I. ,

, The trinity project

, Use Case Scenarios, 2013.

G. Aupy, O. Beaumont, and L. Eyraud-dubois, What size should your buffers to disks be?, 2018 IEEE International Parallel and Distributed Processing Symposium (IPDPS), pp.660-669, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01623846

G. Aupy, A. Gainaru, and V. L. Fèvre, Periodic i/o scheduling for super-computers, International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01654645

G. Aupy, Y. Robert, F. Vivien, and D. Zaidouni, Checkpointing algorithms and fault prediction, Journal of Parallel and Distributed Computing, vol.74, issue.2, pp.2048-2064, 2014.
URL : https://hal.archives-ouvertes.fr/hal-00788313

L. Bautista-gomez, S. Tsuboi, D. Komatitsch, F. Cappello, N. Maruyama et al., Fti: high performance fault tolerance interface for hybrid systems, Proceedings of 2011 international conference for high performance computing, networking, storage and analysis, p.32, 2011.
URL : https://hal.archives-ouvertes.fr/hal-01298430

G. Bosilca, A. Bouteiller, E. Brunet, F. Cappello, J. Dongarra et al., Unified model for assessing checkpointing protocols at extreme-scale, Concurrency and Computation: Practice and Experience, vol.26, issue.17, pp.2772-2791, 2014.
URL : https://hal.archives-ouvertes.fr/hal-00696154

L. Cao, B. W. Settlemyer, and J. Bent, To share or not to share: comparing burst buffer architectures, Proceedings of the 25th High Performance Computing Symposium, 2017.

F. Cappello, A. Geist, W. Gropp, S. Kale, B. Kramer et al., Toward exascale resilience: 2014 update, Supercomputing frontiers and innovations, vol.1, issue.1, pp.5-28, 2014.

P. Carns, K. Harms, W. Allcock, C. Bacon, S. Lang et al., Storage access characteristics of computational science applications, MSST, 2011.

P. Carns, K. Harms, W. Allcock, C. Bacon, S. Lang et al., Understanding and improving computational science storage access through continuous characterization, ACM Transactions on Storage (TOS), vol.7, issue.3, 2011.

R. F. Silva, S. Callaghan, and E. Deelman, On the use of burst buffers for accelerating data-intensive scientific workflows, Proceedings of the 12th Workshop on Workflows in Support of Large-Scale Science, 2017.

C. S. Daley, D. Ghoshal, G. K. Lockwood, S. Dosanjh, L. Ramakrishnan et al., Performance characterization of scientific workflows for the optimal use of burst buffers. Future Generation Computer Systems, 2017.

C. S. Daley, D. Ghoshal, G. K. Lockwood, S. S. Dosanjh, L. Ramakrishnan et al., Performance characterization of scientific workflows for the optimal use of burst buffers, WORKS@ SC, 2016.

. Ddn-storage, BURST BUFFER & BEYOND, I/O & Application Acceleration Technology, p.20, 2014.

A. Gainaru, G. Aupy, A. Benoit, F. Cappello, Y. Robert et al., Scheduling the i/o of hpc applications under congestion, Parallel and Distributed Processing Symposium (IPDPS), pp.1013-1022, 2015.
URL : https://hal.archives-ouvertes.fr/hal-00983789

J. Han, D. Koo, G. K. Lockwood, J. Lee, H. Eom et al., Accelerating a burst buffer via user-level i/o isolation, 2017 IEEE International Conference on, pp.245-255, 2017.

D. Henseler, B. Landsteiner, D. Petesch, C. Wright, and N. J. Wright, Architecture and design of cray datawarp, 2016.

S. Herbein, D. H. Ahn, D. Lipari, T. R. Scogland, M. Stearman et al., Scalable i/o-aware job scheduling for burst buffer enabled hpc clusters, Proceedings of the 25th ACM International Symposium on High-Performance Parallel and Distributed Computing, pp.69-80, 2016.

F. Isaila, J. Carretero, and R. Ross, Clarisse: A middleware for data-staging coordination and control on large-scale hpc platforms, Cluster, Cloud and Grid Computing (CCGrid), pp.346-355, 2016.

D. Kimpe, K. Mohror, A. Moody, B. Van-essen, M. Gokhale et al., Integrated in-system storage architecture for high performance computing, Proceedings of the 2nd International Workshop on Runtime and Operating Systems for Supercomputers, 2012.

S. Lanl and N. , Apex workflows, 2016.

N. Liu, J. Cope, P. Carns, C. Carothers, R. Ross et al., On the role of burst buffers in leadership-class storage systems, Mass Storage Systems and Technologies (MSST), 2012 IEEE 28th Symposium on, pp.1-11, 2012.

M. Mubarak, P. Carns, J. Jenkins, J. K. Li, N. Jain et al., Quantifying i/o and communication traffic interference on dragonfly networks equipped with burst buffers, 2017 IEEE International Conference on, pp.204-215, 2017.

D. A. Reed and J. Dongarra, Exascale computing and big data, Communications of the ACM, vol.58, issue.7, pp.56-68, 2015.

W. Schenck, S. E. Sayed, M. Foszczynski, W. Homberg, and D. Pleiter, Evaluation and performance modeling of a burst buffer solution, ACM SIGOPS Operating Systems Review, vol.50, issue.1, pp.12-26, 2017.

K. Tang, P. Huang, X. He, T. Lu, S. S. Vazhkudai et al., Toward managing hpc burst buffers effectively: Draining strategy to regulate bursty i/o behavior, MASCOTS, pp.87-98, 2017.

A. B. Yoo, M. A. Jette, and M. Grondona, Slurm: Simple linux utility for resource management, Workshop on Job Scheduling Strategies for Parallel Processing, pp.44-60, 2003.