Search Results for "parallel genetic algorithm" - Page 4
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Showing 242 open source projects for "parallel genetic algorithm"
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Eye candy showing parallel Conway's Life games in the bit planes of the screen, using boolean BitBlt operations. (Independently rediscovered algorithm given already in Smalltalk-80 Blue Book, by the inventors of BitBlt.)
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ESTReMo
An evolutionary simulator of transcription regulatory networks
ESTReMo is a genetic algorithm-based simulator to explore the evolution of transcription factors and their binding motifs on realistic genomic backgrounds. -
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fPotencia
Power flow library in C++
fPotencia is the fruit of free time and passion for power systems simulation. After observing the lack of ready-to-implement libraries for power system analisys, and that the existing ones focus on command line workflow, I decided myself to start a project to fill the gap. Since Power system simulations have started needing to be executed in parallel, the old C-like designs are outdated; modular design is now needed to launch many simulations at the same time based on a base... -
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Evolutionary Nursery
A simple genetic algorithm for numerical optimization
Evolutionary nursery is a result for my passion for developing genetic algorithms. I implemented this simple GA in 2008. This is especially intended for numerical optimization problems. -
Desktop and Mobile Device Management SoftwareDesktop Central is a unified endpoint management (UEM) solution that helps in managing servers, laptops, desktops, smartphones, and tablets from a central location.
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Genetic Programming in OpenCL is a parallel implementation of genetic programming targeted at heterogeneous devices, such as CPU and GPU. It is written in OpenCL, an open standard for portable parallel programming across many computing platforms.
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FamSeq
Variant calling on the basis of pedigree information
...FamSeq accommodates de novo mutations and can perform variant calling at chromosome X. To accommodate variations in data complexity, FamSeq consists of three distinct implementations of the Mendelian genetic model: the Bayesian network algorithm, Elston-Stewart algorithm and Markov chain Monte Carlo algorithm. To make the software efficient and applicable to large families, we parallelized the Bayesian network algorithm that copes with pedigrees with inbreeding loops without losing calculation precision on an NVIDIA® graphics processing unit. -
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Ezys
Ezys 3D medical image registration program
Ezys is a non-linear 3D medical image registration program. Ezys fully exploits the parallel computing power of inexpensive commercial graphics processing units (GPU), resulting in a very fast and accurate program capable of running on desktop PCs and even some laptops. On these systems, non-linear image registrations take less than a minute to complete. Ezys implements a diffeomorphic inverse consistent image registration algorithm with a demons-style regularization based on a non-parametric free form deformation model. ... -
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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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NEAT Visualizer SFML
A NEAT Implementation and Visualization System
Evolves neural networks using the Neuro-Evolution of Augmenting Topologies (NEAT) technique. A separate visualization system uses another genetic algorithm to evolve images of the otherwise dimensionless networks so their structure can be observed. -
AI-First Supply Chain ManagementLogility is a market-leading provider of AI-first supply chain management solutions engineered to help organizations build sustainable digital supply chains that improve people’s lives and the world we live in. The company’s approach is designed to reimagine supply chain planning by shifting away from traditional “what happened” processes to an AI-driven strategy that combines the power of humans and machines to predict and be ready for what’s coming. Logility’s fully integrated, end-to-end platform helps clients know faster, turn uncertainty into opportunity, and transform the supply chain from a cost center to an engine for growth.
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niGA
Heterogenous Multiprocessor Scheduling Using Genetic Algorithms
Implementation of task scheduling using Genetics algorithm for heterogeneous parallel programming -
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Distributed Multithread Apriori (DMTA)
A parallel implementation using MPI and OpenMP to Apriori algorithm
DMTA (Distributed Multithreaded Apriori) is a parallel implementation of Apriori algorithm, which exploits the parallelism at the level of threads and processes, seeking to perform load balancing among the cores. Was implemented in C++ language, using the parallelization libraries OpenMP and MPI. The algorithm was generated as a result of a project developed by André Camilo Bolina, under the guidance of teachers Marluce Rodrigues Pereira, Ahmed Ali Abdalla Esmin and Denilson Alves Pereira, in Department of Computer Science at Federal University of Lavras. ... -
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VariantMaster
Extract causative variants for monogenic and sporadic genetic diseases
...To improve the identification of the variants from HTS, we developed VariantMaster, an original program that accurately and efficiently extracts causative variants in familial and sporadic genetic diseases. The algorithm takes into account predicted variants (SNPs and indels) in affected individuals or tumor samples and utilizes the row (BAM) data to robustly estimate the conditional probability of segregation in a family, as well as the probability of it being de novo or somatic. In familial cases, various modes of inheritance are considered: X-linked, autosomal dominant, and recessive (homozygosity or compound heterozygosity). ... -
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ALCHEMY is a genotype calling algorithm for Affymetrix and Illumina products which is not based on clustering methods. Features include explicit handling of reduced heterozygosity due to inbreeding and accurate results with small sample sizes
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Evochumps
Evolving recursive artificial neural networks in a simulation.
