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1981
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SIMULA language has been designed as a general-purpose programming tool and is particularly offered for describing and efficiently simulating large-scale systems. Such simulation models are usually characterized by inherent parallelism, which reflects corresponding activities of the system. This kind of natural parallelism remains unexploited by the implementation of the SIMULA language in a uniprocessor machine. We have critically assessed SIMULA, and we present a scheme that aims towards implementing ...
Computer Languages, 1984
SIMULA is a powerful general purpose programming language which includes sophisticated simulation facilities. However, unfamiliarity with the language concepts and the restrictive amount of literature covering the language structure have led to the development of an inertia which has prevented many skilful programmers from using it. This paper presents an attempt towards introducing the concepts of simplicity and expressive power inherent in SIMULA to a wider audience.
IEEE Design & Test of Computers, 2000
COMPUTER SIMULATION is wide ly used today in practically all major areas of science, engineering, and management. As computers become more powerful and their use expands, the need to simulate larger and more complex systems in reasonable computing times b e comes more important. Though s e quential simulation of complex systems requires considerable CPU time, parallel simulation can significantly reduce this time. Neverthe less, simulating complex systems on highspeed computers with multiprocessor capabilities is not a trivial task.
Annals of Operations Research, 1994
This paper surveys topics that presently define the state of the art in parallel simulation. Included in the tutorial are discussions on new protocols, mathematical performance analysis, time parallelism, hardware support for parallel simulation, load balancing algorithms, and dynamic memory management for optimistic snchronization.
2010
This paper presents how the DUP System, a straightforward POSIX-compatible framework that enables programminglanguage-agnostic parallel and distributed stream processing, can be used to facilitate parallel and distributed simulations. Specifically, we describe two ways of using DUP to utilize available resources for efficient simulation: (1) a straightforward technique for parallelizing multiple runs of an existing simulation program with minimal changes, and (2) FiDES, a Discrete-Event Simulation (DES) framework built atop DUP that provides a simple, yet powerful, means of implementing a parallel and/or distributed DES. We then describe a toolset for profiling, debugging and visualization that aids the development of DUP simulations. To support these claims, we present various performance benchmarks that collectively demonstrate how DUP and FiDES can make highperformance simulation accessible to everyone.
Information Sciences, 1996
This paper presents the development of a parallel object-oriented language which is an extension of C++, called C ++//. C ++// offers reusability, flexibility and extensibility in concurrent programming through a set of language primitives (indeed a Meta-Object Protocol), independent of any parallel paradigm. It permits us to build libraries of nearly all concurrent programming models. One of them, presented here, is an MIMD model based on data-flow synchronizations (wait-by-necessity). C++// runtime main concern is versatility so its implementation is in fact an interface to any low-level runtime support.
2004
The Following survey aims at identifying some of th e prominent researches in the filed of modeling and simulation, by means of their published papers. The selected researches are Richard Fujimoto, David M.Nicol, and Philip A.W ilsey. The following document will attempt to summarize some of their latest works in the field of modelling and simulation, as for the selection of the topics it was based accord ing to their relativity to our interest in parallel simulation of complex networks.
Software: Practice and Experience, 2005
Discrete event simulators are important scientific tools and their efficient design and execution is the subject of much research. In this paper, we propose a new approach for constructing simulators that leverages virtual machines and combines advantages from the traditional systems-based and language-based simulator designs. We introduce JiST, a Java-based simulation system that executes discrete event simulations both efficiently and transparently by embedding simulation semantics directly into the Java execution model. The system provides standard benefits that the modern Java runtime affords. In addition, JiST is efficient, out-performing existing highly optimized simulation runtimes.
Simulation Modelling Practice and Theory, 2014
Recent advances in computing architectures and networking are bringing parallel computing systems to the masses so increasing the number of potential users of these kinds of systems. In particular, two important technological evolutions are happening at the ends of the computing spectrum: at the "small" scale, processors now include an increasing number of independent execution units (cores), at the point that a mere CPU can be considered a parallel shared-memory computer; at the "large" scale, the Cloud Computing paradigm allows applications to scale by offering resources from a large pool on a pay-as-you-go model. Multi-core processors and Clouds both require applications to be suitably modified to take advantage of the features they provide. Despite laying at the extreme of the computing architecture spectrum-multi-core processors being at the small scale, and Clouds being at the large scale-they share an important common trait: both are specific forms of parallel/distributed architectures. As such, they present to the developers well known problems of synchronization, communication, workload distribution, and so on. Is parallel and distributed simulation ready for these challenges? In this paper, we analyze the state of the art of parallel and distributed simulation techniques, and assess their applicability to multi-core architectures or Clouds. It turns out that most of the current approaches exhibit limitations in terms of usability and adaptivity which may hinder their application to these new computing architectures. We propose an adaptive simulation mechanism, based on the multi-agent system paradigm, to partially address some of those limitations. While it is unlikely that a single approach will work well on both settings above, we argue that the proposed adaptive mechanism has useful features which make it attractive both in a multi-core processor and in a Cloud system. These features include the ability to reduce communication costs by migrating simulation components, and the support for adding (or removing) nodes to the execution architecture at runtime. We will also show that, with the help of an additional support layer, parallel and distributed simulations can be executed on top of unreliable resources.
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