28,139 research outputs found
MultiVeStA: Statistical Model Checking for Discrete Event Simulators
The modeling, analysis and performance evaluation of large-scale systems are difficult tasks. Due to the size and complexity of the considered systems, an approach typically followed by engineers consists in performing simulations of systems models to obtain statistical estimations of quantitative properties. Similarly, a technique used by computer scientists working on quantitative analysis is Statistical Model Checking (SMC), where rigorous mathematical languages (typically logics) are used to express systems properties of interest. Such properties can then be automatically estimated by tools performing simulations of the model at hand. These property specifications languages, often not popular among engineers, provide a formal, compact and elegant way to express systems properties without needing to hard-code them in the model definition. This paper presents MultiVeStA, a statistical analysis tool which can be easily integrated with existing discrete event simulators, enriching them with efficient distributed statistical analysis and SMC capabilities
Simulation modelling and visualisation: toolkits for building artificial worlds
Simulations users at all levels make heavy use of compute resources to drive computational
simulations for greatly varying applications areas of research using different simulation
paradigms. Simulations are implemented in many software forms, ranging from highly standardised
and general models that run in proprietary software packages to ad hoc hand-crafted
simulations codes for very specific applications. Visualisation of the workings or results of a
simulation is another highly valuable capability for simulation developers and practitioners.
There are many different software libraries and methods available for creating a visualisation
layer for simulations, and it is often a difficult and time-consuming process to assemble a
toolkit of these libraries and other resources that best suits a particular simulation model. We
present here a break-down of the main simulation paradigms, and discuss differing toolkits and
approaches that different researchers have taken to tackle coupled simulation and visualisation
in each paradigm
A General Simulation Framework for Supply Chain Modeling: State of the Art and Case Study
Nowadays there is a large availability of discrete event simulation software
that can be easily used in different domains: from industry to supply chain,
from healthcare to business management, from training to complex systems
design. Simulation engines of commercial discrete event simulation software use
specific rules and logics for simulation time and events management.
Difficulties and limitations come up when commercial discrete event simulation
software are used for modeling complex real world-systems (i.e. supply chains,
industrial plants). The objective of this paper is twofold: first a state of
the art on commercial discrete event simulation software and an overview on
discrete event simulation models development by using general purpose
programming languages are presented; then a Supply Chain Order Performance
Simulator (SCOPS, developed in C++) for investigating the inventory management
problem along the supply chain under different supply chain scenarios is
proposed to readers.Comment: International Journal of Computer Science Issues online at
http://ijcsi.org/articles/A-General-Simulation-Framework-for-Supply-Chain-Modeling-State-of-the-Art-and-Case-Study.ph
Simulating Distributed Systems
The simulation framework developed within the "Models of Networked Analysis at Regional Centers" (MONARC) project as a design and optimization tool for large scale distributed systems is presented. The goals are to provide a realistic simulation of distributed computing systems, customized for specific physics data processing tasks and to offer a flexible and dynamic environment to evaluate the performance of a range of possible distributed computing architectures. A detailed simulation of a large system, the CMS High Level Trigger (HLT) production farm, is also presented
One-dimensional collision carts computer model and its design ideas for productive experiential learning
We develop an Easy Java Simulation (EJS) model for students to experience the
physics of idealized one-dimensional collision carts. The physics model is
described and simulated by both continuous dynamics and discrete transition
during collision. In the field of designing computer simulations, we discuss
briefly three pedagogical considerations such as 1) consistent simulation world
view with pen paper representation, 2) data table, scientific graphs and
symbolic mathematical representations for ease of data collection and multiple
representational visualizations and 3) game for simple concept testing that can
further support learning. We also suggest using physical world setup to be
augmented complimentary with simulation while highlighting three advantages of
real collision carts equipment like tacit 3D experience, random errors in
measurement and conceptual significance of conservation of momentum applied to
just before and after collision. General feedback from the students has been
relatively positive, and we hope teachers will find the simulation useful in
their own classes. 2015 Resources added:
http://iwant2study.org/ospsg/index.php/interactive-resources/physics/02-newtonian-mechanics/02-dynamics/46-one-dimension-collision-js-model
http://iwant2study.org/ospsg/index.php/interactive-resources/physics/02-newtonian-mechanics/02-dynamics/195-elastic-collisionComment: 6 pages, 8 figures, 1 table, 1 L. K. Wee, Physics Education 47 (3),
301 (2012); ISSN 0031-912
RELEASE: A High-level Paradigm for Reliable Large-scale Server Software
Erlang is a functional language with a much-emulated model for building reliable distributed systems. This paper outlines the RELEASE project, and describes the progress in the first six months. The project aim is to scale the Erlang’s radical concurrency-oriented programming paradigm to build reliable general-purpose software, such as server-based systems, on massively parallel machines. Currently Erlang has inherently scalable computation and reliability models, but in practice scalability is constrained by aspects of the language and virtual machine. We are working at three levels to address these challenges: evolving the Erlang virtual machine so that it can work effectively on large scale multicore systems; evolving the language to Scalable Distributed (SD) Erlang; developing a scalable Erlang infrastructure to integrate multiple, heterogeneous clusters. We are also developing state of the art tools that allow programmers to understand the behaviour of massively parallel SD Erlang programs. We will demonstrate the effectiveness of the RELEASE approach using demonstrators and two large case studies on a Blue Gene
RELEASE: A High-level Paradigm for Reliable Large-scale Server Software
Erlang is a functional language with a much-emulated model for building reliable distributed systems. This paper outlines the RELEASE project, and describes the progress in the rst six months. The project aim is to scale the Erlang's radical concurrency-oriented programming paradigm to build reliable general-purpose software, such as server-based systems, on massively parallel machines. Currently Erlang has inherently scalable computation and reliability models, but in practice scalability is constrained by aspects of the language and virtual machine. We are working at three levels to address these challenges: evolving the Erlang virtual machine so that it can work effectively on large scale multicore systems; evolving the language to Scalable Distributed (SD) Erlang; developing a scalable Erlang infrastructure to integrate multiple, heterogeneous clusters. We are also developing state of the art tools that allow programmers to understand the behaviour of massively parallel SD Erlang programs. We will demonstrate the e ectiveness of the RELEASE approach using demonstrators and two large case studies on a Blue Gene
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