Evolutionary algorithms (EA) are proven effective and robust in searching large varied spaces in a wide range of applications such as feature selection, electrical-circuit synthesis, and data mining. A growing demand from the multimedia and games industries has enabled graphics hardware companies to develop high-performance parallel graphics accelerators that resulted in the development of graphics processing unit (GPU). GPU handles rendering requests using a 3D graphics application programming interface (API). GPU lets processors communicate with any other processor directly, which enables to implement more flexible, fine grained EAs. A parallel EA can be implemented on consumer graphics cards found in many PCs. Evolutionary programming an...
Genetic programming (GP) is a machine learning technique that is based on the evolution of computer ...
Genetic algorithms (GAs) are optimization techniques which imitate the way that nature selects the b...
International audienceA parallel solution to the implementation of evolutionary algorithms is propos...
Evolutionary Algorithms (EAs) are effective and robust methods for solving many practical problems s...
In this research, we have implemented a parallel EP on consumer-level graphics processing units and ...
In this paper, we propose to parallelize a Hybrid Genetic Algorithm (HGA) on Graphics Processing Uni...
In this paper, we report a parallel Hybrid Genetic Algorithm (HGA) on consumer-level graphics cards....
Graphical Processing Units stand for the success of Artificial Neural Networks over the past decade ...
Genetic Algorithms (GAs) is proven to be effective in solving many optimization tasks. GAs is one of...
Recent years have witnessed the emergence of a huge number of parallel computer architectures. Almos...
Many optimization problems have complex search space, which either increase the solving problem time...
Graphic processing units (GPUs) emerged recently as an exciting new hardware environment for a truly...
Evolutionary algorithms have been gaining increased attention the past few years because of their ve...
A genetic algorithm (GA) is an optimization method based on natural selection. Genetic algorithms ha...
General purpose graphic programming unit (GPGPU) programming is a novel approach for solving paralle...
Genetic programming (GP) is a machine learning technique that is based on the evolution of computer ...
Genetic algorithms (GAs) are optimization techniques which imitate the way that nature selects the b...
International audienceA parallel solution to the implementation of evolutionary algorithms is propos...
Evolutionary Algorithms (EAs) are effective and robust methods for solving many practical problems s...
In this research, we have implemented a parallel EP on consumer-level graphics processing units and ...
In this paper, we propose to parallelize a Hybrid Genetic Algorithm (HGA) on Graphics Processing Uni...
In this paper, we report a parallel Hybrid Genetic Algorithm (HGA) on consumer-level graphics cards....
Graphical Processing Units stand for the success of Artificial Neural Networks over the past decade ...
Genetic Algorithms (GAs) is proven to be effective in solving many optimization tasks. GAs is one of...
Recent years have witnessed the emergence of a huge number of parallel computer architectures. Almos...
Many optimization problems have complex search space, which either increase the solving problem time...
Graphic processing units (GPUs) emerged recently as an exciting new hardware environment for a truly...
Evolutionary algorithms have been gaining increased attention the past few years because of their ve...
A genetic algorithm (GA) is an optimization method based on natural selection. Genetic algorithms ha...
General purpose graphic programming unit (GPGPU) programming is a novel approach for solving paralle...
Genetic programming (GP) is a machine learning technique that is based on the evolution of computer ...
Genetic algorithms (GAs) are optimization techniques which imitate the way that nature selects the b...
International audienceA parallel solution to the implementation of evolutionary algorithms is propos...