24 research outputs found
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
Performance Evaluation of RAM-Based Implementation of Finite State Machines in FPGAs
This paper presents a study of performance of
RAM-based implementations in FPGAs of Finite State Machines
(FSMs). The influence of the FSM characteristics on speed and
area has been studied, taking into account the particular features
of different FPGA families, like the size of LUTs, the size of
memory blocks, the number of embedded multiplexer levels and
the specific decoding logic for distributed RAM. Our study can be
useful for efficiently implementing FPGA-based state machines
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
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
Performance Analysis of a Parallel Discrete Model for the Simulation of Laser Dynamics
This paper presents an analysis on the performance of
a parallel implementation of a discrete model of laser dynamics,
which is based on cellular automata. The performance
of a 2D parallel version of the model is studied as
a rst step to test the feasibility of a parallel 3D version,
which is needed to simulate speci c laser systems. The 3D
version will have to run on a parallel computer due to its
runtime and memory requirements. The model has been implemented
on a Beowulf Cluster using the message passing
paradigm. The parallel implementation is found to exhibit
a good speedup, allowing us to run realistic simulations of
laser systems on clusters of workstations, which could not
be afforded on an individual machine due to the extensive
runtime and memory size needed.Ministerio de Educación y Ciencia TIC2002-04498-C05-0
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
Control of Bloat in Genetic Programming by Means of the Island Model
This paper presents a new proposal for reducing bloat in Genetic
Programming. This proposal is based in a well-known parallel evolutionary
model: the island model. We firstly describe the theoretical motivation for this
new approach to the bloat problem, and then we present a set of experiments
that gives us evidence of the findings extracted from the theory. The experiments
have been performed on a representative problem extracted from the GP
field: the even parity 5 problem. We analyse the evolution of bloat employing
different settings for the parameters employed. The conclusion is that the Island
Model helps to prevent the bloat phenomenon
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
A Cellular Automata Agent-Based Hybrid Simulation Tool to Analyze the Deployment of Electric Vehicle Charging Stations
We present a hybrid model combining cellular automata (CA) and agent-based modeling
(ABM) to analyze the deployment of electric vehicle charging stations through microscopic traffic
simulations. This model is implemented in a simulation tool called SIMTRAVEL, which allows
combining electric vehicles (EVs) and internal combustion engine vehicles (ICEVs) that navigate in a
city composed of streets, avenues, intersections, roundabouts, and including charging stations (CSs).
Each EV is modeled as an agent that incorporates complex behaviors, such as decisions about the
route to destination or CS, when to drive to a CS, or which CS to choose. We studied three different
CS arrangements for a synthetic city: a single large central CS, four medium sized distributed CSs or
multiple small distributed CSs, with diverse amounts of traffic and proportions of EVs. The simulator
output is found to be robust and meaningful and allows one to extract a first useful conclusion: traffic
conditions that create bottlenecks around the CSs play a crucial role, leading to a deadlock in the city
when the traffic density is above a certain critical level. Our results show that the best disposition
is a distributed network, but it is fundamental to introduce smart routing measures to balance the
distribution of EVs among CSs.Ministerio de Ciencia e Innovación TIN2017-89842PMinisterio de Ciencia e Innovación PID2019-110455GB-I0