… GAs with GPU computing. We assume that readers have basic understanding on GPU
architecture and CUDA programming. If you need to know primary knowledge of GPU computing, …

… Genetic algorithms (GAs) are powerful solutions to … with GPU computing have received
significant attention from both practitioners and researchers, ever since the emergence of GPU-…

… GA and parallel GA categories to work in GPU depending on the type of genetic algorithm.
Parallel GA for GPU covers the architecture of Compute Unified Device Architecture (CUDA). …

… Genetic Algorithm have a subclass known as Cellular Genetic Algorithm (cGA) which … Cellular
Genetic Algorithm (cGA) is implemented for multi-GPU to accelerate the execution process …

… also called cellular Genetic Algorithm (cGA) [9] for implementation of fine grained GAs over
a GPU (SIMT architecture). The 2D structure of cGA maps well to the GPU architecture, which …

… in parallel genetic algorithms (PGAs). We have selected these algorithms because of the …
where running times and other computational resources are greedily consumed by present …

… We present a multi-purpose genetic algorithm, designed and implemented with GPGPU /
CUDA parallel computing … Since genetic algorithms are inherently parallel, the GPGPU …

… Genetic algorithms are effective in solving many optimization … of genetic algorithm on graphics
processing units (GPUs) using … efforts does not utilize the GPU resources effectively. Our …

… to speed up computation. For parallel computing of genetic algorithms on GPUs, we examine
steps of a genetic algorithm and observe three kinds of problems need to be considered: …

… GPU computation is 6.7 and 6.6 times faster than GA-1 and GA-2, respectively. Although the
speedup ratios of GPU computation are … with GPU computation on instances in this study. …