Abstract. The availability of low cost powerful parallel graphics cards has stimulated a trend to port GP on Graphics Processing Units (GPUs). Previous works on GPUs have shown evaluation phase speedups for large training cases sets. Using the CUDA language on the G80 GPU, we show it is possible to efficiently interpret several GP programs in parallel, thus obtaining speedups also for small training sets starting at less than 100 training cases. Our scheme was embedded in the well-known ECJ library, providing an easy entry point for owners of G80 GPUs.
GPU-accelerated computing drives current scientific research. Writing fast numeric algorithms for GP...
Abstract—In this paper, we present three parallel cultural algorithms using CUDA-enabled GPUs. First...
A Single Instruction Multiple Thread CUDA interpreter provides SIMD like parallel evaluation of the ...
Abstract The availability of low cost powerful parallel graphics cards has stim-ulated the port of G...
The availability of low cost powerful parallel graphics cards has stimulated the port of Genetic Pro...
This paper investigates the speed improvements available when using a graphics processing unit (GPU)...
Graphics Processing Units (GPUs) were originally developed for computer gaming and other graphical t...
In this research, we have implemented a parallel EP on consumer-level graphics processing units and ...
GPU-accelerated computing drives current scientific research. Writing fast numeric algorithms for GP...
This diploma shows how to solve a compute-intensive problem using a graphics processing unit. Curre...
Abstract. Large graphs involving millions of vertices are common in many prac-tical applications and...
This thesis represents master's thesis focused on acceleration of Genetic algorithms using GPU. Firs...
The future of computation is the GPU, i.e. the Graphical Processing Unit. The graphics cards have sh...
The computational speed on microprocessors is increasing faster than the communication speed, especi...
Graphic processors are becoming faster and faster. Computational power within graphic processing uni...
GPU-accelerated computing drives current scientific research. Writing fast numeric algorithms for GP...
Abstract—In this paper, we present three parallel cultural algorithms using CUDA-enabled GPUs. First...
A Single Instruction Multiple Thread CUDA interpreter provides SIMD like parallel evaluation of the ...
Abstract The availability of low cost powerful parallel graphics cards has stim-ulated the port of G...
The availability of low cost powerful parallel graphics cards has stimulated the port of Genetic Pro...
This paper investigates the speed improvements available when using a graphics processing unit (GPU)...
Graphics Processing Units (GPUs) were originally developed for computer gaming and other graphical t...
In this research, we have implemented a parallel EP on consumer-level graphics processing units and ...
GPU-accelerated computing drives current scientific research. Writing fast numeric algorithms for GP...
This diploma shows how to solve a compute-intensive problem using a graphics processing unit. Curre...
Abstract. Large graphs involving millions of vertices are common in many prac-tical applications and...
This thesis represents master's thesis focused on acceleration of Genetic algorithms using GPU. Firs...
The future of computation is the GPU, i.e. the Graphical Processing Unit. The graphics cards have sh...
The computational speed on microprocessors is increasing faster than the communication speed, especi...
Graphic processors are becoming faster and faster. Computational power within graphic processing uni...
GPU-accelerated computing drives current scientific research. Writing fast numeric algorithms for GP...
Abstract—In this paper, we present three parallel cultural algorithms using CUDA-enabled GPUs. First...
A Single Instruction Multiple Thread CUDA interpreter provides SIMD like parallel evaluation of the ...