R. Allen and K. Kennedy, Optimizing Compilers for Modern Architectures: A Dependence- Based Approach, 2002.

D. Barthou, A. C. Rubial, W. Jalby, S. Koliai, and C. Valensi, Performance Tuning of x86 OpenMP Codes with MAQAO, 2010.
DOI : 10.1007/978-3-642-11261-4_7

D. Callahan, J. Dongarra, and D. Levine, Vectorizing compilers: a test suite and results, Proceedings. SUPERCOMPUTING '88, 1988.
DOI : 10.1109/SUPERC.1988.44642

R. Cytron, J. Ferrante, B. K. Rosen, M. N. Wegman, and F. K. Zadeck, Efficiently computing static single assignment form and the control dependence graph, ACM Transactions on Programming Languages and Systems, vol.13, issue.4, 1991.
DOI : 10.1145/115372.115320

A. E. Eichenberger, P. Wu, and K. O-'brien, Vectorization for SIMD architectures with alignment constraints, ACM SIGPLAN Conf. on Programming Language Design and Implementation, 2004.

E. Park, L. N. Cavazos, J. Cohen, A. Sadayappan, and P. , Predictive modeling in a polyhedral optimization space, In: ACM/IEEE Intl. Conf. on Code Generation and Optimization, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00918653

J. Holewinski, R. Ramamurthi, M. Ravishankar, N. Fauzia, L. N. Pouchet et al., Dynamic trace-based analysis of vectorization potential of applications, ACM SIGPLAN Conf. on Programming Language Design and Implementation, 2012.

A. Ketterlin and P. Clauss, Prediction and trace compression of data access addresses through nested loop recognition, Proceedings of the sixth annual IEEE/ACM international symposium on Code generation and optimization , CGO '08, pp.94-103, 2008.
DOI : 10.1145/1356058.1356071

URL : https://hal.archives-ouvertes.fr/inria-00504597

M. Kong, R. Veras, K. Stock, F. Franchetti, L. N. Pouchet et al., When polyhedral transformations meet SIMD code generation, ACM SIGPLAN Conf. on Programming Language Design and Implementation, 2013.
DOI : 10.1145/2491956.2462187

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.307.4089

O. Krzikalla, K. Feldhoff, R. Muller-pfefferkorn, and W. E. Nagel, Scout: A Source-to-Source Transformator for SIMD-Optimizations, 2011.
DOI : 10.1007/978-3-642-29740-3_17

S. Larsen and S. Amarasinghe, Exploiting superword level parallelism with multimedia instruction sets, In: ACM SIGPLAN Conf. on Programming Language Design and Implementation, 2000.
DOI : 10.1145/358438.349320

URL : http://cag.lcs.mit.edu/commit/papers/00/SLarsen-SM.pdf

C. K. Luk, R. Cohn, R. Muth, H. Patil, A. Klauser et al., Pin: building customized program analysis tools with dynamic instrumentation, ACM SIGPLAN Conf. on Programming Language Design and Implementation, 2005.

J. Mak and A. Mycroft, Limits of parallelism using dynamic dependency graphs, Proceedings of the Seventh International Workshop on Dynamic Analysis, WODA '09, 2009.
DOI : 10.1145/2134243.2134253

S. Maleki, Y. Gao, M. J. Garzarn, T. Wong, and D. A. Padua, An evaluation of vectorization compilers, International Conference on Parallel Architectures and Compilation Techniques (PACT), 2011.

D. Nuzman, S. Dyshel, E. Rohou, I. Rosen, K. Williams et al., Vapor SIMD: Auto-vectorize once, run everywhere, International Symposium on Code Generation and Optimization (CGO 2011), 2011.
DOI : 10.1109/CGO.2011.5764683

URL : https://hal.archives-ouvertes.fr/inria-00589692

D. Nuzman and R. Henderson, Multi-platform Auto-vectorization, International Symposium on Code Generation and Optimization (CGO'06), 2006.
DOI : 10.1109/CGO.2006.25

D. Nuzman, I. Rosen, and A. Zaks, Auto-vectorization of interleaved data for SIMD, ACM SIGPLAN Conf. on Programming Language Design and Implementation, 2006.

D. Nuzman and A. Zaks, Autovectorization in GCC-two years later, Proceedings of the GCC Developers Summit, 2006.

P. M. Petersen and D. A. Padua, Static and dynamic evaluation of data dependence analysis, International Conference on Supercomputing, 1993.

M. Pharr and W. R. Mark, ispc: A SPMD compiler for high-performance CPU programming, 2012 Innovative Parallel Computing (InPar), 2012.
DOI : 10.1109/InPar.2012.6339601

G. Tournavitis, Z. Wang, B. Franke, and M. F. Oboyle, Towards a holistic approach to autoparallelization: integrating profile-driven parallelism detection and machine-learning based mapping, In: ACM SIGPLAN Conf. on Programming Language Design and Implementation, 2009.

K. Trifunovic, D. Nuzman, A. Cohen, A. Zaks, and I. Rosen, Polyhedral-model guided loopnest auto-vectorization, International Conference on Parallel Architectures and Compilation Techniques, 2009.
DOI : 10.1109/pact.2009.18

URL : https://hal.archives-ouvertes.fr/hal-00645325