. Collective-mind-node, Android application connected to Collective Mind repository to crowdsource characterization and optimization of computer systems using off-the-shelf mobile phones and tablets

B. Aarts, OCEANS: Optimizing compilers for embedded applications, Proc. Euro-Par 97, pp.1351-1356, 1997.
DOI : 10.1007/BFb0002894

J. Ansel, C. Chan, Y. L. Wong, M. Olszewski, Q. Zhao et al., Petabricks: a language and compiler for algorithmic choice, Proceedings of the 2009 ACM SIGPLAN conference on Programming language design and implementation , PLDI '09, pp.38-49, 2009.

K. Asanovic, R. Bodik, B. C. Catanzaro, J. J. Gebis, P. Husbands et al., The landscape of parallel computing research: a view from Berkeley, 2006.

K. Asanovic, The landscape of parallel computing research: a view from Berkeley, 2006.

E. Bailey, PERI auto-tuning, Journal of Physics: Conference Series, vol.125, pp.1-6, 2008.
DOI : 10.1088/1742-6596/125/1/012089

C. M. Bishop, Pattern Recognition and Machine Learning (Information Science and Statistics), 2007.

U. Bondhugula, A. Hartono, J. Ramanujam, and P. Sadayappan, A practical automatic polyhedral program optimization system, ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), 2008.

B. Calder, D. Grunwald, M. Jones, D. Lindsay, J. Martin et al., Evidence-based static branch prediction using machine learning, ACM Transactions on Programming Languages and Systems, vol.19, issue.1, 1997.
DOI : 10.1145/239912.239923

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

Y. Chen, Y. Huang, L. Eeckhout, G. Fursin, L. Peng et al., Evaluating iterative optimization across 1000 data sets, Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), 2010.
DOI : 10.1145/1806596.1806647
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.188.4481

K. D. Cooper, P. J. 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.

T. Cristian, I. Chung, and J. K. Hollingsworth, Active harmony: towards automated performance tuning, Proceedings of the 2002 ACM/IEEE conference on Supercomputing, Supercomputing '02, pp.1-11, 2002.

J. Dongarra, The International Exascale Software Project roadmap, International Journal of High Performance Computing Applications, vol.25, issue.1, pp.3-60, 2011.
DOI : 10.1177/1094342010391989

C. Dubach, T. M. Jones, E. V. Bonilla, G. Fursin, and M. F. O-'boyle, Portable compiler optimization across embedded programs and microarchitectures using machine learning, Proceedings of the IEEE/ACM International Symposium on Microarchitecture (MICRO), 2009.

T. W. Epps and L. B. Pulley, A test for normality based on the empirical characteristic function, Biometrika, vol.70, issue.3, pp.723-726, 1983.
DOI : 10.1093/biomet/70.3.723

D. Ferrucci, Building Watson: An Overview of the DeepQA Project, AI Magazine, vol.31, issue.3, pp.59-79, 2010.

B. Franke, M. F. 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. G. Fursin, M. F. O-'boyle, and P. M. 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
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1.4652

G. Fursin, Collective Tuning Initiative: automating and accelerating development and optimization of computing systems, Proceedings of the GCC Developers' Summit, 2009.
URL : https://hal.archives-ouvertes.fr/inria-00436029

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, 2007.
DOI : 10.1007/978-3-540-69338-3_17

G. Fursin, Y. Kashnikov, A. W. Memon, Z. Chamski, O. Temam et al., Milepost GCC: Machine Learning Enabled Self-tuning Compiler, International Journal of Parallel Programming, vol.16, issue.2???3, pp.296-327, 2011.
DOI : 10.1007/s10766-010-0161-2
URL : https://hal.archives-ouvertes.fr/hal-00685276

G. Fursin, R. Miceli, A. Lokhmotov, M. Gerndt, M. Baboulin et al., Collective Mind: Towards Practical and Collaborative Auto-Tuning, Scientific Programming, pp.309-329, 2014.
DOI : 10.1155/2014/797348
URL : https://hal.archives-ouvertes.fr/hal-01054763

M. Hall, D. Padua, and K. Pingali, Compiler research, Communications of the ACM, vol.52, issue.2, pp.60-67, 2009.
DOI : 10.1145/1461928.1461946

T. Hey, S. Tansley, and K. M. Tolle, The Fourth Paradigm ??? Data-Intensive Scientific Discovery, 2009.
DOI : 10.1007/978-3-642-33299-9_1

E. Geoffrey, S. Hinton, and . Osindero, A fast learning algorithm for deep belief nets, Neural Computation, vol.18, 2006.

J. Hopfield, Neural networks and physical systems with emergent collective computational abilities, Proceedings of the National Academy of Sciences, pp.2554-2558, 1982.

