N. Halbwachs, P. Caspi, P. Raymond, and D. Pilaud, The synchronous data flow programming language LUSTRE, Proceedings of the IEEE, pp.1305-1320, 1991.
DOI : 10.1109/5.97300

URL : http://www-verimag.imag.fr/~raymond/publis/lustre.ieee.ps.gz

W. Thies, Language and compiler support for stream programs, 2009.

G. Kahn, The semantics of a simple language for parallel programming, Information processing, 1974.

I. Amer, C. Lucarz, G. Roquier, M. Mattavelli, M. Raulet et al., Reconfigurable video coding on multicore, IEEE Signal Processing Magazine, vol.26, issue.6, pp.113-123, 2009.
DOI : 10.1109/MSP.2009.934107

URL : https://hal.archives-ouvertes.fr/hal-00429360

M. I. Gordon, Compiler techniques for scalable performance of stream programs on multicore architectures, 2010.

J. B. Dennis, First version of a data flow procedure language, Symposium on Programming, pp.362-376, 1974.
DOI : 10.1007/3-540-06859-7_145

P. Aubry, P. Beaucamps, F. Blanc, B. Bodin, S. Carpov et al., Extended Cyclostatic Dataflow Program Compilation and Execution for an Integrated Manycore Processor, Procedia Computer Science, vol.18, pp.1624-1633, 2013.
DOI : 10.1016/j.procs.2013.05.330

URL : https://hal.archives-ouvertes.fr/hal-00832504

G. Bilsen, M. Engels, R. Lauwereins, and J. Peperstraete, Cycle-static dataflow, IEEE Transactions on Signal Processing, vol.44, issue.2, pp.397-408, 1996.
DOI : 10.1109/78.485935

R. Deriche, Using canny's criteria to derive a recursively implemented optimal edge detector Available: https://doi, International Journal of Computer Vision, vol.110, issue.2, pp.167-187, 1007.
DOI : 10.1007/bf00123164

URL : https://cours.etsmtl.ca/sys844/Documents/Lecture2.pdf

P. Feautrier, Dataflow analysis of array and scalar references, International Journal of Parallel Programming, vol.24, issue.4, pp.23-53, 1991.
DOI : 10.1145/360827.360844

URL : http://www.prism.uvsq.fr/public/paf/dataflow.ps

, Some efficient solutions to the affine scheduling problem, II, multi-dimensional time, International Journal of Parallel Programming, vol.21, issue.6, pp.389-420, 1992.

U. Bondhugula, A. Hartono, J. Ramanujam, and P. Sadayappan, A practical automatic polyhedral parallelizer and locality optimizer, Proceedings of the 29th ACM SIGPLAN Conference on Programming Language Design and Implementation , ser. PLDI '08, pp.101-113, 2008.

A. Darte, R. Schreiber, and G. Villard, Lattice-Based Memory Allocation, IEEE Transactions on Computers, vol.54, issue.10, pp.1242-1257, 2005.
DOI : 10.1109/TC.2005.167

URL : https://hal.archives-ouvertes.fr/hal-02101912

V. Basupalli, T. Yuki, S. Rajopadhye, A. Morvan, S. Derrien et al., ompVerify: Polyhedral Analysis for the OpenMP Programmer, Proceedings of the 7th International Workshop on OpenMP, ser. IWOMP '11, pp.37-53, 2011.
DOI : 10.1007/978-3-642-13217-9_2

URL : https://hal.archives-ouvertes.fr/hal-00752626

, Author Version of « Polyhedral DataFlow Programming, a Case Study, 2018.

T. Yuki, P. Feautrier, S. Rajopadhye, and V. Saraswat, Array dataflow analysis for polyhedral X10 programs, Proceedings of the 18th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, ser. PPoPP '13, pp.23-34, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00761537

M. Benabderrahmane, L. Pouchet, A. Cohen, and C. Bastoul, The Polyhedral Model Is More Widely Applicable Than You Think, Proceedings of the 19th Joint European Conference on Theory and Practice of Software, International Conference on Compiler Construction, ser. CC'10, pp.283-303, 2010.
DOI : 10.1007/978-3-642-11970-5_16

URL : https://hal.archives-ouvertes.fr/inria-00551087

S. Rus, L. Rauchwerger, and J. Hoeflinger, Hybrid analysis, Proceedings of the 16th international conference on Supercomputing , ICS '02, pp.251-283, 2003.
DOI : 10.1145/514191.514229

