Search Results for "genetic algorithm cuda"
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Showing 29 open source projects for "genetic algorithm cuda"
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pgapack, the parallel genetic algorithm library is a powerfull genetic algorithm library by D. Levine, Mathematics and Computer Science Division Argonne National Laboratory. The library is written in C. PGAPy wraps this library for use with Python.
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GSvit
Fast FDTD solver with graphics card support
Fast FDTD solver with graphics card support. Optimized for nanoscale optics - scanning near field optical microscopy, rough surface scattering and solar cells. Uses CUDA environment for graphics card operation. -
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The ASCO project aims to bring circuit optimization capabilities to existing SPICE simulators using a high-performance parallel differential evolution (DE) optimization algorithm. It supports Eldo, HSPICE, LTspice, Spectre, and Qucs.
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CUDASW++: Smith-Waterman Algorithm
The fastest Smith-Waterman protein database search algorithm on GPUs
CUDASW++ software is a public open source software for Smith-Waterman protein database searches on Graphics Processing Units with CUDA. This software have been added to the NVIDIA Tesla Bio Workbench (http://www.nvidia.com/object/swplusplus_on_tesla.html -
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xmrMiner
A CUDA based miner for Monero
An optimized Monero miner designed to maximize GPU mining efficiency. -
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CUDA-Quicksort
CUDA-Quicksort: A GPU-based implementation of the quicksort algorithm
CUDA-quicksort is a GPU-based implementation of the quicksort algorithm. CUDA-quicksort is designed to exploit the power computing of modern NVIDIA GPUs. "Two GPU-based implementations of the quicksort were presented in literature: the GPU-quicksort, a compute-unified device architecture (CUDA) iterative implementation, and the CUDA dynamic parallel (CDP) quicksort, a recursive implementation provided by NVIDIA Corporation."[*]. -
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Parallel Neural Networks
Neural networks in CUDA & OpenCL with back propagation algorithm
This project is my engineering diploma. It's aim is to compare the efficiency of both technologies and to check where which hacks works better. What is more one of my tasks is to compare different ways of decomposing computations in parallel. -
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HIPAcc
Heterogeneous Image Processing Acceleration (HIPACC) Framework
HIPAcc development has moved to github: https://github.com/hipacc HIPAcc allows to design image processing kernels and algorithms in a domain-specific language (DSL). From this high-level description, low-level target code for GPU accelerators is generated using source-to-source translation. As back ends, the framework supports CUDA, OpenCL, and Renderscript. HIPAcc allows programmers to develop imaging applications while providing high productivity, flexibility and portability as well as competitive performance: the same algorithm description serves as basis for targeting different GPU accelerators and low-level languages. -
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GPU Edge Detector
GPU Interactive Program For Edge detection
This is a standalone, all in one Edge Detector that is mainly running on GPU using the CUDA technology. Each algorithm also has an OpenCV counterpart which is the closest one in terms of speed. This project is partly based on the Sobel Filter sample available as part of the CUDA SDK. This project also partly uses the OpenCV library to load different types of image. This program includes: Prewitt filter, Roberts Cross, Canny edge detector and finally Sobel filter with the ability to modify some variables such as sigma in Canny and see the result in real-time. ... -
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libfgen
Library for optimization using a genetic algorithm or particle swarms
libfgen is a library that implements an efficient and customizable genetic algorithm (GA). It also provides particle swarm optimization (PSO) functionality and an interface for real-valued function minimization or model fitting. It is written in C, but can also be compiled with a C++ compiler. Both Linux and Windows are supported. -
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texgenpack
Texture compression and conversion program with KTX and DDS support.
texgenpack is a texture compression and conversion program featuring a command line utility and a simple GUI program . Compression is implemented using a genetic algorithm. It supports compression, decompression, conversion and comparison of texture and image files. The image format supported is PNG, while for textures there is support for KTX, PKM and DDS using ETC1, ETC2, DXT1/3/5 or BPTC (BC7) texture compression. Several uncompressed texture format are also supported. This program requires the installation of libfgen, also avalable on SourceForge. -
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Bouc-Wen-Baber-Noori model of hysteresis
Compute parameters of the Bouc-Wen-Baber-Noori model of hysteresis
..."A Fast and Elitist multi-objective Genetic Algorithm: NSGA-II". Journal IEEE Transactions on Evolutionary Computation (IEEE-TEC). 2002. Vol. 6. No. 2. pp. 182-197. - Gilberto A. Ortiz, Diego A. Alvarez, Daniel Bedoya-Ruiz. "Identification of Bouc-Wen type models using multi-objective optimization algorithms". Computers & Structures. Vol. 114-115. pp. 121-132. 2013. -
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Alkindus is an automated solver for short monoalphabetic substitution ciphers without word divisions.
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Developed as a final year project at Islamic University of Technology (IUT) during 2010 - 2011 academic year. This code is a simple implementation of real coded genetic algorithm for numerical optimization. Code is written in C/C++.
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Allows CUDA developers to deploy kernels requiring more global GPU memory than is available by transparently mapping pinned CPU memory into the GPU memory map. Works behind the scenes and is easily added to existing projects with minimal effort.
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This library is a lightweight implementation of genetic algorithm, contains the most popular types of chromosomes and the basic algorithms for selection, elitism, crossing and mutation.
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Evolutionary Structural Optimization Package (ESOP) consists of software for viewing, analyzing, and optimizing structures containing beam, truss, and membrane plate elements utilizing OpenGL and the Genetic Algorithm (GA). Created for use in M.S. theses
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libida si library which implements Rabin's Information Dispersal Algorithm through various kernels (e.g. CUDA).
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Searches for adecuate design for feedforward backpropagation neural network, employing genetic algorithm as refining engine. The result topolgy may not be orthodox.
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This project aims to create an application to solve the job shop schedule problem using genetic algorithm on the IBM Cell BE processor. This is useful especially using the power of Cell for the large scale job shop schedule problem.
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A flexible programming library for evolutionary computation. Steady-state, generational and island model genetic algorithms are supported, using Darwinian, Lamarckian or Baldwinian evolution. Includes support for multiprocessor and distributed systems.
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NullAllEst is the implementation of a maximum likelihood algorithm to estimate the frequency of a null allele in microsatellite genetic data. A Markov Chain Monte Carlo simulation is used to solve the likelihood function.
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Disk Optimizer selects files to be placed on any disk medium that will maximize the space used. It is very efficient in finding an optimum file set since it uses a Genetic Algorithm instead of brute force.
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The goal of the Rats and Mazes project is to build a simple genetic algorithm to find general solutions to random non-cyclic single path mazes. I believe that the solutions will tend towards either the right/left-hand rule.
