Faster simulation of (Coloured) Petri nets using parallel computing

International audienceFast simulation, i.e., automatic computation of sequential runs, is widely used to analyse Petri nets. In particular, it enables for quantitative statistical analysis by observing large sets of runs. Moreover, fast simulation may be used to actually run a Petri net model as a (prototype) implementation of a system, in which case such a net would embed fragments of the code of the system. In both these contexts, being able to perform faster simulation is highly desirable. In this paper, we propose a way to accelerate fast simulation by exploiting parallel computing, targeting both the multi-core cpus available nowadays in every laptop or workstation, and larger parallel computers including those with distributed memory (clusters). We design an algorithm to do so and assess in particular its correctness and completeness through its formal modelling as a Petri net whose state space is analysed. We also present a benchmark of a prototype implementation that clearly shows how our algorithm effectively accelerates fast simulation, in particular in the case of large concurrent coloured Petri nets, which is precisely the kind of nets that are usually slow to simulate

Parallelizing Timed Petri Net simulations

The possibility of using parallel processing to accelerate the simulation of Timed Petri Nets (TPN's) was studied. It was recognized that complex system development tools often transform system descriptions into TPN's or TPN-like models, which are then simulated to obtain information about system behavior. Viewed this way, it was important that the parallelization of TPN's be as automatic as possible, to admit the possibility of the parallelization being embedded in the system design tool. Later years of the grant were devoted to examining the problem of joint performance and reliability analysis, to explore whether both types of analysis could be accomplished within a single framework. In this final report, the results of our studies are summarized. We believe that the problem of parallelizing TPN's automatically for MIMD architectures has been almost completely solved for a large and important class of problems. Our initial investigations into joint performance/reliability analysis are two-fold; it was shown that Monte Carlo simulation, with importance sampling, offers promise of joint analysis in the context of a single tool, and methods for the parallel simulation of general Continuous Time Markov Chains, a model framework within which joint performance/reliability models can be cast, were developed. However, very much more work is needed to determine the scope and generality of these approaches. The results obtained in our two studies, future directions for this type of work, and a list of publications are included

Research in progress in applied mathematics, numerical analysis, fluid mechanics, and computer science

This report summarizes research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, fluid mechanics, and computer science during the period October 1, 1993 through March 31, 1994. The major categories of the current ICASE research program are: (1) applied and numerical mathematics, including numerical analysis and algorithm development; (2) theoretical and computational research in fluid mechanics in selected areas of interest to LaRC, including acoustics and combustion; (3) experimental research in transition and turbulence and aerodynamics involving LaRC facilities and scientists; and (4) computer science

Infrastructure for distributed enterprise simulation

Traditional discrete-event simulations employ an inherently sequential algorithm and are run on a single computer. However, the demands of many real-world problems exceed the capabilities of sequential simulation systems. Often the capacity of a computer`s primary memory limits the size of the models that can be handled, and in some cases parallel execution on multiple processors could significantly reduce the simulation time. This paper describes the development of an Infrastructure for Distributed Enterprise Simulation (IDES) - a large-scale portable parallel simulation framework developed to support Sandia National Laboratories` mission in stockpile stewardship. IDES is based on the Breathing-Time-Buckets synchronization protocol, and maps a message-based model of distributed computing onto an object-oriented programming model. IDES is portable across heterogeneous computing architectures, including single-processor systems, networks of workstations and multi-processor computers with shared or distributed memory. The system provides a simple and sufficient application programming interface that can be used by scientists to quickly model large-scale, complex enterprise systems. In the background and without involving the user, IDES is capable of making dynamic use of idle processing power available throughout the enterprise network. 16 refs., 14 figs

