Generic Pipelined Processor Modeling and High Performance Cycle-Accurate Simulator Generation

Detailed modeling of processors and high performance cycle-accurate simulators are essential for today's hardware and software design. These problems are challenging enough by themselves and have seen many previous research efforts. Addressing both simultaneously is even more challenging, with many existing approaches focusing on one over another. In this paper, we propose the Reduced Colored Petri Net (RCPN) model that has two advantages: first, it offers a very simple and intuitive way of modeling pipelined processors; second, it can generate high performance cycle-accurate simulators. RCPN benefits from all the useful features of Colored Petri Nets without suffering from their exponential growth in complexity. RCPN processor models are very intuitive since they are a mirror image of the processor pipeline block diagram. Furthermore, in our experiments on the generated cycle-accurate simulators for XScale and StrongArm processor models, we achieved an order of magnitude (~15 times) speedup over the popular SimpleScalar ARM simulator.Comment: Submitted on behalf of EDAA (http://www.edaa.com/

Application of artificial neural networks and colored petri nets on earthquake resilient water distribution systems

Water distribution systems are important lifelines and a critical and complex infrastructure of a country. The performance of this system during unexpected rare events is important as it is one of the lifelines that people directly depend on and other factors indirectly impact the economy of a nation. In this thesis a couple of methods that can be used to predict damage and simulate the restoration process of a water distribution system are presented. Contributing to the effort of applying computational tools to infrastructure systems, Artificial Neural Network (ANN) is used to predict the rate of damage in the pipe network during seismic events. Prediction done in this thesis is based on earthquake intensity, peak ground velocity, and pipe size and material type. Further, restoration process of water distribution network in a seismic event is modeled and restoration curves are simulated using colored Petri nets. This dynamic simulation will aid decision makers to adopt the best strategies during disaster management. Prediction of damages, modeling and simulation in conjunction with other disaster reduction methodologies and strategies is expected to be helpful to be more resilient and better prepared for disasters --Abstract, page iv

Analysis of Petri Net Models through Stochastic Differential Equations

It is well known, mainly because of the work of Kurtz, that density dependent Markov chains can be approximated by sets of ordinary differential equations (ODEs) when their indexing parameter grows very large. This approximation cannot capture the stochastic nature of the process and, consequently, it can provide an erroneous view of the behavior of the Markov chain if the indexing parameter is not sufficiently high. Important phenomena that cannot be revealed include non-negligible variance and bi-modal population distributions. A less-known approximation proposed by Kurtz applies stochastic differential equations (SDEs) and provides information about the stochastic nature of the process. In this paper we apply and extend this diffusion approximation to study stochastic Petri nets. We identify a class of nets whose underlying stochastic process is a density dependent Markov chain whose indexing parameter is a multiplicative constant which identifies the population level expressed by the initial marking and we provide means to automatically construct the associated set of SDEs. Since the diffusion approximation of Kurtz considers the process only up to the time when it first exits an open interval, we extend the approximation by a machinery that mimics the behavior of the Markov chain at the boundary and allows thus to apply the approach to a wider set of problems. The resulting process is of the jump-diffusion type. We illustrate by examples that the jump-diffusion approximation which extends to bounded domains can be much more informative than that based on ODEs as it can provide accurate quantity distributions even when they are multi-modal and even for relatively small population levels. Moreover, we show that the method is faster than simulating the original Markov chain

A Review of Building Information Modeling and Simulation as Virtual Representations Under the Digital Twin Concept

Building Information Modeling (BIM) is a highly promising technique for achieving digitalization in the construction industry, widely used in modern construction projects for digitally representing facilities. Nevertheless, retains limitations in terms of representing construction operations. The digital twin concept may potentially overcome these limitations and initiate advanced digital transformation in the construction industry as it has revolutionized the product lifecycle management in the manufacturing industry. This research provides a critical review of applying digital twin in the construction industry. Altogether, 140 papers from related journals and databases were reviewed. The digital aspect of twinning consists of BIM and simulation modeling. These two techniques have been used to create virtual or digital representations of actual buildings and real-world construction processes. However, integrating and applying BIM and simulation modeling according to the digital twin concept remains to be fully studied. Comprehensive evaluations of BIM, simulation modeling, and digital twin will provide a well-defined framework for this research, to identify direction and potential for digital twin in the construction industry, thereby progressing to the next level of digitalization and improvement in construction management practice

On the Use of Queueing Petri Nets for Modeling and Performance Analysis of Distributed Systems

Predictive performance models are used increasingly throughout the phases of the software engineering lifecycle of distributed systems. However, as systems grow in size and complex-ity, building models that accurately capture the different aspects of their behavior becomes a more and more challenging task. The challenge stems from the limited model expressivenes

Modeling and Simulation of Task Allocation with Colored Petri Nets

The task allocation problem is a key element in the solution of several applications from different engineering fields. With the explosion of the amount of information produced by the today Internet-connected solutions, scheduling techniques for the allocation of tasks relying on grids, clusters of computers, or in the cloud computing, is at the core of efficient solutions. The task allocation is an important problem within some branch of the computer sciences and operations research, where it is usually modeled as an optimization of a combinatorial problem with the inconvenience of a state explosion problem. This chapter proposes the modeling of the task allocation problem by the use of Colored Petri nets. The proposed methodology allows the construction of compact models for task scheduling problems. Moreover, a simulation process is possible within the constructed model, which allows the study of some performance aspects of the task allocation problem before any implementation stage

Representing Resources in Petri Net Models: Hardwiring or Soft-coding?

©2011 IEEE. Reprinted, with permission, from : Reggie Davidrajuh; Representing Resources in Petri Net Models : Hardwiring or Soft-coding?, 2011 IEEE International Conference on Service Operations, Logistics, and Informatics (SOLI), 2011; Beijing, China. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Stavanger's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs‐[email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.This paper presents an interesting design problem in developing a new tool for discrete-event dynamic systems (DEDS). A new tool known as GPenSIM was developed for modeling and simulation of DEDS; GPenSIM is based on Petri Nets. The design issue this paper talks about is whether to represent resources in DEDS hardwired as a part of the Petri net structure (which is the widespread practice) or to soft code as common variables in the program code. This paper shows that soft coding resources give benefits such as simpler and skinny models