Exploring the capabilities of support vector machines in detecting silent data corruptions
Tài liệu tham khảo
Vapnik, 1995
SDC Detection Framework and Library, Available at: https://collab.cels.anl.gov/display/esr/aid.
S. Di, F. Cappello, Adaptive impact-driven detection of silent data corruption for HPC applications, IEEE Transactions on Parallel and Distributed Systems doi:10.1109/TPDS.2016.2517639.
Bautista-Gomez, 2015, Detecting and correcting data corruption in stencil applications through multivariate interpolation, 2015 IEEE International Conference on Cluster Computing (CLUSTER), 595, 10.1109/CLUSTER.2015.108
Subasi, 2016, Spatial support vector regression to detect silent errors in the exascale era, 413
Cao, 2003, Support vector machine with adaptive parameters in financial time series forecasting, IEEE Trans. Neural Netw., 14, 1506, 10.1109/TNN.2003.820556
Farooq, 2007, Chaotic time series prediction using knowledge based Green's kernel and least-squares support vector machines, 2007 IEEE International Conference on Systems, Man and Cybernetics, 373, 10.1109/ICSMC.2007.4414023
Raicharoen, 2003, Application of critical support vector machine to time series prediction, Proceedings of the 2003 International Symposium on Circuits and Systems, vol. 5, V-741
Fan, 2006, Dynamic least squares support vector machine, The Sixth World Congress on Intelligent Control and Automation, vol. 1, 4886
Smola, 2004, A tutorial on support vector regression, Stat. Comput., 14, 199, 10.1023/B:STCO.0000035301.49549.88
Cortes, 1995, Support-vector networks, Mach. Learn., 20, 273, 10.1007/BF00994018
Kuhn, 1951, Nonlinear programming, Proceedings of the Second Berkeley Symposium on Mathematical Statistics and Probability, 481
Ovari, 2000
Chang, 2011, LIBSVM: a library for support vector machines, ACM Trans. Intell. Syst. Technol., 2, 27:1, 10.1145/1961189.1961199
Bautista-Gomez, 2011, FTI: high performance fault tolerance interface for hybrid systems, 32:1
Colella, 1984, The piecewise parabolic method (PPM) for gas-dynamical simulations, J. Comput. Phys., 54, 174, 10.1016/0021-9991(84)90143-8
Sod, 1978, A survey of several finite difference methods for systems of nonlinear hyperbolic conservation laws, J. Comput. Phys., 27, 1, 10.1016/0021-9991(78)90023-2
Martí, 2003, vol. 6
Schulz-Rinne, 1993, Numerical solution of the Riemann problem for two-dimensional gas dynamics, SIAM J. Sci. Comput., 14, 1394, 10.1137/0914082
Brio, 1988, An upwind differencing scheme for the equations of ideal magnetohydrodynamics, J. Comput. Phys., 75, 400, 10.1016/0021-9991(88)90120-9
Orszag, 1979, Small-scale structure of two-dimensional magnetohydrodynamic turbulence, J. Fluid Mech., 90, 129, 10.1017/S002211207900210X
Timmes, 2000, On the cellular structure of carbon detonations, Astrophys. J., 543, 938, 10.1086/317135
Fusion Cluster, Available at: http://www.lcrc.anl.gov/.
Fryxell, 2000, FLASH: an adaptive mesh hydrodynamics code for modeling astrophysical thermonuclear flashes, Astrophys. J. Suppl., 131, 273, 10.1086/317361
Schölkopf, 1997
Berrocal, 2015, Lightweight silent data corruption detection based on runtime data analysis for HPC applications, 275
Gomez, 2015, Detecting and correcting data corruption in stencil applications through multivariate interpolation, 2015 IEEE International Conference on Cluster Computing, 595, 10.1109/CLUSTER.2015.108
Di, 2015, An efficient silent data corruption detection method with error-feedback control and even sampling for HPC applications, 271
Sharma, 2015, Detecting soft errors in stencil based computations, The 11th Workshop on Silicon Errors in Logic – System Effects
Subasi, 2016, Spatial support vector regression to detect silent errors in the exascale era, 413
Thomas, 2016, Sirius: neural network based probabilistic assertions for detecting silent data corruption in parallel programs, 35th Symposium on Reliable Distributed Systems (SRDS)
Subasi, 2016, CRC-based memory reliability for task-parallel HPC applications, 1101
Fiala, 2012, Detection and correction of silent data corruption for large-scale high-performance computing, 78:1
Subasi, 2015, Programmer-directed partial redundancy for resilient HPC, 47:1
Turmon, 2003, Tests and tolerances for high-performance software-implemented fault detection, IEEE Trans. Comput., 52, 579, 10.1109/TC.2003.1197125
Ciocca, 2004, Application-level fault tolerance in the orbital thermal imaging spectrometer, 43
Sloan, 2012, Algorithmic approaches to low overhead fault detection for sparse linear algebra, 1
Bautista-Gomez, 2011, FTI: high performance fault tolerance interface for hybrid systems, Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, SC, 32:1
Subasi, 2015, Nanocheckpoints: a task-based asynchronous dataflow framework for efficient and scalable checkpoint/restart, 23rd Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), 99
Subasi, 2015, Marriage between coordinated and uncoordinated checkpointing for the exascale era, 470
Martsinkevich, 2015, Fault-tolerant protocol for hybrid task-parallel message-passing applications, IEEE International Conference on Cluster Computing, CLUSTER, 563
Subasi, 2016, Unified fault-tolerance framework for hybrid task-parallel message-passing applications, Int. J. High Perform. Comput. Appl., 0