E. Agullo, P. R. Amestoy, A. Buttari, A. Guermouche, J. L. Excellent et al., Robust Memory-Aware Mappings for Parallel Multifrontal Factorizations, SIAM Journal on Scientific Computing, vol.38, issue.3, p.2016
DOI : 10.1137/130938505

URL : https://hal.archives-ouvertes.fr/hal-01334113

C. Augonnet, S. Thibault, R. Namyst, and P. Wacrenier, StarPU: a unified platform for task scheduling on heterogeneous multicore architectures . Concurrency and Computation: Practice and Experience, pp.187-198, 2011.
DOI : 10.1007/978-3-642-03869-3_80

URL : https://hal.archives-ouvertes.fr/inria-00384363

G. Aupy, C. Brasseur, and L. Marchal, Dynamic Memory-Aware Task-Tree Scheduling, 2017 IEEE International Parallel and Distributed Processing Symposium (IPDPS), pp.758-767, 2017.
DOI : 10.1109/IPDPS.2017.58

URL : https://hal.archives-ouvertes.fr/hal-01390107

S. Bharathi and A. Chervenak, Scheduling data-intensive workflows on storage constrained resources, Proceedings of the 4th Workshop on Workflows in Support of Large-Scale Science, WORKS '09, 2009.
DOI : 10.1145/1645164.1645167

URL : http://www.isi.edu/~annc/papers/works2009.pdf

G. Bosilca, A. Bouteiller, A. Danalis, M. Faverge, T. Herault et al., PaRSEC: Exploiting Heterogeneity to Enhance Scalability, Computing in Science & Engineering, vol.15, issue.6, pp.36-45, 2013.
DOI : 10.1109/MCSE.2013.98

T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein, Introduction to Algorithms, 2009.

R. F. Da-silva, W. Chen, G. Juve, K. Vahi, and E. Deelman, Community Resources for Enabling Research in Distributed Scientific Workflows, 2014 IEEE 10th International Conference on e-Science, pp.177-184, 2014.
DOI : 10.1109/eScience.2014.44

F. Desprez and F. Suter, A Bi-criteria Algorithm for Scheduling Parallel Task Graphs on Clusters, 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing, pp.243-252, 2010.
DOI : 10.1109/CCGRID.2010.43

URL : https://hal.archives-ouvertes.fr/hal-00533904

M. Drozdowski, Scheduling parallel tasks ? algorithms and complexity, Handbook of Scheduling. Chapman and Hall/CRC, 2004.

M. Garey, D. Johnson, and L. Stockmeyer, Some simplified NP-complete graph problems, Theoretical Computer Science, vol.1, issue.3, pp.237-267, 1976.
DOI : 10.1016/0304-3975(76)90059-1

URL : https://doi.org/10.1016/0304-3975(76)90059-1

M. R. Garey and D. S. Johnson, Computers and Intractability, a Guide to the Theory of NP-Completeness, 1979.

T. Gautier, X. Besseron, and L. Pigeon, KAAPI, Proceedings of the 2007 international workshop on Parallel symbolic computation, PASCO '07, pp.15-23, 2007.
DOI : 10.1145/1278177.1278182

URL : https://hal.archives-ouvertes.fr/hal-00727795

A. V. Goldberg and R. E. Tarjan, A new approach to the maximum flow problem, Proceedings of the Eighteenth Annual ACM Symposium on Theory of Computing, STOC '86, pp.136-146, 1986.

S. Hunold, One step toward bridging the gap between theory and practice in moldable task scheduling with precedence constraints. Concurrency and Computation: Practice and Experience, pp.1010-1026, 2015.

M. Jacquelin, L. Marchal, Y. Robert, and B. Uçar, On Optimal Tree Traversals for Sparse Matrix Factorization, 2011 IEEE International Parallel & Distributed Processing Symposium, pp.556-567, 2011.
DOI : 10.1109/IPDPS.2011.60

URL : https://hal.archives-ouvertes.fr/hal-00945078

R. M. Karp, Reducibility among combinatorial problems, Complexity of computer computations, pp.85-103, 1972.
DOI : 10.1007/978-3-540-68279-0_8

M. Lampis, G. Kaouri, and V. Mitsou, On the algorithmic effectiveness of digraph decompositions and complexity measures, Discrete Optimization, vol.8, issue.1, pp.129-138, 2011.
DOI : 10.1016/j.disopt.2010.03.010

E. L. Lawler, Combinatorial optimization: networks and matroids, Courier Corporation, 2001.

J. W. Liu, An Application of Generalized Tree Pebbling to Sparse Matrix Factorization, SIAM Journal on Algebraic Discrete Methods, vol.8, issue.3, pp.375-395, 1987.
DOI : 10.1137/0608031

J. Planas, R. M. Badia, E. Ayguadé, and J. Labarta, Hierarchical Task-Based Programming With StarSs, The International Journal of High Performance Computing Applications, vol.83, issue.12, pp.284-299, 2009.
DOI : 10.1109/5.476078

A. Ramakrishnan, G. Singh, H. Zhao, E. Deelman, R. Sakellariou et al., Scheduling dataintensiveworkflows onto storage-constrained distributed resources, Proceedings of the IEEE Symposium on Cluster Computing and the Grid (CC- Grid'07), pp.401-409, 2007.
DOI : 10.1109/ccgrid.2007.101

URL : http://www.isi.edu/~deelman/ccgrid07.pdf

D. Sbîrlea, Z. Budimli´cbudimli´c, and V. Sarkar, Bounded memory scheduling of dynamic task graphs, Proceedings of the 23rd international conference on Parallel architectures and compilation, PACT '14, pp.343-356, 2014.
DOI : 10.1145/2628071.2628090

M. Sergent, D. Goudin, S. Thibault, and O. Aumage, Controlling the Memory Subscription of Distributed Applications with a Task-Based Runtime System, 2016 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), pp.318-327, 2016.
DOI : 10.1109/IPDPSW.2016.105

URL : https://hal.archives-ouvertes.fr/hal-01284004

R. Sethi, Complete Register Allocation Problems, SIAM Journal on Computing, vol.4, issue.3, pp.226-248, 1975.
DOI : 10.1137/0204020

URL : http://graal.ens-lyon.fr/%7Elmarchal/scheduling/sethi_complete_register_allocation.pdf

R. Sethi and J. Ullman, The Generation of Optimal Code for Arithmetic Expressions, Journal of the ACM, vol.17, issue.4, pp.715-728, 1970.
DOI : 10.1145/321607.321620

F. Suter, Daggen: A synthetic task graph generator

H. Topcuoglu, S. Hariri, and M. Y. Wu, Performance-effective and low-complexity task scheduling for heterogeneous computing, IEEE Transactions on Parallel and Distributed Systems, vol.13, issue.3, pp.260-274, 2002.
DOI : 10.1109/71.993206

URL : http://meseec.ce.rit.edu/eecc722-fall2002/papers/hc/5/l0260.pdf