Application Driven MOdels for Resource Management in Cloud Environments

El despliegue y la ejecución de aplicaciones de gran escala en sistemas distribuidos con unos parametros de Calidad de Servicio adecuados necesita gestionar de manera eficiente los recursos computacionales. Para desacoplar los requirimientos funcionales y los no funcionales (u operacionales) de dichas aplicaciones, se puede distinguir dos niveles de abstracción: i) el nivel funcional, que contempla aquellos requerimientos relacionados con funcionalidades de la aplicación; y ii) el nivel operacional, que depende del sistema distribuido donde se despliegue y garantizará aquellos parámetros relacionados con la Calidad del Servicio, disponibilidad, tolerancia a fallos y coste económico, entre otros. De entre las diferentes alternativas del nivel operacional, en la presente tesis se contempla un entorno cloud basado en la virtualización de contenedores, como puede ofrecer Kubernetes.El uso de modelos para el diseño de aplicaciones en ambos niveles permite garantizar que dichos requerimientos sean satisfechos. Según la complejidad del modelo que describa la aplicación, o el conocimiento que el nivel operacional tenga de ella, se diferencian tres tipos de aplicaciones: i) aplicaciones dirigidas por el modelo, como es el caso de la simulación de eventos discretos, donde el propio modelo, por ejemplo Redes de Petri de Alto Nivel, describen la aplicación; ii) aplicaciones dirigidas por los datos, como es el caso de la ejecución de analíticas sobre Data Stream; y iii) aplicaciones dirigidas por el sistema, donde el nivel operacional rige el despliegue al considerarlas como una caja negra.En la presente tesis doctoral, se propone el uso de un scheduler específico para cada tipo de aplicación y modelo, con ejemplos concretos, de manera que el cliente de la infraestructura pueda utilizar información del modelo descriptivo y del modelo operacional. Esta solución permite rellenar el hueco conceptual entre ambos niveles. De esta manera, se proponen diferentes métodos y técnicas para desplegar diferentes aplicaciones: una simulación de un sistema de Vehículos Eléctricos descrita a través de Redes de Petri; procesado de algoritmos sobre un grafo que llega siguiendo el paradigma Data Stream; y el propio sistema operacional como sujeto de estudio.En este último caso de estudio, se ha analizado cómo determinados parámetros del nivel operacional (por ejemplo, la agrupación de contenedores, o la compartición de recursos entre contenedores alojados en una misma máquina) tienen un impacto en las prestaciones. Para analizar dicho impacto, se propone un modelo formal de una infrastructura operacional concreta (Kubernetes). Por último, se propone una metodología para construir índices de interferencia para caracterizar aplicaciones y estimar la degradación de prestaciones incurrida cuando dos contenedores son desplegados y ejecutados juntos. Estos índices modelan cómo los recursos del nivel operacional son usados por las applicaciones. Esto supone que el nivel operacional maneja información cercana a la aplicación y le permite tomar mejores decisiones de despliegue y distribución.<br /

Automated Parallelization of Timed Petri-Net Simulations

Timed Petri-nets are used to model numerous types of large complex systems, especially computer architectures and communication networks. While formal analysis of such models is sometimes possible, discrete-event simulation remains the most general technique available for assessing the model&apos;s behavior. However, simulation&apos;s computational requirements can be massive, especially on the large complex models that defeat analytic methods. One way of meeting these requirements is by executing the simulation on a parallel machine. This paper describes simple techniques for the automated parallelization of timed Petri-net simulations. We address both the issue of processor synchronization, as well as the automated mapping, static and dynamic, of the Petri-net to the parallel architecture. As part of this effort we describe a new mapping algorithm, one that also applies to more general parallel computations. We establish analytic properties of the solution produced by the algorithm, including ..

Méthodes systémiques d'analyse des données de simulation de modèles de voies de signalisation cellulaire

Les réseaux de pétri, un outil de modélisation polyvalent -- Une approche systémique en biologie moléculaire : le génie à la rencontre de la biologie -- Démarche de l'ensemble du travail de recherche et organisation générale du document -- Functional abstraction and spectral representation to visualize the system dynamics and the information flux in a biochemical model -- Petri net-based visualization of signal transduction pathway simulations -- Petri net-based method for the analysis of the dynamics of signal propagation in signaling pathways

Distributed Simulation of High-Level Algebraic Petri Nets

In the field of Petri nets, simulation is an essential tool to validate and evaluate models. Conventional simulation techniques, designed for their use in sequential computers, are too slow if the system to simulate is large or complex. The aim of this work is to search for techniques to accelerate simulations exploiting the parallelism available in current, commercial multicomputers, and to use these techniques to study a class of Petri nets called high-level algebraic nets. These nets exploit the rich theory of algebraic specifications for high-level Petri nets: Petri nets gain a great deal of modelling power by representing dynamically changing items as structured tokens whereas algebraic specifications turned out to be an adequate and flexible instrument for handling structured items. In this work we focus on ECATNets (Extended Concurrent Algebraic Term Nets) whose most distinctive feature is their semantics which is defined in terms of rewriting logic. Nevertheless, ECATNets have two drawbacks: the occultation of the aspect of time and a bad exploitation of the parallelism inherent in the models. Three distributed simulation techniques have been considered: asynchronous conservative, asynchronous optimistic and synchronous. These algorithms have been implemented in a multicomputer environment: a network of workstations. The influence that factors such as the characteristics of the simulated models, the organisation of the simulators and the characteristics of the target multicomputer have in the performance of the simulations have been measured and characterised. It is concluded that synchronous distributed simulation techniques are not suitable for the considered kind of models, although they may provide good performance in other environments. Conservative and optimistic distributed simulation techniques perform well, specially if the model to simulate is complex or large - precisely the worst case for traditional, sequential simulators. This way, studies previously considered as unrealisable, due to their exceedingly high computational cost, can be performed in reasonable times. Additionally, the spectrum of possibilities of using multicomputers can be broadened to execute more than numeric applications