, The Trinity project

G. Aupy, O. Beaumont, and L. Eyraud-dubois, What size should your Buffers to Disk be, Proceedings of the 32nd International Parallel Processing Symposium, (IPDPS'18), 2018.

G. Aupy, O. Beaumont, and L. Eyraud-dubois, Sizing and Partitioning Strategies for BurstBuffers to Reduce IO Contention, Proceedings of the 33rd International Parallel Processing Symposium, (IPDPS'19), 2019.
URL : https://hal.archives-ouvertes.fr/hal-02141616

G. Aupy, A. Gainaru, and V. L. Fèvre, Periodic I/O Scheduling for Supercomputers, PMBS 2017, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01654645

. Behzad, Taming parallel I/O complexity with auto-tuning, SC13, 2013.

R. Biswas, C. Aftosmis, B. Kiris, and . Shen, Petascale computing: Impact on future NASA missions. Petascale Computing: Architectures and Algorithms, pp.29-46, 2007.

H. George, J. Bryan, and . Michael-fritsch, A benchmark simulation for moist nonhydrostatic numerical models, Monthly Weather Review, vol.130, p.12, 2002.

L. Greg and . Bryan, Enzo: An Adaptive Mesh Refinement Code for Astrophysics, 2013.

S. Byna, Y. Chen, X. Sun, R. Thakur, and W. Gropp, Parallel I/O prefetching using MPI file caching and I/O signatures, SC '08: Proceedings of the 2008 ACM/IEEE Conference on Supercomputing. 1-12, 2008.

P. Carns, R. Latham, R. Ross, . Iskra, K. Lang et al., 24/7 characterization of petascale I/O workloads. Cluster Computing and Workshops, 2009. CLUSTER'09, IEEE International Conference on, pp.1-10, 2009.

J. Carter, J. Borrill, and L. Oliker, Performance characteristics of a cosmology package on leading HPC architectures, HiPC, pp.176-188, 2005.

P. Colella, Chombo infrastructure for adaptive mesh refinement, 2005.

J. T. Daly, A higher order estimate of the optimum checkpoint interval for restart dumps, FGCS, vol.22, p.3, 2004.

M. Dorier, G. Antoniu, and R. Ross, CALCioM: Mitigating I/O Interference in HPC Systems through Cross-Application Coordination, IPDPS'14, 2014.
URL : https://hal.archives-ouvertes.fr/hal-00916091

M. Dorier, S. Ibrahim, G. Antoniu, and R. Ross, Omnisc'IO: a grammar-based approach to spatial and temporal I/O patterns prediction, SC, pp.623-634, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01025670

S. Ethier, M. Adams, J. Carter, and L. Oliker, Petascale parallelization of the gyrokinetic toroidal code, 2012.

. Valentin-le-fèvre, , 2017.

A. Gainaru, G. Aupy, A. Benoit, F. Cappello, Y. Robert et al., Scheduling the I/O of HPC applications under congestion, IPDPS. IEEE, pp.1013-1022, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01251938

G. Robert and . Gallager, Information theory and reliable communication, vol.2, 1968.

S. Habib, The universe at extreme scale: multi-petaflop sky simulation on the BG/Q. In SC12, IEEE Computer Society, p.4, 2012.

C. Hanen and A. Munier, Cyclic scheduling on parallel processors: an overview, 1993.

B. Harrod, Big data and scientific discovery, 2014.

J. He, J. Bent, A. Torres, G. Grider, and G. Gibson, Carlos Maltzahn, and Xian-He Sun. 2013. I/O Acceleration with Pattern Detection, Proceedings of the 22Nd International Symposium on High-performance Parallel and Distributed Computing (HPDC '13), pp.25-36

T. Herault, Y. Robert, A. Bouteiller, D. Arnold, K. Ferreira et al., Optimal Cooperative Checkpointing for Shared High-Performance Computing Platforms, APDCM 2018, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01621295

W. Hu, G. Liu, Q. Li, Y. Jiang, and G. Cai, Storage wall for exascale supercomputing, Journal of Zhejiang University-SCIENCE, vol.2016, pp.10-25, 2016.

F. Isaila and J. Carretero, Making the case for data staging coordination and control for parallel applications, Workshop on Exascale MPI at Supercomputing Conference, 2015.

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. IEEE, pp.346-355, 2016.

A. Kougkas, M. Dorier, R. Latham, R. Ross, and X. Sun, Leveraging Burst Buffer Coordination to Prevent I/O Interference, IEEE International Conference on eScience, 2016.

S. Kumar, Characterization and modeling of PIDX parallel I/O for performance optimization, 2013.

A. Lazzarini, Advanced LIGO Data & Computing, 2003.

N. Liu, On the Role of Burst Buffers in Leadership-Class Storage Systems, 2012.

K. Glenn, S. Lockwood, T. Snyder, S. Wang, P. Byna et al., A year in the life of a parallel file system, Proceedings of the International Conference for High Performance Computing, Networking, Storage, and Analysis, p.74, 2018.

J. Lofstead, Managing variability in the IO performance of petascale storage systems, 2010.

J. Lofstead and R. Ross, Insights for exascale IO APIs from building a petascale IO API, SC13. ACM, p.87, 2013.

R. D. Nair and H. M. Tufo, Petascale atmospheric general circulation models, Journal of Physics: Conference Series, vol.78, p.12078, 2007.

. Sankaran, Direct numerical simulations of turbulent lean premixed combustion, In Journal of Physics: conference series, vol.46, p.38, 2006.

R. Seetharami, P. J. Seelam, and . Teller, Virtual I/O Scheduler: A Scheduler of Schedulers for Performance Virtualization, Proceedings VEE. ACM, pp.105-115, 2007.

H. Shan and J. Shalf, Using IOR to Analyze the I/O Performance for HPC Platforms, 2007.

D. Skinner and W. Kramer, Understanding the Causes of Performance Variability in HPC Workloads, IEEE Workload Characterization Symposium, pp.137-149, 2005.

K. Tang, P. Huang, X. He, T. Lu, S. Sudharshan et al., Toward Managing HPC Burst Buffers Effectively: Draining Strategy to Regulate Bursty I/O Behavior, MASCOTS. IEEE, pp.87-98, 2017.

F. Tessier, P. Malakar, V. Vishwanath, E. Jeannot, and F. Isaila, Topology-aware data aggregation for intensive I/O on large-scale supercomputers, First Workshop on Optimization of Communication in HPC, pp.73-81, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01394741

X. Zhang, K. Davis, and S. Jiang, Opportunistic data-driven execution of parallel programs for efficient I/O services, IPDPS'12. IEEE, pp.330-341, 2012.

Z. Zhou, X. Yang, D. Zhao, P. Rich, W. Tang et al., 2015. I/O-Aware Batch Scheduling for Petascale Computing Systems, Cluster15, pp.254-263
URL : https://hal.archives-ouvertes.fr/hal-01158942