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

J. K. Lenstra and D. B. Shmoys, Approximation algorithms for scheduling unrelated parallel machines, 1990.
DOI : 10.1007/bf01585745
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.115.708

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, vol.23, issue.4, pp.187-198, 2011.
DOI : 10.1002/cpe.1631
URL : https://hal.archives-ouvertes.fr/inria-00384363

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
URL : http://hdl.handle.net/2117/28379

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, pp.123-132, 2008.
DOI : 10.1145/1345206.1345227

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

E. Hermann, B. Raffin, F. Faure, T. Gautier, and J. Allard, Multi-GPU and Multi-CPU Parallelization for Interactive Physics Simulations, Euro-Par, pp.2010-235
DOI : 10.1007/978-3-642-15291-7_23
URL : https://hal.archives-ouvertes.fr/inria-00502448

G. Bosilca, A. Bouteiller, A. Danalis, M. Faverge, T. Hérault et al., PaRSEC: A programming paradigm exploiting heterogeneity for enhancing scalability, Computing in Science and Engineering, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00930217

V. Bonifaci and A. Wiese, Scheduling unrelated machines of few different types

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), pp.1021-1030, 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, Concurrency and Computation: Practice and Experience, 2016.
DOI : 10.1002/cpe.3723
URL : https://hal.archives-ouvertes.fr/hal-01359458

E. V. Shchepin and N. Vakhania, An optimal rounding gives a better approximation for scheduling unrelated machines, Operations Research Letters, vol.33, issue.2, 2005.
DOI : 10.1016/j.orl.2004.05.004

C. Imreh, Scheduling Problems on Two Sets of Identical Machines, Computing, vol.70, issue.4, pp.277-294, 2003.
DOI : 10.1007/s00607-003-0011-9

R. Bleuse, T. Gautier, J. V. Lima, G. Mounié, and D. Trystram, Scheduling Data Flow Program in XKaapi: A New Affinity Based Algorithm for Heterogeneous Architectures, pp.560-571, 2014.
DOI : 10.1007/978-3-319-09873-9_47
URL : https://hal.archives-ouvertes.fr/hal-01081629