Add to ORKGMackey-Glass chaotic time series prediction and nuclear protein classification show the feasibility of evaluating genetic programming populations directly on parallel consumer gaming graphics processing units. Using a Linux KDE computer equipped with an nVidia GeForce 8800 GTX graphics processing unit card the C++ SPMD interpretter evolves programs at giga GP operation per second (895 million GPops). We use the RapidMind general processing on GPU (GPGPU) framework to evaluate an entire population of a quarter of a million individual programs on a non-trivial problem in 4 seconds. An efficient reverse polish notation (RPN) tree based GP is given
This paper proposes a new approach to produce classification rules based on evolutionary computation...
Estimating Site Frequency Spectrum (SFS) from gene sequences is an important task in population gene...
The isolation with migration (IM) model is important for studies in population genetics and phylogeo...
A Single Instruction Multiple Thread CUDA interpreter provides SIMD like parallel evaluation of the ...
We present a multi-purpose genetic algorithm, designed and implemented with GPGPU / CUDA parallel co...
We created a powerful computing platform based on video cards with the goal of accelerating the perf...
The availability of low cost powerful parallel graphics cards has stimulated the port of Genetic Pro...
In this paper, we describe our work to investigate how much cyclic graph based Genetic Programming (...
This paper investigates the speed improvements available when using a graphics processing unit (GPU)...
Genetic programming (GP) is a machine learning technique that is based on the evolution of computer ...
This thesis represents master's thesis focused on acceleration of Genetic algorithms using GPU. Firs...
As the field of Genetic Programming (GP) matures and its breadth of application increases, the need ...
Abstract The availability of low cost powerful parallel graphics cards has stim-ulated the port of G...
Parallel genetic algorithms are usually implemented on parallel machines or distributed systems. Thi...
A GPU is used to datamine five million correlations between probes within Affymetrix HG-U133A probes...
This paper proposes a new approach to produce classification rules based on evolutionary computation...
Estimating Site Frequency Spectrum (SFS) from gene sequences is an important task in population gene...
The isolation with migration (IM) model is important for studies in population genetics and phylogeo...
A Single Instruction Multiple Thread CUDA interpreter provides SIMD like parallel evaluation of the ...
We present a multi-purpose genetic algorithm, designed and implemented with GPGPU / CUDA parallel co...
We created a powerful computing platform based on video cards with the goal of accelerating the perf...
The availability of low cost powerful parallel graphics cards has stimulated the port of Genetic Pro...
In this paper, we describe our work to investigate how much cyclic graph based Genetic Programming (...
This paper investigates the speed improvements available when using a graphics processing unit (GPU)...
Genetic programming (GP) is a machine learning technique that is based on the evolution of computer ...
This thesis represents master's thesis focused on acceleration of Genetic algorithms using GPU. Firs...
As the field of Genetic Programming (GP) matures and its breadth of application increases, the need ...
Abstract The availability of low cost powerful parallel graphics cards has stim-ulated the port of G...
Parallel genetic algorithms are usually implemented on parallel machines or distributed systems. Thi...
A GPU is used to datamine five million correlations between probes within Affymetrix HG-U133A probes...
This paper proposes a new approach to produce classification rules based on evolutionary computation...
Estimating Site Frequency Spectrum (SFS) from gene sequences is an important task in population gene...
The isolation with migration (IM) model is important for studies in population genetics and phylogeo...
