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Improving 3D Medical Image Registration CUDA Software with Genetic Programming

by William B. Langdon, Marc Modat, Justyna Petke, Mark Harman
"... Genetic Improvement (GI) is shown to optimise, in some cases by more than 35%, a critical component of health-care industry software across a diverse range of six nVidia graphics processing units (GPUs). GP and other search based software engineering techniques can automatically op-timise the curren ..."
Abstract - Cited by 2 (2 self) - Add to MetaCart
Genetic Improvement (GI) is shown to optimise, in some cases by more than 35%, a critical component of health-care industry software across a diverse range of six nVidia graphics processing units (GPUs). GP and other search based software engineering techniques can automatically op

Parallel Genetic Algorithm on the CUDA Architecture

by Petr Pospichal, Jiri Jaros, Josef Schwarz - In Applications of Evolutionary Computation, LNCS 6024 , 2010
"... Abstract. This paper deals with the mapping of the parallel island-based genetic algorithm with unidirectional ring migrations to nVidia CUDA software model. The proposed mapping is tested using Rosen-brock’s, Griewank’s and Michalewicz’s benchmark functions. The ob-tained results indicate that our ..."
Abstract - Cited by 11 (1 self) - Add to MetaCart
Abstract. This paper deals with the mapping of the parallel island-based genetic algorithm with unidirectional ring migrations to nVidia CUDA software model. The proposed mapping is tested using Rosen-brock’s, Griewank’s and Michalewicz’s benchmark functions. The ob-tained results indicate that our

Genetically improved CUDA C++ software

by W. B. Langdon, M. Harman - In 17th European Conference on Genetic Programming (EuroGP , 2014
"... Abstract. 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 ..."
Abstract - Cited by 10 (9 self) - Add to MetaCart
Abstract. 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

PGI ® Cuda Fortran

by unknown authors
"... warranty for the use of its products and assumes no responsibility for any errors that may appear, or for damages resulting from the use of the information contained herein. The Portland Group retains the right to make changes to this information at any time, without notice. The software described i ..."
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warranty for the use of its products and assumes no responsibility for any errors that may appear, or for damages resulting from the use of the information contained herein. The Portland Group retains the right to make changes to this information at any time, without notice. The software described

PGI ® Cuda Fortran

by unknown authors
"... warranty for the use of its products and assumes no responsibility for any errors that may appear, or for damages resulting from the use of the information contained herein. The Portland Group retains the right to make changes to this information at any time, without notice. The software described i ..."
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warranty for the use of its products and assumes no responsibility for any errors that may appear, or for damages resulting from the use of the information contained herein. The Portland Group retains the right to make changes to this information at any time, without notice. The software described

PGI ® Cuda Fortran

by unknown authors
"... warranty for the use of its products and assumes no responsibility for any errors that may appear, or for damages resulting from the use of the information contained herein. The Portland Group retains the right to make changes to this information at any time, without notice. The software described i ..."
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warranty for the use of its products and assumes no responsibility for any errors that may appear, or for damages resulting from the use of the information contained herein. The Portland Group retains the right to make changes to this information at any time, without notice. The software described

PGI ® Cuda Fortran

by unknown authors
"... Inc., makes no warranty for the use of its products and assumes no responsibility for any errors that may appear, or for damages resulting from the use of the information contained herein. The Portland Group retains the right to make changes to this information at any time, without notice. The softw ..."
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. The software described in this document is distributed under license from STMicroelectronics and/or The Portland Group and may be used or copied only in accordance with the terms of the license agreement ("EULA").

Genetically Improved BarraCUDA

by W. B. Langdon, Brian Yee, Hong Lam , 2015
"... Spectra-Based Fault Localisation (SBFL) aims to assist de- bugging by applying risk evaluation formulæ (sometimes called suspiciousness metrics) to program spectra and ranking statements according to the predicted risk. Designing a risk evaluation formula is often an intuitive process done by human ..."
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software engineer. This paper presents a Genetic Programming approach for evolving risk assessment formulæ. The empirical evaluation using 92 faults from four Unix utilities produces promising results1. GP-evolved equations can consistently outperform many of the human-designed formulæ, such as Tarantula

Review of Graph Algorithms on GPU using CUDA Architecture

by Trupti R. Desale
"... Abstract — In many practical applications include image processing, space searching, network analysis, graph partitioning etc. in that graphs structure are used to store data with involving millions of vertices. Graph algorithms are fundamental tools in this fields. Hence efficient graph processing ..."
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is must for application performance. In ordered to increase the efficiency, Graphics Processing Unit (GPU) has been adopted to accelerate graph processing. This device can be treated as an array of Single Instruction Multiple Data (SIMD) processors using CUDA software interface by Nvidia. CUDA device has

CUDA Massively Parallel Trajectory Evolution

by Jürgen Leitner (idsia
"... At the European Space Agency a software framework was developed over the last few years focusing on global optimization. The framework, mainly developed in-house at the Advanced Concepts Team (ACT), was released as an ..."
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At the European Space Agency a software framework was developed over the last few years focusing on global optimization. The framework, mainly developed in-house at the Advanced Concepts Team (ACT), was released as an
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