Machine Learning for Reliability Analysis of Large Scale Systems

Author:

Smirni Evgenia

Publisher

Springer International Publishing

Reference17 articles.

1. Top500 Supercomputer Sites, November 2018. https://www.top500.org/lists/2018/11/

2. Alter, J., Xue, J., Dimnaku, A., Smirni, E.: SSD failures in the field: symptoms, causes, and prediction models. In: Taufer, M., Balaji, P., Peña, A.J. (eds.) Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2019, Denver, Colorado, USA, 17–19 November 2019, pp. 75:1–75:14. ACM (2019). https://doi.org/10.1145/3295500.3356172

3. Backblaze: Hard drive data and stats. https://www.backblaze.com/b2/hard-drive-test-data.html. Accessed 28 Apr 2020

4. Birke, R., Björkqvist, M., Chen, L.Y., Smirni, E., Engbersen, T.: (Big)data in a virtualized world: volume, velocity, and variety in cloud datacenters. In: Schroeder, B., Thereska, E. (eds.) Proceedings of the 12th USENIX conference on File and Storage Technologies, FAST 2014, Santa Clara, CA, USA, 17–20 February 2014, pp. 177–189. USENIX (2014). https://www.usenix.org/conference/fast14/technical-sessions/presentation/birke

5. Nie, B., Jog, A., Smirni, E.: Characterizing accuracy-aware resilience of GPGPU applications. In: 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing, CCGRID 2020, Melbourne, Australia, 11–14 May 2020, pp. 111–120. IEEE (2020). https://doi.org/10.1109/CCGrid49817.2020.00-82

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