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Java app. to utilise (waste) as much CPU as it can. The application allows the user to create multiple Java threads, each performing a CPU-intensive task tasks with a selectable memory footprint. The options let you 'thrash' the aspect you want.



This article is for you if you have a wish to build your own supercomputer. This explains parallel programming on clusters in a simplified manner. Parallel clustering is changing the face of supercomputing these days. This article shows you how to...



This waitbar was first designed to be used for distributed computing with the Parallel Computing Toolboxd-OC?D? but can be used independently.
classWaitbardist uses 2 other MATLAB custom classes, classTCPIPSender and classTCPIPReceiver, that...



An object oriented library of an Genetic Algorithm, implemented in Java. Clear separation of the several concepts of the algorithm, e.g. Gene, Chromosome, Genotype, Phenotype, Population and Fitness Function. The fitness calculation is parallelized.



Framework to simplify the task of writing and executing threads in Java. Developer writes a Callable with annotations. The executor returns an extended Future with built-in support for cancelling, pausing, calculating progress, and much more.



A similar to Tripwire, file system integrity checking tool but develop in java and cross platform. This tools checking and source control using check sum algorithm like MD5, SHA and CRC. It provide generate current file integiry checksum record to...



A Java workbench and toolkit for developing, evaluating, and playing with classical and state-of-the-art optimization algorithms on standard benchmark problem domains; including reference algorithm implementations, graphing, visualizations and...



A Java based, pMars compatible, CoreWars simulator with Genetic Algorithm warrior evolver functionality. Java 6 is needed. Run with the following command: java -jar CWEvolver-0.4.jar --debug --size 300 validate.red



Galapagos is a Genetic Algorithm framework written in Java 5 with the intended audience of undergraduates in an Artificial Intelligence class. The goal of Galapagos is usability: a competent student should be able to learn this library in an...



LEA is a lightweight eyetracking algorithm library (hence the name) written in and for Java. LEA is able to track eye movements with an ordinary webcam and returns relative movements (up, down, ...). It is also able to compensate for slight head...



LineFold is a Java 6 implementation of the TeX paragraph line-breaking algorithm.



Java API for implementing any kind of Genetic Algorithm and Genetic Programming applications quickly and easily. Contains a wide range of ready-to-use GA and GP algorithms and operators to be plugged-in or extended. Includes Tutorials and Examples.



SpeedyGA is a vectorized implementation of a genetic algorithm in the Matlab programming language. Without bells and whistles, it faithfully implements the specification for a Simple GA given on pgs 10, 11 of M. Mitchell's GA book. See comments in...



Java framework for applying meta-heuristic (multi-objective) optimization algorithms like an Evolutionary Algorithm, Particle Swarm Optimizer, Differential Evolution, or Simulated Annealing to arbitrary optimization problems.(visit:...



JNSGA2 is a Java library with an implementation of the multi-objective genetic algorithm NSGA-II published by Deb et al.



A Java implementation of the NEAT algorithm as created by Kenneth O Stanley. Also provides a toolkit for further experiments to be created and can provide both local and distributed learning environments.



GAIA is a framework that allows OO projects to use Genetic Algorithm mechanisms to solve optimization and best solution search problems. With a set of specialized classes and a configuration file, any java application can abstract the GA logic.



This package has a collection of readily usable genetic operators for order based genetic algorithm and is implemented using java.



X-GAT (XML-based Genetic Algorithm Toolkit) is a Java framework to optimize problems with Genetic Algorithms (GAs). Differently from other frameworks, X-GAT contains ready-to-use GAs implementations and new features can be easily added.



This tool helps you to reverse engineer UML Sequence Diagram for your java program at runtime. It works well with both complex java programs (that have multiple threads) and J2EE applications deployed on Application Servers.