A Genetic Algorithm to Study a P3 Non-trivial Collective Task

Here we report new results of a genetic algorithm (GA) used to evolve one dimensional Cellular Automata (CA) to perform a P3 non-trivial collective behavior task. For this task the goal is to find a CA rule that reaches one final configuration in which the concentration of active cells oscillates among three different values. Though the majority of the best evolved rules belong to the II Wolfram’s class, the GA also finds rules of the III and IV classes. The different computational mechanisms used by each rule to synchronize the entire lattice are analyzed by means of the spatio-temporal patterns generated

Developing Efficient Discrete Simulations on Multicore and GPU Architectures

In this paper we show how to efficiently implement parallel discrete simulations on multicoreandGPUarchitecturesthrougharealexampleofanapplication: acellularautomatamodel of laser dynamics. We describe the techniques employed to build and optimize the implementations using OpenMP and CUDA frameworks. We have evaluated the performance on two different hardware platforms that represent different target market segments: high-end platforms for scientific computing, using an Intel Xeon Platinum 8259CL server with 48 cores, and also an NVIDIA Tesla V100GPU,bothrunningonAmazonWebServer(AWS)Cloud;and on a consumer-oriented platform, using an Intel Core i9 9900k CPU and an NVIDIA GeForce GTX 1050 TI GPU. Performance results were compared and analyzed in detail. We show that excellent performance and scalability can be obtained in both platforms, and we extract some important issues that imply a performance degradation for them. We also found that current multicore CPUs with large core numbers can bring a performance very near to that of GPUs, and even identical in some cases.Ministerio de Economía, Industria y Competitividad, Gobierno de España (MINECO), and the Agencia Estatal de Investigación (AEI) of Spain, cofinanced by FEDER funds (EU) TIN2017-89842

Cellular automata and cluster computing: An application to the simulation of laser dynamics

Firstly, the application of a cellular automata (CA) model to simulate the dynamics of lasers is reviewed. With this kind of model, the macroscopic properties of the laser system emerge as a cooperative phenomenon from elementary components locally inter-acting under simple rules. Secondly, a parallel implementation of this kind of model for distributed-memory parallel computers is presented. Performance and scalability of this parallel implementation running on a computer cluster are analyzed, giving very satisfac-tory results. This confirms the feasibility of running large 3D simulations— unaffordable on an individual machine—on computer clusters, in order to simulate specific real laser systems.Ministerio de Educación y Ciencia TIN2005-08818-C04-0

Simulation of the Dynamics of Pulsed Pumped Lasers Based on Cellular Automata

Laser dynamics is traditionally modeled using differential equations. Recently, a new approach has been introduced in which laser dynamics is modeled using two-dimensional Cellular Automata (CA). In this work, we study a modified version of this model in order to simulate the dynamics of pulsed pumped lasers. The results of the CA approach are in qualitative agreement with the outcome of the numerical integration of the laser rate equations

Activity Recognition Using Hybrid Generative/Discriminative Models on Home Environments Using Binary Sensors

Activities of daily living are good indicators of elderly health status, and activity recognition in smart environments is a well-known problem that has been previously addressed by several studies. In this paper, we describe the use of two powerful machine learning schemes, ANN (Artificial Neural Network) and SVM (Support Vector Machines), within the framework of HMM (Hidden Markov Model) in order to tackle the task of activity recognition in a home setting. The output scores of the discriminative models, after processing, are used as observation probabilities of the hybrid approach. We evaluate our approach by comparing these hybrid models with other classical activity recognition methods using five real datasets. We show how the hybrid models achieve significantly better recognition performance, with significance level p<0 : 0 5, proving that the hybrid approach is better suited for the addressed domain.This work has been supported by the Ambient Assisted Living Programme (Joint Initiative by the European Commission and EU Member States) under the Trainutri (Training and nutrition senior social platform) Project (AAL-2009-2-129) and by the Spanish Government under i-Support (Intelligent Agent Based Driver Decision Support) Project (TRA2011-29454-C03-03)

Cellular automaton model for the simulation of laser dynamics

The classical modeling approach for laser study relies on the differential equations. In this paper, a cellular automaton model is proposed as an alternative for the simulation of population dynamics. Even though the model is simplified it captures the essence of laser phenomenology: (i) there is a threshold pumping rate that depends inversely on the decaying lifetime of the atoms and the photons; and (ii) depending on these lifetimes and on the pumping rate, a constant or an oscillatory behavior can be observed. More complex behaviors such as spiking and pattern formation can also be studied with the cellular automaton model

Computational simulation of laser dynamics as a cooperative phenomenon

The different kinds of behavior exhibited by the system in a laser dynamics simulation using a cellular automata model are analyzed. Three distinct types of behavior have been found: laser constant operation, laser spiking and a complex behavior showing irregular oscillations. In the last case, the power spectrum follows a power law of the type 1/f − with exponent close to = 2. In the laser spiking regime, the dependence of the decay rate of the oscillations is found to be in good agreement with the predictions of the theoretical laser rate equations and the experimental phenomenology. In our model the system components evolve under local rules which reproduce the physics of the laser system at the microscopic level, and the laser properties appear as cooperative emergent phenomena associated to these rules

Distribución potencial del caimán del Orinoco (Crocodylus intermedius Graves 1819) en la Orinoquia colombiana y venezolana

Crocodylus intermedius (Graves 1819), commonly known at the Orinoco Crocodile, is an endemic species of the Orinoco River Basin that occurs in Colombia and Venezuela. Within the Neotropical Crocodylia, it is considered the most endangered species, listed as Critically Endangered. The use of potential distribution models is an important tool in biogeographical analysis for the conservation of rare and endangered species threatened with extinction. For this reason in this study we determined the potential distribution range for the Orinoco Crocodile using the maximum entropy model Maxent. Initial data to calculate potential range included 654 records of known occurrence for this species, 20 environmental and one limnological variable. The distribution of the Orinoco Crocodile was found to be correlated with precipitation climate variables and the type of water (white, clear or black).Crocodylus intermedius (Graves 1819) comúnmente denominado caimán llanero o caimán del Orinoco, es una especie endémica de la cuenca del Orinoco, con distribución en Colombia y Venezuela. Dentro de los Crocodylia del Neotrópico, es considerada la especie más amenazada y se encuentra en la categoría de Peligro Crítico. El uso de modelos de distribución potencial en el análisis biogeográfico es una herramienta importante para la conservación de especies raras o en peligro de extinción. Es por ello que en este trabajo se buscó determinar la distribución potencial del caimán llanero mediante el uso del algoritmo de maximización de la entropía, Maxent. Como información de entrada se utilizaron 654 registros de presencia de la especie y 20 variables ambientales incluyendo una limnológica. Se concluye que la distribución del caimán llanero está relacionada con la precipitación y con el tipo de aguas (blancas, claras y negras) presentes en la cuenca