S. Rus, G. He, C. Alias, and L. Rauchwerger, Region array SSA, Proceedings of the 15th international conference on Parallel architectures and compilation techniques , PACT '06, 2006.
DOI : 10.1145/1152154.1152165

A. Jimborean, P. Clauss, J. Dollinger, V. Loechner, and M. J. Manuel, Dynamic and Speculative Polyhedral Parallelization Using Compiler-Generated Skeletons, International Journal of Parallel Programming, vol.30, issue.3, pp.529-545, 2014.
DOI : 10.1017/S095679680200463X

URL : https://hal.archives-ouvertes.fr/hal-00825738

J. Travis and J. Kring, LabVIEW for everyone: graphical programming made easy and fun, 2007.

M. Abadi, P. Barham, J. Chen, Z. Chen, A. Davis et al., Tensorflow: A system for large-scale machine learning, OSDI, pp.265-283, 2016.

E. A. Lee and D. G. Messerschmitt, Static Scheduling of Synchronous Data Flow Programs for Digital Signal Processing, IEEE Transactions on Computers, vol.36, issue.1, pp.24-355009446, 1987.
DOI : 10.1109/TC.1987.5009446

L. Morel, M. Selva, K. Marquet, C. Saysset, and T. Risset, CalMAR -a Multi-Application Dataflow Runtime (short paper) Available: https, Thirteenth ACM International Conference on Embedded Software 2017, EMSOFT'17, 2017.

T. Grosser, S. Pop, R. J. , and S. Sadayappan, On recovering multi-dimensional arrays in Polly, IMPACT 2015 -5th International Workshop on Polyhedral Compilation Techniques IMPACT 2015, p.9, 2015.

F. Branchaud-charron and F. R. Lee, Keras: The Python Deep Learning library Available: https

S. Verdoolaege, Polyhedral Process Networks, pp.1335-1375

, Available: https://doi.org/10

P. Feautrier, Scalable and Structured Scheduling, International Journal of Parallel Programming, vol.28, issue.6, pp.459-487, 1007.
DOI : 10.1007/s10766-006-0011-4

C. Alias and A. Plesco, Data-aware Process Networks Inria -Research Centre Grenoble ? Rhône-Alpes Available: https, 2015.

C. Alias, Improving Communication Patterns in Polyhedral Process Networks INRIA Grenoble -Rhône-Alpes Available: https, 2017.

B. Kenhuis, E. Rijpkema, and E. F. Deprettere, Compaan, Proceedings of the eighth international workshop on Hardware/software codesign , CODES '00, 2000.
DOI : 10.1145/334012.334015

J. T. Zhai, H. Nikolov, and T. Stefanov, Modeling adaptive streaming applications with parameterized polyhedral process networks, Proceedings of the 48th Design Automation Conference on, DAC '11, pp.116-121, 2011.
DOI : 10.1145/2024724.2024752

S. Derrien, A. Turjan, C. Zissulescu, and E. F. Deprettere, Deriving efficient control in Process Networks with Compaan/Laura Available: https, International Journal of Embedded Systems, p.20298, 2008.

K. Didier, A. Cohen, A. Gauffriau, A. Graillat, and D. Potop-butucaru, Sheep in wolf's clothing: Implementation models for data-flow multi-threaded software Available: https, Inria Paris, 2017.

A. Cohen, A. Darte, and P. Feautrier, Static Analysis of OpenStream Programs CNRS ; Inria, ENS Lyon, issue.16, 2016.

, Available: https

A. Sb??rleasb??rlea, J. Shirako, L. Pouchet, and V. Sarkar, Polyhedral optimizations for a data-flow graph language, Languages and Compilers for Parallel Computing, pp.57-72, 2016.

A. Balevic and B. Kienhuis, A data parallel view on polyhedral process networks, Proceedings of the 14th International Workshop on Software and Compilers for Embedded Systems, SCOPES '11, pp.38-47, 2011.
DOI : 10.1145/1988932.1988939

G. Bosilca, A. Bouteiller, A. Danalis, T. Herault, and J. Dongarra, From Serial Loops to Parallel Execution on Distributed Systems, Euro-Par 2012 Parallel Processing, pp.246-257, 2012.
DOI : 10.1007/978-3-642-32820-6_25