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

H. David and . Hubel, Eye, Brain, and Vision (Scientific American Library, 1995.

Y. Janin, C. Vincent, and R. Duraffort, CARE, the comprehensive archiver for reproducible execution, Proceedings of the 1st ACM SIGPLAN Workshop on Reproducible Research Methodologies and New Publication Models in Computer Engineering, TRUST '14, pp.1-1, 2014.
DOI : 10.1145/2618137.2618138

V. Jimenez, I. Gelado, L. Vilanova, M. Gil, G. Fursin et al., Predictive Runtime Code Scheduling for Heterogeneous Architectures, Proceedings of the International Conference on High Performance Embedded Architectures & Compilers, 2009.
DOI : 10.1007/978-3-540-92990-1_4
URL : https://hal.archives-ouvertes.fr/inria-00445304

T. Kisuki, P. M. Knijnenburg, and M. F. O-'boyle, Combined selection of tile sizes and unroll factors using iterative compilation, Proceedings 2000 International Conference on Parallel Architectures and Compilation Techniques (Cat. No.PR00622), pp.237-246, 2000.
DOI : 10.1109/PACT.2000.888348

P. Kulkarni, W. Zhao, H. Moon, K. Cho, D. Whalley et al., Finding effective optimization phase sequences, Proceedings of the Conference on Languages, Compilers, and Tools for Embedded Systems (LCTES), pp.12-23, 2003.
DOI : 10.1145/780732.780735
URL : http://big-oh.cs.hamilton.edu/~bailey/pubs/conferences/lctes03.pdf

H. T. Kung, F. Luccio, and F. P. Preparata, On Finding the Maxima of a Set of Vectors, Journal of the ACM, vol.22, issue.4, pp.469-476, 1975.
DOI : 10.1145/321906.321910

C. Lattner and V. Adve, LLVM: A compilation framework for lifelong program analysis & transformation, International Symposium on Code Generation and Optimization, 2004. CGO 2004., 2004.
DOI : 10.1109/CGO.2004.1281665

Q. Le, R. Marc-'aurelio-ranzato, M. Monga, K. Devin, G. Chen et al., Building highlevel features using large scale unsupervised learning, International Conference in Machine Learning, 2012.
DOI : 10.1109/icassp.2013.6639343
URL : http://arxiv.org/abs/1112.6209

J. Lu, H. Chen, P. Yew, and W. Hsu, Design and implementation of a lightweight dynamic optimization system, Journal of Instruction-Level Parallelism, 2004.

L. Luo, Y. Chen, C. Wu, S. Long, and G. Fursin, Finding representative sets of optimizations for adaptive multiversioning applications, 3rd Workshop on Statistical and Machine Learning Approaches Applied to Architectures and Compilation (SMART'09), 2009.
URL : https://hal.archives-ouvertes.fr/inria-00436034

I. Manotas, L. Pollock, and J. Clause, SEEDS: a software engineer's energy-optimization decision support framework, Proceedings of the 36th International Conference on Software Engineering, ICSE 2014, pp.503-514, 2014.
DOI : 10.1145/2568225.2568297

J. Mars, N. Vachharajani, R. Hundt, and M. L. Soffa, Contention aware execution, Proceedings of the 8th annual IEEE/ ACM international symposium on Code generation and optimization, CGO '10, pp.257-265, 2010.
DOI : 10.1145/1772954.1772991

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.

R. Miceli, AutoTune: A Plugin-Driven Approach to the Automatic Tuning of Parallel Applications, Proceedings of the 11th International Conference on Applied Parallel and Scientific Computing'12, pp.328-342, 2013.
DOI : 10.1007/978-3-642-36803-5_24

W. Ryan, B. R. Moore, and . Childers, Automatic generation of program affinity policies using machine learning, CC, pp.184-203, 2013.

A. Nisbet, Iterative feedback directed parallelisation using genetic algorithms, Proceedings of the Workshop on Profile and Feedback Directed Compilation in conjunction with International Conference on Parallel Architectures and Compilation Technique (PACT), 1998.

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.

J. Shen, A. L. Varbanescu, H. J. Sips, M. Arntzen, and D. G. Simons, Glinda, Proceedings of the ACM International Conference on Computing Frontiers, CF '13, p.14, 2013.
DOI : 10.1145/2482767.2482785

Y. Shoham and K. Leyton-brown, Multiagent Systems: Algorithmic , Game-Theoretic, and Logical Foundations, 2008.
DOI : 10.1017/CBO9780511811654

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, S. Amarasinghe, M. Martin, and U. Reilly, Meta optimization: Improving compiler heuristics with machine learning, Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI'03), pp.77-90, 2003.

M. J. Voss and R. Eigenmann, ADAPT: Automated De-coupled Adaptive Program Transformation, Proceedings 2000 International Conference on Parallel Processing, 2000.
DOI : 10.1109/ICPP.2000.876107

R. Whaley and J. Dongarra, Automatically Tuned Linear Algebra Software, Proceedings of the IEEE/ACM SC98 Conference, 1998.
DOI : 10.1109/SC.1998.10004
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.108.3487