N. Ali, P. Carns, K. Iskra, D. Kimpe, S. Lang et al., Scalable I/O Forwarding Framework for High-Performance Computing Systems. In: Proceedings, IEEE International Conference on Cluster Computing and Workshops, pp.1-10, 2009.
DOI : 10.1109/clustr.2009.5289188

G. Almási, R. Bellofatto, J. Brunheroto, C. Ca¸scavalca¸scaval, J. G. Castanos et al., An overview of the Blue Gene/L system software organization, Proceedings, pp.543-555, 2003.

B. Behzad, H. V. Luu, J. Huchette, S. Byna, R. Aydt et al., Taming parallel I/O complexity with auto-tuning, SC '13: Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, SC '13, pp.1-12, 2013.
DOI : 10.1145/2503210.2503278

D. A. Berry and B. Fristedt, Bandit problems: sequential allocation of experiments (monographs on statistics and applied probability), London: Chapman and Hall, vol.5, pp.71-87, 1985.

J. L. Bez, F. Z. Boito, L. M. Schnorr, P. O. Navaux, and J. F. Méhaut, TWINS: Server Access Coordination in the I/O Forwarding Layer, 2017 25th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP), pp.116-123, 2017.
DOI : 10.1109/pdp.2017.61

URL : https://hal.archives-ouvertes.fr/hal-01515047

F. Z. Boito, R. V. Kassick, P. O. Navaux, and Y. Denneulin, Automatic I/O scheduling algorithm selection for parallel file systems, Concurrency and Computation: Practice and Experience, 2015.
DOI : 10.1002/cpe.3606

URL : https://hal.archives-ouvertes.fr/hal-01247942

M. Dorier, S. Ibrahim, G. Antoniu, and R. Ross, Omnisc'IO: a grammar-based approach to spatial and temporal I/O patterns prediction, Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, pp.623-634, 2014.
DOI : 10.1109/sc.2014.56

URL : https://hal.archives-ouvertes.fr/hal-01025670

F. Isaila, J. Carretero, and R. Ross, CLARISSE: A middleware for data-staging coordination and control on large-scale HPC platforms, 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing), pp.346-355, 2016.
DOI : 10.1109/ccgrid.2016.24

F. Isaila, J. Garcia-blas, J. Carretero, R. Latham, and R. Ross, Design and evaluation of multiple-level data staging for blue gene systems. Parallel and Distributed Systems, IEEE Transactions on, vol.22, issue.6, pp.946-959, 2011.
DOI : 10.1109/tpds.2010.127

Y. Li, O. Bel, K. Chang, E. L. Miller, and D. D. Long, Capes: Unsupervised storage performance tuning using neural network-based deep reinforcement learning, Supercomputing '17, 2017.

Y. Liu, R. Gunasekaran, X. Ma, and S. S. Vazhkudai, Automatic Identification of Application I/O Signatures from Noisy Server-Side Traces, FAST'14 Proceedings of USENIX conference on File and Storage Technologies, pp.213-228, 2014.

Y. Liu, R. Gunasekaran, X. Ma, and S. S. Vazhkudai, Server-side log data analytics for I/O workload characterization and coordination on large shared storage systems, High Performance Computing, Networking, Storage and Analysis, SC16: International Conference for, pp.819-829, 2016.
DOI : 10.1109/sc.2016.69

R. Mclay, D. James, S. Liu, J. Cazes, and W. Barth, A user-friendly approach for tuning parallel file operations, Proceedings..., SC '14, pp.229-236, 2014.

R. Nou, J. Giralt, and T. Cortes, Automatic I/O scheduler selection through online workload analysis, 9th International Conference on Autonomic and Trusted Computing, pp.431-438, 2012.
DOI : 10.1109/uic-atc.2012.12

URL : https://upcommons.upc.edu/bitstream/2117/19470/1/ATC2012-IOAnalyzer.pdf

K. Ohta, D. Kimpe, J. Cope, K. Iskra, R. Ross et al., Optimization Techniques at the I/O Forwarding Layer, International Conference on Cluster Computing, pp.312-321, 2010.
DOI : 10.1109/cluster.2010.36

R. S. Sutton and A. G. Barto, Reinforcement Learning: An Introduction, 2017.

H. Tang, X. Zou, J. Jenkins, I. I. Boyuka, D. A. Ranshous et al., Improving Read Performance with Online Access Pattern Analysis and Prefetching, Euro-Par, pp.246-257, 2014.
DOI : 10.1007/978-3-319-09873-9_21

V. Vishwanath, M. Hereld, K. Iskra, D. Kimpe, V. Morozov et al., Accelerating I/O forwarding in IBM Blue Gene/P systems, Proceedings..., SC'10, pp.1-10, 2010.

R. L. Walko and R. Avissar, The Ocean-Land-Atmosphere Model (OLAM). Part I: Shallow-Water Tests, Monthly Weather Review, vol.136, issue.11, pp.4033-4044, 2008.