Search Results for "parallel genetic"

Mendel’s Accountant is a biologically realistic, forward-time, parallel, numerical simulation program which models genetic change within a population, as affected by mutation and selection.

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.

Airfoil optimization using the highly-regarded Xfoil engine for aerodynamic calculations. Starting with a seed airfoil, Xoptfoil uses particle swarm, genetic algorithm and direct search methodologies to perturb the geometry and maximize performance. The user selects a number of operating points over which to optimize, desired constraints, and the optimizer does the rest.

popt4jlib is an open-source parallel optimization library for the Java programming language supporting both shared memory and distributed message passing models. Implements a number of meta-heuristic algorithms for Non-Linear Programming, including Genetic Algorithms, Differential Evolution, Evolutionary Algorithms, Simulated Annealing, Particle Swarm Optimization, Firefly Algorithm, Monte-Carlo Search, Local Search algorithms, Gradient-Descent-based algorithms, as well as some well-known network flow and other graph algorithms. ...

...Carbon catabolite repression (CCR) is the main mechanism controlling carbohydrate uptake in bacteria, and therefore also controlling whether or not different carbon sources are metabolized in parallel or sequentially. Although described as a paradigm of the regulation of bacterial metabolism, the underlying mechanisms remain controversial. The models in the ensemble can be categorized according to regulatory, stoichiometric, and physiological constraints and differ from each other on only a single aspect. We distinguish four groups of models: (1) flux balance models that only define reaction kinetics for substrate uptake and by-product excretion, (2) kinetic models without and (3) kinetic models with regulation on the metabolic and/or genetic level, and (4) resource allocation models.

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...

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...

Parallel Reinforcement Evolutionary Artificial Neural Networks (PREANN) is a framework of flexible multi-layer ANN's with reinforcement learning based on genetic algorithms and a parallel implementation (using XMM registers and NVIDIA's CUDA).

PGAF provides a framework tuned, user-specific genetic algorithms by handling I/O, UI, and parallelism. It is designed for optimizing functions that take a "very long time" to evaluate.

IU parallel fastDNAml is a program that infers evolutionary histories from genetic sequences, modified and extended from the serial version of fastDNAml to run in parallel on heterogeneous and widely distributed systems.

The Distributed Genetic Programming Framework is a scalable Java genetic programming environment. It comes with an optional specialization for evolving assembler-syntax algorithms. The evolution can be performed in parallel in any computer network.