J. Larus, Spending Moore's dividend, Communications of the ACM, vol.52, issue.5, pp.62-69, 2009.
DOI : 10.1145/1506409.1506425

D. Brooks, P. Bose, and S. E. Schuster, Power-Aware Microarchitecture: Design and Modeling Challenges for 800

D. Göddeke, D. Komatitsch, M. Geveler, D. Ribbrock, N. Rajovic et al., The Low-Power Architecture Approach Towards Exascale Computing, Workshop on Scalable 805 Algorithms for Large-Scale Systems (ScalA), pp.1-2, 2011.

X. Nguyen, R. Raynaud, and . Sirdey, Extended Cyclostatic Dataflow Program Compilation and Execution for an Inte- 815 grated Manycore Processor, International Conference on Computational Science (ICCS), p.816

G. Laporte, The traveling salesman problem: An overview of exact and approximate algorithms, European Journal of Operational Research, vol.59, issue.2, pp.231-247, 1992.
DOI : 10.1016/0377-2217(92)90138-Y

N. Multicore and M. , Platforms for an Irregular Application, p.821

&. Architectures, E. H. Denver, H. L. Li, M. Sudarsan, K. C. Stumm et al., Article No. 822 5 Locality and Loop Scheduling on NUMA Multiprocessors, International Conference on Parallel Processing (ICPP), pp.824-825, 1993.

]. R. Xu, I. Wunsch, and D. , Survey of clustering algorithms Finding groups in data: an introduction to cluster analysis, Neural Networks IEEE Transactions on, vol.826, issue.827, pp.645-678, 2005.

A. K. Jain, R. C. Dubes, ]. T. Kanungo, D. Mount, N. Netanyahu et al., Algorithms for Clustering Data An ecient k-means clustering algorithm: 831 analysis and implementation, Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.24, issue.14, pp.829-830, 1988.

. Ho, Large-Scale Parallel Data Mining, Lecture Notes in Computer Science, vol.1759

]. S. Rao, E. V. Prasad, and N. B. Venkateswarlu, A scalable k-means clustering algorithm on Multi-Core architecture, 2009 Proceeding of International Conference on Methods and Models in Computer Science (ICM2CS), pp.837-838, 2009.
DOI : 10.1109/ICM2CS.2009.5397976

]. L. Rodrigues, L. Zarate, C. Nobre, and H. Freitas, Parallel and distributed kmeans to identify the translation initiation 839 site of proteins, in: Systems, Man, and Cybernetics (SMC) The Finite-di?erence Time-domain method for Modeling of Seis- 842 mic Wave Propagation, 2012 IEEE International Conference on Advances in Wave Propagation in Heterogeneous Media, pp.1639-840

H. Aochi, T. Ulrich, A. Ducellier, F. Dupros, and D. Michea, Finite di?erence simulations of seismic wave propagation 845 for understanding earthquake physics and predicting ground motions: Advances and challenges, p.846

]. F. Dupros, H. Do, and H. Aochi, On Scalability Issues of the Elastodynamics Equations on Multicore Platforms, International Conference on Computational Science (ICCS), volume 18 of Procedia Computer Science, pp.851-852
DOI : 10.1016/j.procs.2013.05.289
URL : https://hal.archives-ouvertes.fr/hal-00797682

. Architectures, International Parallel Computing conference (ParCo), volume 19 of Advances in Parallel Com- 856 puting, pp.67-74, 2010.

T. Furumura, L. K. Chen-]-r, L. L. Tesser, F. Pilla, P. O. Dupros et al., Parallel simulation of strong ground motions during recent and historical damaging earth- 861 quakes in tokyo, japan Parallel Graphics and Visualization Improving the performance 863 of seismic wave simulations with dynamic load balancing, Euromicro International Conference on Parallel, 864 Distributed and Network-Based Processing (PDP) Exploiting Intensive Multithreading for the E- 866 cient Simulation of 3D Seismic Wave Propagation International Conference on Computational Science and 867 Engineering, pp.31-149, 2005.

M. Hähnel, B. Döbel, M. Völp, and H. Härtig, Measuring Energy Consumption for Short Code Paths Using RAPL, ACM Sigmetrics Performance Evaluation Review, vol.874, issue.40, pp.13-17, 2012.

C. Andreolli, P. Thierry, L. Borges, C. Yount, and G. Skinner, Genetic Algorithm Based Auto-Tuning of Seismic 876

]. K. Datta, S. Kamil, S. Williams, L. Oliker, J. Shalf et al., Optimization and performance modeling of stencil 879 computations on modern microprocessors, SIAM Review, vol.878, pp.51-129, 2009.

]. R. Love, K. Korner, ]. E. Cpu-anity34, D. A. Padoin, P. De-oliveira et al., Time-to-Solution and Energy-to-Solution: A Comparison 882 between ARM and Xeon, Workshop on Applications for Multi-Core Architectures (WAMCA), pp.881-883, 2003.

]. E. Totoni and B. Behzad, Comparing the Power and Performance of Intel's SCC to State-of-the-Art CPUs and 888

A. Morari, A. Tumeo, O. Villa, S. Secchi, and M. Valero, Ecient sorting on the Tilera manycore architecture, IEEE International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD), IEEE 892 Computer Society, pp.890-891

A. Gharaibeh, E. Santos-neto, L. B. Costa, and M. Ripeanu, The energy case for graph processing on hybrid cpu 894 and gpu systems, Proceedings of the 3rd Workshop on Irregular Applications: Architectures and Algorithms, 895 IA3 '13, pp.1-2, 2013.