P. Brucker and S. Knust, Complexity results for scheduling problems

J. K. Lenstra, D. B. Shmoys, and E. Tardos, Approximation algorithms for scheduling unrelated parallel machines, Mathematical Programming, vol.23, issue.1-3, pp.259-271, 1990.
DOI : 10.1007/BF01585745

R. Bleuse, S. Kedad-sidhoum, F. Monna, G. Mounié, and D. Trystram, Scheduling independent tasks on multi-cores with GPU accelerators, Concurrency and Computation: Practice and Experience, vol.20, issue.4, pp.1625-1638, 2015.
DOI : 10.1002/cpe.3359

URL : https://hal.archives-ouvertes.fr/hal-01081625

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, Special Issue: Euro-Par, pp.187-198, 2009.

J. Planas, R. M. Badia, E. Ayguadé, and J. Labarta, Hierarchical Task-Based Programming With StarSs, International Journal of High Performance Computing Applications, vol.23, issue.3, pp.284-299, 2009.
DOI : 10.1177/1094342009106195

E. Chan, F. G. Van-zee, P. Bientinesi, E. S. Quintana-orti, G. Quintana-orti et al., SuperMatrix, Proceedings of the 13th ACM SIGPLAN Symposium on Principles and practice of parallel programming , PPoPP '08, p.123132, 2008.
DOI : 10.1145/1345206.1345227

A. Yarkhan, J. Kurzak, and J. Dongarra, Guide: QUeueing And Runtime for Kernels, 2011.

G. Bosilca, A. Bouteiller, A. Danalis, M. Faverge, T. Hérault 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

H. Topcuouglu, S. Hariri, and M. 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

E. Agullo, O. Beaumont, L. Eyraud-dubois, and S. Kumar, Are Static Schedules so Bad? A Case Study on Cholesky Factorization, 2016 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2016.
DOI : 10.1109/IPDPS.2016.90

URL : https://hal.archives-ouvertes.fr/hal-01223573

E. Agullo, B. Bramas, O. Coulaud, E. Darve, M. Messner et al., Task-based FMM for heterogeneous architectures Available: https, 2014.

E. Agullo, J. Demmel, J. Dongarra, B. Hadri, J. Kurzak et al., Numerical linear algebra on emerging architectures: The PLASMA and MAGMA projects, Dense Linear Algebra on Distributed Heterogeneous Hardware with a Symbolic DAG Approach Scalable Computing and Communications: Theory and Practice, pp.12-037, 2009.
DOI : 10.1088/1742-6596/180/1/012037

G. Quintana-ortí, F. D. Igual, E. S. Quintana-ortí, and R. A. Van-de-geijn, Solving dense linear systems on platforms with multiple hardware accelerators, PPOPP'09, pp.121-130, 2009.

W. Wu, A. Bouteiller, G. Bosilca, M. Faverge, and J. Dongarra, Hierarchical DAG Scheduling for Hybrid Distributed Systems, 2015 IEEE International Parallel and Distributed Processing Symposium, 2015.
DOI : 10.1109/IPDPS.2015.56

URL : https://hal.archives-ouvertes.fr/hal-01078359

. Wacrenier, Exploiting two-level parallelism by aggregating computing resources in task-based applications over accelerator-based machines Available: https, 2015.

R. L. Graham, Bounds on Multiprocessing Timing Anomalies, SIAM Journal on Applied Mathematics, vol.17, issue.2, pp.416-429, 1969.
DOI : 10.1137/0117039

H. Bouwmeester and J. Langou, A Critical Path Approach to Analyzing Parallelism of Algorithmic Variants. Application to Cholesky Inversion, 1010.

H. M. Bouwmeester, Tiled algorithms for matrix computations on multicore architectures

R. D. Blumofe and C. E. Leiserson, Scheduling multithreaded computations by work stealing, Journal of the ACM, vol.46, issue.5, pp.720-748, 1999.
DOI : 10.1145/324133.324234

P. Dutot, G. Mounié, and D. Trystram, Scheduling Parallel Tasks: Approximation Algorithms, " in Handbook of Scheduling: Algorithms, Models, and Performance Analysis, ser. chapter 26 Available: https, pp.26-27, 2004.

R. Bleuse, S. Hunold, S. Kedad-sidhoum, F. Monna, G. Mounié et al., Scheduling Independent Moldable Tasks on Multi-Cores with GPUs Inria Grenoble Rhône-Alpes Available: https, 2016.

E. Agullo, B. Bramas, O. Coulaud, E. Darve, M. Messner et al., Task-Based FMM for Multicore Architectures, SIAM Journal on Scientific Computing, vol.36, issue.1, 2014.
DOI : 10.1137/130915662

URL : https://hal.archives-ouvertes.fr/hal-00807368

E. Agullo, O. Beaumont, L. Eyraud-dubois, J. Herrmann, S. Kumar et al., Bridging the Gap between Performance and Bounds of Cholesky Factorization on Heterogeneous Platforms Available: https, Heterogeneity in Computing Workshop 2015, 2015.

]. G. Quintana-ortí, E. S. Quintana-ortí, R. A. Van-de-geijn, F. G. Zee, and E. Chan, Available: https://project.inria.fr/chameleon [26 Programming matrix algorithms-by-blocks for threadlevel parallelism, ACM Trans. Math. Softw, vol.36, issue.3, 2009.

F. Broquedis, J. Clet-ortega, S. Moreaud, N. Furmento, B. Goglin et al., hwloc: a Generic Framework for Managing Hardware Affinities in HPC Applications Available: https, PDP 2010 -The 18th Euromicro International Conference on Parallel, Distributed and Network-Based Computing, 2010.