, The trinity project

, I/o at argonne national laboratory

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

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.

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, pp.2772-2791, 2014.
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F. Isaila, J. Carretero, and R. Ross, Clarisse: A middleware for datastaging coordination and control on large-scale hpc platforms, Cluster, Cloud and Grid Computing (CCGrid), pp.346-355, 2016.

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.

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

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.

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

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

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.

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, Cluster Computing, International Conference on, pp.204-215, 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.

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, p.4, 2012.

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

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. Society for Computer Simulation International, p.4, 2017.

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.

S. Herbein, D. H. Ahn, D. Lipari, T. R. Scogland, M. Stearman et al., Scalable i/oaware 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.

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

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, p.2, 2017.

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

, Trinity / NERSC-8 Use Case Scenarios, 2013.

. Available,

G. Aupy, O. Beaumont, and L. Eyraud-dubois, Sizing and Partitioning Strategies for Burst-Buffers to Reduce IO Contention, Inria; Univ. Bordeaux, 2018.
URL : https://hal.archives-ouvertes.fr/hal-02141616

S. Lanl, . Nersc-;-lanl, . Nersc, T. Snl, and . Rep, Apex workflows, 2016.

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