D. Hendricks, D. Cieslakiewicz, D. Wilcox, T. Gebbie
During times of stock market turbulence, monitoring the intraday clustering behaviour of financial instruments allows one to better understand market characteristics and systemic risks. While genetic algorithms provide a versatile methodology for identifying such clusters, serial implementations are computationally intensive and can take a long time to converge to the global optimum. We implement a […]
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W. B. Langdon, M. Harman
Genetic Programming (GP) may dramatically increase the performance of software written by domain experts. GP and autotuning are used to optimise and refactor legacy GPGPU C code for modern parallel graphics hardware and software. Speed ups of more than six times on recent nVidia GPU cards are reported compared to the original kernel on the […]
Hasan Furhad, Fahmida Ahmed, Faisal Faruque, Iqbal Hasan Sarker
Construction of optimal schedule for airline crew-scheduling requires high computation time. The main objective to create this optimal schedule is to assign all the crews to available flights in a minimum amount of time. This is a highly constrained optimization problem. In this paper, we implement co-evolutionary genetic algorithm in order to solve this problem. […]
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W. B. Langdon, M. Harman
Genetic Programming (GP) may dramatically increase the performance of software written by domain experts. GP and autotuning are used to optimise and refactor legacy GPGPU C code for modern parallel graphics hardware and software. Speed ups of more than six times on recent nVidia GPU cards are reported compared to the original kernel on the […]
Vuppuluri Sumati
This paper deals about the parallel implementation of the compact Genetic Algorithm on the Compute Unified Device Architecture (CUDA) platform of GPU. We elaborate implementation details on the parallel platform.
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Sandor Szenasi, Zoltan Vamossy
The use of digital microscopy allows diagnosis through automated quantitative and qualitative analysis of the digital images. Often to evaluate the samples, the first step is determining the number and location of cell nuclei. For this purpose, we have developed a GPGPU based data-parallel region growing algorithm that is equally as accurate as the already […]
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Jorge F. Fabeiro, Diego Andrade, Basilio B. Fraguela
Nowadays, computers include several computational devices with parallel capacities, such as multicore processors and Graphic Processing Units (GPUs). OpenCL enables the programming of all these kinds of devices. An OpenCL program consists of a host code which discovers the computational devices available in the host system and it queues up commands to the devices, and […]
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Tony Lewis
Evolution through natural selection offers the possibility of automatically generating functionally complex solutions to a wide range of problems. Methods such as Genetic Programming (GP) show the promise of this approach but tend to stagnate after relatively few generations. To research this issue, execution speed must be substantially improved. This thesis presents work to accelerate […]
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Alwyn V. Husselmann, K. A. Hawick
Genetic Programming (GP) has been employed in many problem domains, and as a result, it has been the subject of much scientific inquiry. The extensive literature body of GP has reported applications in algorithm discovery, image enhancement and cooperative multi-agent systems, as well as many other areas and disciplines, such as agent-based modelling in Geography […]
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Martin Burtscher, Hassan Rabeti
This paper presents a fast GPU implementation of a genetic algorithm for synthesizing bimodal predictor FSMs of a given size. Bimodal predictors, i.e., predictors that make binary yes/no predictions, are ubiquitous in microprocessors. Many of these predictors are based on finite-state machines (FSMs). However, there are countless possible FSMs and even heuristic searches for finding […]
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A.V. Husselmann, K.A. Hawick
Population-based evolutionary algorithms continue to play an important role in artifically intelligent systems, but can not always easily use parallel computation. We have combined a geometric (any-space) particle swarm optimisation algorithm with use of Ferreira’s Karva language of gene expression programming to produce a hybrid that can accelerate the genetic operators and which can rapidly […]
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Maciej Kolomycki
This article presents a method of implementation genetic algorithm in CUDA. Used algorithm operat on a large population and a complex genotype, so that it exceeded the size of the cache memory. It is not completely transferred to the graphics card. It consists of modules that run on the CPU and are synchronized through it. […]
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