A Vectorial DEVS Extension for Large Scale System Modeling and Parallel Simulation

In this article we introduce an extension to the Discrete Event System (DEVS) formalism called Vectorial DEVS (VECDEVS) that allows to represent large scale systems in a graphic block diagram way. A pure VECDEVS model basically consist in an array of identical classic DEVSmodels that may differ in their parameters. The interconnection of VECDEVS models with some special classic DEVS models that can handle VECDEVS events allows to easily represent large systems of arbitrary structure. A noticeable feature of this extension is that VECDEVS models can be easily split for parallel simulation. For that purpose, we developed an algorithm that automatically splits VECDEVS models into an arbitrary number of sub-models for parallel simulation. The implementation of VECDEVS and the partitioning algorithm in a DEVS simulation tool is also described and its usage is illustrated through some application examples.Fil: Bergero, Federico. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; ArgentinaFil: Kofman, Ernesto Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; Argentin

A Stand–Alone Quantized State System Solver for Continuous System Simulation

This article introduces a stand-alone implementation of the quantized state system (QSS) integration methods for continuous and hybrid system simulation. QSS methods replace the time discretization of classic numerical integration by the quantization of the state variables. These algorithms lead to discrete event approximations of the original continuous systems and show some advantages over classic numerical integration schemes. For simplicity, most implementations of QSS methods were confined to discrete event simulation engines. The problem is that they were not fully efficient, as they wasted much of the computational load in the discrete event simulation mechanism. The stand-alone QSS solver presented here overcomes this problem, improving in more than one order of magnitude the computation times of the previous discrete event implementations. Besides describing the solver structure and functionality, the article analyzes four different models and compares the performance of the new solver with that of the discrete event implementation, and with that of different classic solvers.Fil: Kofman, Ernesto Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; ArgentinaFil: Fernandez, Joaquin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; Argentin

A novel parallelization technique for DEVS simulation of continuous and hybrid systems.

In this paper, we introduce a novel parallelization technique for Discrete Event System Specification (DEVS) simulation of continuous and hybrid systems. Here, like in most parallel discrete event simulation methodologies, the models are first split into several sub-models which are than concurrently simulated on different processors. In order to avoid the cost of the global synchronization of all processes, the simulation time of each sub-model is locally synchronized in a real-time fashion with a scaled version of physical time, which implicitly synchronizes all sub-models. The new methodology, coined Scaled Real-Time Synchronization (SRTS), does not ensure a perfect synchronization in its implementation. However, under certain conditions, the synchronization error introduced only provokes bounded numerical errors in the simulation results. SRTS uses the same physical time-scaling parameter throughout the entire simulation. We also developed an adaptive version of the methodology (Adaptive-SRTS) where this parameter automatically evolves during the simulation according to the workload. We implemented the SRTS and Adaptive-SRTS techniques in PowerDEVS , a DEVS simulation tool, under a real-time operating system called the Real-Time Application Interface (RTAI) . We tested their performance by simulating three large-scale models, obtaining in all cases a considerable speedup.Fil: Bergero, Federico. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Kofman, Ernesto Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Cellier, François. Swiss Federal Institute Of Technology Zurich. Departament Informatik. Modeling And Simulation Research Group; Suiz

Quantization-based new integration methods for stiff ordinary differential equations

In this paper we introduce new classes of numerical ordinary differential equation (ODE) solvers that base their internal discretization method on state quantization instead of time slicing. These solvers have been coined quantized state system (QSS) simulators. The primary result of the research described in this article is a first-order accurate QSS-based stiff system solver, called the backward QSS (BQSS). The numerical properties of this new algorithm are discussed, and it is shown that this algorithm exhibits properties that make it a potentially attractive alternative to the classical numerical ODE solvers. Some simulation examples illustrate the advantages of this method. As a collateral result, a first-order accurate QSS-based solver designed for solving marginally stable systems is briefly outlined as well. This new method, called the centered QSS (CQSS), is successfully applied to a challenging benchmark problem describing a high-order system that is simultaneously stiff and marginally stable. However, the primary emphasis of this article is on the BQSS method, that is, on a stiff system solver based on state quantization.Fil: Migoni, Gustavo Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Kofman, Ernesto Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Cellier, François. Eidgenössische Technische Hochschule Zürich; Suiz

GNSS-stereo-inertial SLAM for arable farming

The accelerating pace in the automation of agricultural tasks demands highly accurate and robust localization systems for field robots. Simultaneous Localization and Mapping (SLAM) methods inevitably accumulate drift on exploratory trajectories and primarily rely on place revisiting and loop closing to keep a bounded global localization error. Loop closure techniques are significantly challenging in agricultural fields, as the local visual appearance of different views is very similar and might change easily due to weather effects. A suitable alternative in practice is to employ global sensor positioning systems jointly with the rest of the robot sensors. In this paper we propose and implement the fusion of global navigation satellite system (GNSS), stereo views, and inertial measurements for localization purposes. Specifically, we incorporate, in a tightly coupled manner, GNSS measurements into the stereo-inertial ORB-SLAM3 pipeline. We thoroughly evaluate our implementation in the sequences of the Rosario data set, recorded by an autonomous robot in soybean fields, and our own in-house data. Our data includes measurements from a conventional GNSS, rarely included in evaluations of state-of-the-art approaches. We characterize the performance of GNSS-stereo-inertial SLAM in this application case, reporting pose error reductions between 10% and 30% compared to visual-inertial and loosely coupled GNSS-stereo-inertial baselines. In addition to such analysis, we also release the code of our implementation as open source.Comment: This paper has been accepted for publication in Journal of Field Robotics, 202

Quantized State Simulation of Spiking Neural Networks

In this work, we explore the usage of quantized state system (QSS) methods in the simulation of networks of spiking neurons. We compare the simulation results obtained by these discrete-event algorithms with the results of the discrete time methods in use by the neuroscience community. We found that the computational costs of the QSS methods grow almost linearly with the size of the network, while they grows at least quadratically in the discrete time algorithms. We show that this advantage is mainly due to the fact that QSS methods only perform calculations in the components of the system that experience activity. © 2012, Simulation Councils Inc. All rights reserved.Fil: Grinblat, Guillermo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Ahumada, Hernán. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Kofman, Ernesto Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentin

Discrete-Time Modeling of COVID-19 Propagation in Argentina with Explicit Delays

We present a new deterministic discrete-Time compartmental model of COVID-19 that explicitly takes into account relevant delays related to the stages of the disease, its diagnosis and report system, allowing to represent the presence of imported cases. In addition to developing the model equations, we describe an automatic parameter fitting mechanism using official data on the spread of the virus in Argentina. The result consistently reflects the behavior of the disease with respect to characteristic times: latency, infectious period, report of cases (confirmed and dead), and allows for detecting automatically changes in the reproductive number and in the mortality factor. We also analyse the model´s prediction capability and present simulation results assuming different future scenarios. We discuss usage of the model in a closed-loop control scheme, where the explicit presence of delays plays a key role in projecting more realistic dynamics than that of classic continuous-Time models.Fil: Bergonzi, Mariana. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Pecker Marcosig, Ezequiel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires; ArgentinaFil: Kofman, Ernesto Javier. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Castro, Rodrigo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires; Argentin