. Eu-milepost-project, MachIne Learning for Embedded PrOgramS opTimization)

I. Open64, Interactive Compilation Interface for Open64 research compiler

F. Agakov, E. Bonilla, J. Cavazos, B. Franke, G. Fursin et al., Using Machine Learning to Focus Iterative Optimization, International Symposium on Code Generation and Optimization (CGO'06), 2006.
DOI : 10.1109/CGO.2006.37

F. Bodin, T. Kisuki, P. Knijnenburg, M. O. Boyle, and E. Rohou, Iterative compilation in a non-linear optimisation space, Proceedings of the Workshop on Profile and Feedback Directed Compilation, 1998.
URL : https://hal.archives-ouvertes.fr/inria-00475919

M. Byler, J. R. Davies, C. Huson, B. Leasure, and M. Wolfe, Multiple version loops, International Conf. on Parallel Processing, pp.312-318, 1987.

J. Cavazos, G. Fursin, F. Agakov, E. Bonilla, M. O. Boyle et al., Rapidly Selecting Good Compiler Optimizations using Performance Counters, International Symposium on Code Generation and Optimization (CGO'07), 2007.
DOI : 10.1109/CGO.2007.32

J. Cavazos and J. Moss, Inducing heuristics to decide whether to schedule, Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), 2004.

K. Cooper, A. Grosul, T. Harvey, S. Reeves, D. Subramanian et al., ACME: adaptive compilation made efficient, Proceedings of the Conference on Languages, Compilers, and Tools for Embedded Systems (LCTES), 2005.

K. Cooper, P. Schielke, and D. Subramanian, Optimizing for reduced code space using genetic algorithms, Proceedings of the Conference on Languages, Compilers , and Tools for Embedded Systems (LCTES), pp.1-9, 1999.

K. Cooper, D. Subramanian, and L. Torczon, Adaptive optimizing compilers for the 21st century, Journal of Supercomputing, vol.23, issue.1, 2002.

P. C. Diniz and M. C. Rinard, Dynamic feedback: An effective technique for adaptive computing, SIGPLAN Conference on Programming Language Design and Implementation, pp.71-84, 1997.

B. Franke, M. O. 'boyle, J. Thomson, and G. Fursin, Probabilistic source-level optimisation of embedded programs, Proceedings of the Conference on Languages, Compilers, and Tools for Embedded Systems (LCTES), 2005.

G. Fursin, J. Cavazos, M. O. Boyle, and O. Temam, MiDataSets: Creating the Conditions for a More Realistic Evaluation of Iterative Optimization, Proceedings of the International Conference on High Performance Embedded Architectures & Compilers (HiPEAC), 2007.
DOI : 10.1007/978-3-540-69338-3_17

G. Fursin, A. Cohen, M. O. Boyle, and O. Temam, A Practical Method for Quickly Evaluating Program Optimizations, Proceedings of the 1st International Conference on High Performance Embedded Architectures & Compilers (HiPEAC), number 3793 in LNCS, pp.29-46, 2005.
DOI : 10.1007/11587514_4

URL : https://hal.archives-ouvertes.fr/inria-00001054

G. Fursin, C. Miranda, O. Temam, M. Namolaru, E. Yom-tov et al., Milepost gcc: machine learning based research compiler, Proceedings of the GCC Developers' Summit, 2008.
URL : https://hal.archives-ouvertes.fr/inria-00294704

G. Fursin, M. O. Boyle, and P. Knijnenburg, Evaluating Iterative Compilation, Proceedings of the Workshop on Languages and Compilers for Parallel Computers (LCPC), pp.305-315, 2002.
DOI : 10.1007/11596110_24

G. Fursin and O. Temam, Collective optimization, Proceedings of the International Conference on High Performance Embedded Architectures & Compilers, 2009.
URL : https://hal.archives-ouvertes.fr/inria-00445326

K. Heydemann and F. Bodin, Iterative compilation for two antagonistic criteria: Application to code size and performance, Proceedings of the 4th Workshop on Optimizations for DSP and Embedded Systems, 2006.

K. Hoste and L. Eeckhout, Cole, Proceedings of the sixth annual IEEE/ACM international symposium on Code generation and optimization , CGO '08, 2008.
DOI : 10.1145/1356058.1356080

T. Kisuki, P. Knijnenburg, M. O. Boyle, and H. Wijshoff, Iterative compilation in program optimization, Proceedings of the Workshop on Compilers for Parallel Computers (CPC2000), pp.35-44, 2000.

P. Kulkarni, W. Zhao, H. Moon, K. Cho, D. Whalley et al., Finding effective optimization phase sequences, Proc. Languages, Compilers, and Tools for Embedded Systems (LCTES), pp.12-23, 2003.

J. Lau, M. Arnold, M. Hind, and B. Calder, Online performance auditing: Using hot optimizations without getting burned, Proceedings of the ACM SIGPLAN Conference on Programming Languaged Design and Implementation (PLDI), 2006.

X. Li, M. J. Garzarán, and D. Padua, A dynamically tuned sorting library, CGO '04: Proceedings of the international symposium on Code generation and optimization, p.111, 2004.

F. Matteo and S. Johnson, FFTW: An adaptive software architecture for the FFT, Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, pp.1381-1384, 1998.

T. Mitchel, Machine Learning, 1997.

A. Monsifrot, F. Bodin, and R. Quiniou, A Machine Learning Approach to Automatic Production of Compiler Heuristics, Proceedings of the International Conference on Artificial Intelligence: Methodology, Systems, Applications, LNCS 2443, pp.41-50, 2002.
DOI : 10.1007/3-540-46148-5_5

Z. Pan and R. Eigenmann, Fast and effective orchestration of compiler optimizations for automatic performance tuning, Proceedings of the International Symposium on Code Generation and Optimization (CGO), pp.319-332, 2006.

B. Singer and M. Veloso, Learning to predict performance from formula modeling and training data, Proceedings of the Conference on Machine Learning, 2000.

M. Stephenson and S. Amarasinghe, Predicting Unroll Factors Using Supervised Classification, International Symposium on Code Generation and Optimization, pp.123-134, 2005.
DOI : 10.1109/CGO.2005.29

M. Stephenson, M. Martin, and U. O. Reilly, Meta optimization: Improving compiler heuristics with machine learning, Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), pp.77-90, 2003.

S. Triantafyllis, M. Vachharajani, N. Vachharajani, and D. August, Compiler optimization-space exploration, International Symposium on Code Generation and Optimization, 2003. CGO 2003., pp.204-215, 2003.
DOI : 10.1109/CGO.2003.1191546

M. J. Voss and R. Eigemann, High-level adaptive program optimization with adapt, PPoPP '01: Proceedings of the eighth ACM SIGPLAN symposium on Principles and practices of parallel programming, pp.93-102, 2001.

R. Whaley and J. Dongarra, Automatically Tuned Linear Algebra Software, Proceedings of the IEEE/ACM SC98 Conference, 1998.
DOI : 10.1109/SC.1998.10004

I. Witten, Data mining, ACM SIGMOD Record, vol.31, issue.1, 2005.
DOI : 10.1145/507338.507355

M. Zhao, B. R. Childers, and M. L. Soffa, A model-based framework: an approach for profit-driven optimization, Proceedings of the Interational Conference on Code Generation and Optimization (CGO), pp.317-327, 2005.