Parallelizing Evolutionary Algorithms on GPGPU Cards with the EASEA Platform

[1]  Carlos M. Fonseca,et al.  Exploring the Performance of Stochastic Multiobjective Optimisers with the Second-Order Attainment Function , 2005, EMO.

[2]  Jean-Philippe Rennard,et al.  Stochastic Optimization Algorithms , 2007, ArXiv.

[3]  Nicolas Lachiche,et al.  Coarse grain parallelization of evolutionary algorithms on GPGPU cards with EASEA , 2009, GECCO.

[4]  Cyril Fonlupt,et al.  Population Parallel GP on the G80 GPU , 2008, EuroGP.

[5]  Philippe Clauss,et al.  Efficient Parallel Implementation of Evolutionary Algorithms on GPGPU Cards , 2009, Euro-Par.

[6]  Gary B. Lamont,et al.  Multiobjective Evolutionary Algorithms: Analyzing the State-of-the-Art , 2000, Evolutionary Computation.

[7]  Lothar Thiele,et al.  Comparison of Multiobjective Evolutionary Algorithms: Empirical Results , 2000, Evolutionary Computation.

[8]  Pierre Collet,et al.  Speedups between ×70 and ×120 for a Generic Local Search (Memetic) Algorithm on a Single GPGPU Chip , 2010, EvoApplications.

[9]  Nicolas Lachiche,et al.  Fast Evaluation of GP Trees on GPGPU by Optimizing Hardware Scheduling , 2010, EuroGP.

[10]  Tien-Tsin Wong,et al.  Evolutionary Computing on Consumer Graphics Hardware , 2007, IEEE Intelligent Systems.

[11]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[12]  Marc Schoenauer,et al.  Take It EASEA , 2000, PPSN.

[13]  Enrique Alba,et al.  Parallelism and evolutionary algorithms , 2002, IEEE Trans. Evol. Comput..

[14]  Nicolas Lachiche,et al.  EASEA parallelization of tree-based Genetic Programming , 2010, IEEE Congress on Evolutionary Computation.

[15]  Zhigeng Pan,et al.  Parallel Genetic Algorithms on Programmable Graphics Hardware , 2005, ICNC.