...It has a built-in evolutionary algorith to let the brains evolve conditoned to selective pressure. The program's interface allows you to manipulate all kinds of parameters of both the simulation, the genetic algorithm, and each particular RNN in real time. -
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PyGAO
Genetic Algorithm Optimization for Python
A simple interface for performing genetic algorithm optimization for numerical problems. I am starting with a stripped-down version, where a solution can be described using a single vector of float numbers. Eventually, I will expand to more generic data structures and add multiple-species search options. For the time being, I have no plans of developing a GUI. For now, this is strictly a computational module. -
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The sequence alignment task in MAGI (magi.ucsd.edu) is based on the miRanda algorithm, but we redesign the miRanda algorithm on GPU by taking its advantages of massively parallel computing and extra high memory bandwidth using using NVIDIA’s Compute Unified Device Architecture (CUDA). The CUDA-miRanda implementation is a fast microRNA target identification algorithm that aligns short nucleotide sequences (i.e., < 32 nucleotides) against longer reference sequences (e.g., 20k nucleotides). ...
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GENIE (GEne-geNe IntEraction)
GPU based Parallel Gene-Gene Interaction Analysis
Gene-gene interaction in genetic association studies is computationally intensive when a large number of SNPs are involved. Most of the latest Central Processing Units (CPUs) have multiple cores, whereas Graphics Processing Units (GPUs) also have hundreds of cores and have been recently used to implement faster scientific software. However, currently there are no genetic analysis software packages that allow users to fully utilize the computing power of these multi-core devices for genetic... -
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PPSeq: Parallel NGS Analysis
Parallel Processing for Next-Generation Sequencing (NGS) Analysis
High-throughput next generation sequencing (NGS) technology has quickly emerged as a powerful tool in many aspects of biomedical research. However, along with its rapid development, the data magnitude and analysis complexity for NGS far exceed the capacity and capability of traditional small-scale computing facilities, such as multithreading algorithms on standalone workstations. To address this issue, here we present a solution using the ever-increasing supply of processing power by massive... -
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ABM-Calibration-SensitivityAnalysis
Codes and Data for Calibration and Sensitivity Analysis of ABM
...<http://jasss.soc.surrey.ac.uk/xx/x/x.html> Methods/Techniques used are: a. Parameter fitting: 1. Full Factorial Design 2. Simple Random Sampling 3. Latin Hypercube Sampling 4. Quasi-Newton Method 5. Simulated Annealing 6. Genetic Algorithm 7. Approximate Bayesian Computation b. Sensitivity Analysis: 1. Local SA 2. Morris Screening 3. DoE 4. Partial (Rank) Correlation Coefficient 5. Standardised (Rank) Regression Coefficient 6. Sobol' 7. eFAST 8. FANOVA Decomposition Have also a look on our other projects: http://www.uni-goettingen.de/de/315075.html -
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gpgmpi
An GPGMP in C++/OpenCL with improved time step algorithm
The need for speed is always a challenge for large-scale stochastic simulation. This software is based on a parallel stochastic simulation algorithm already implemented on Graphics Processing Unit (GPU) for inhomogeneous reaction-drift-diffusion systems. We suggest an improved choice of time step which turns out to be almost 3 or even more times fast with nearly identical accuracy. The software is now completely implemented in C++ and OpenCL which only depends on boost library and GPU vendor’s OpenCL SDK. ... -
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NNBrain
A free, open source collection of neural network based AI agents.
NNBrain is a free and open source collection of artificial intelligence agents. These agents have applications in video games, research, business, and more. The included agents function in both discrete and continuous action and state spaces. -
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grn_inference_multigpu
This project is a exhaustive search algoritm for multiple GPUs
...We use CUDA , a general purpose parallel programming platform that allows the usage of NVIDIA GPUs to solve complex problems in an efficient way. -
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The parallelized FDTD Schrodinger Solver implements a parallel algorithm for solving the time-independent 3d Schrodinger equation using the finite difference time domain (FDTD) method. See the Hosted Apps > MediaWiki menu item for more information.
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OpenAIL
Open Artificial Intelligence Library
[Open Artificial Intelligence Library]. This library main goal is to provide a tool box to those who want to use algorithm such as neural network or genetics Algorithm and all algorithms that are commonly within the Artificial Intelligence field. -
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AEvolution
Artificial life game
Artificial life game using a genetic algorithm in a simple 2D world.
