International Conference on Availability, Reliability and …, 2011
An anomaly detection framework for autonomic management of compute cloud systems
D Smith, Q Guan, S Fu
2010 IEEE 34th Annual Computer Software and Applications Conference …, 2010
Towards practical algorithm based fault tolerance in dense linear algebra
P Wu, Q Guan, N DeBardeleben, S Blanchard, D Tao, X Liang, J Chen, ...
Proceedings of the 25th ACM International Symposium on High-Performance …, 2016
Ensemble of bayesian predictors for autonomic failure management in cloud computing
Q Guan, Z Zhang, S Fu
2011 Proceedings of 20th International Conference on Computer Communications …, 2011
Experimental framework for injecting logic errors in a virtual machine to profile applications for soft error resilience
N DeBardeleben, S Blanchard, Q Guan, Z Zhang, S Fu
European Conference on Parallel Processing, 282-291, 2011
Silent data corruption resilient two-sided matrix factorizations
P Wu, N DeBardeleben, Q Guan, S Blanchard, J Chen, D Tao, X Liang, ...
Proceedings of the 22nd ACM SIGPLAN Symposium on Principles and Practice of …, 2017
auto-AID: A data mining framework for autonomic anomaly identification in networked computer systems
Q Guan, S Fu
International Performance Computing and Communications Conference, 73-80, 2010
Letgo: A lightweight continuous framework for hpc applications under failures
B Fang, Q Guan, N Debardeleben, K Pattabiraman, M Ripeanu
Proceedings of the 26th International Symposium on High-Performance Parallel …, 2017
An adaptive power management framework for autonomic resource configuration in cloud computing infrastructures
Z Zhang, Q Guan, S Fu
2012 IEEE 31st International Performance Computing and Communications …, 2012
Qugan: A generative adversarial network through quantum states
SA Stein, B Baheri, D Chen, Y Mao, Q Guan, A Li, B Fang, S Xu
arXiv preprint arXiv:2010.09036, 2020
Interactions between earthworms and mesofauna has no significant effect on emissions of CO2 and N2O from soil
H Wu, M Lu, X Lu, Q Guan, X He
Soil Biology and Biochemistry 88, 294-297, 2015
TSM2: optimizing tall-and-skinny matrix-matrix multiplication on GPUs
J Chen, N Xiong, X Liang, D Tao, S Li, K Ouyang, K Zhao, ...
Proceedings of the ACM International Conference on Supercomputing, 106-116, 2019
Design, use and evaluation of p-fsefi: A parallel soft error fault injection framework for emulating soft errors in parallel applications
Q Guan, N BeBardeleben, P Wu, S Eidenbenz, S Blanchard, L Monroe, ...
Proceedings of the 9th EAI International Conference on Simulation Tools and …, 2016
Efficient and accurate anomaly identification using reduced metric space in utility clouds
Q Guan, CC Chiu, Z Zhang, S Fu
2012 IEEE Seventh International Conference on Networking, Architecture, and …, 2012
Snail (Mollusca: Gastropoda) assemblages as indicators of ecological condition in freshwater wetlands of Northeastern China
H Wu, Q Guan, X Lu, DP Batzer
Ecological Indicators 75, 203-209, 2017
Anomaly detection in large-scale coalition clusters for dependability assurance
Q Guan, D Smith, S Fu
2010 International Conference on High Performance Computing, 1-10, 2010
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