| Liophant_Simulation_Club An international working group of professional simulationists and students dedicated to simulation projects, tools and methodology. |
| List_of_Queueing_Theory_Software List of Queueing Theory Software, including useful simulation tools. The list was compiled by Dr. Myron Hlynka of the University of Windsor, who welcomes any additions to the list. |
| Machine_Simulation_Software Simulation software to emulate products or machinery for the purpose of increasing sales, advanced service, maintenance, and training. |
| MadMax_Optics,_Inc_ Simulation environment for the optoelectronics industry that provides the rapid solution of Maxwell's equations in structures that have been considered too complex for direct simulation. |
| MathCore_AB_-_Makers_of_MathModelica MathModelica marries the intuitive interface and advanced display capabilities of Wolfram Research's Mathematica and the simple, flexible graphical editing tools of Microsoft Visio with the computatio |
| The_MathWorks Developers of MATLAB, Simulink and Stateflow. Offers products for data analysis, visualization, application development, simulation, design, and code generation. |
| McLeod_Institute_-_Mexico Research and application of simulation software and methodology for discrete event and continuous system simulation, queuing models, bond graphs, signal flow graphs, animation in 3D scenarios, and tra |
| MC-SET_Monte_Carlo_simulation_of__electron_trajectories DLM Enterprises develops Monte-Carlo simulation software dealing with electron trajectories for conditions normally used in Scanning and Transmission (SEM, TEM, STEM, EPMA) Electron Microscopy. |
| Medical_Information_Systems Scientific software for end-users and developers aimed at pharmacokinetic-pharmacodynamic applications. |
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| A_Modeling,_Simulation_and_Control_System_Software___SYMBOLS_2000 A modeling tool for dynamic systems using bond graph(bondgraph), iconic and block diagrams, and equation models. Online simulation with event handlers. Download a free full-working demo now with sub-m |
| Multi-domain_system-level_simulation_modeling_platform MLDesigner is a multi-domain simulation modeling tool with hierarchical block diagrams, C++ primitives, TckTk programming and both dynamic and batch execution. Free full-function evaluation downloads. |
| Neosimulation_Engineering Advanced neural network tools and expertise for simulating physical system behavior. Applications include elastomeric components, biomechanical systems, fluid dynamics, and electromagnetics. |
| _Net-based_Simulation_&_Modeling_Consultants Highpoint Software Systems, LLC uses modern software engineering techniques to provide simulation services. |
| Notes_about_network_simulators The aim of this compilation is to overview some of the simulators currently available. |
| NovaSim_simulation_products,_training_and_consulting We can help you with all of your simulation project needs. Let our experience and attention to detail help you with your next project. |
| OMNeT++ OMNeT++ is an open-source, component-based simulation package designed for modeling communication networks, multi-processors and other distributed systems. It offers a large C++ simulation class libra |
| Opal-RT__Open_Scalable_Real-Time_Simulation_&_Control Tools and services to accelerate control system engineering, modeling and simulation software products. |
| OpEMCSS Graphical discrete event simulation library OpEMCSS and associated draft textbook is available for evaluation. |
| Open_Dynamics_Engine ODE is a free library for simulating rigid body dynamics (e.g. ground vehicles, legged creatures, and motion in VR environments). |
| OpenTrack_-_Simulation_of_Railway_Networks OpenTrack is a railway simulation tool developed at the Swiss Federal Institute of Technology. It is a catalyst for practical economic solutions to complex railway technology problems. |
| Operations_Research_/_Management_Science_Today_Resource_Directory The premier buyer's guide for operations research, management science professionals seeking software and consulting solutions. |
| Pathfinder_Systems Simulation, Neural Nets serving simulation of human behavior, combination of virtual and live images, augmented reality, high-altitude long-endurance unmanned air vehicles. |
| pedsim A Modular, Distributed Pedestrian Crowd Simulation System. |
| Pitch_software_for_the_High_Level_Architecture The High Level Architecture (HLA IEEE 1516) is the latest standard for connecting simulation systems. Pitch's website contains descriptions of the standard as well as software supporting it, both comm |
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| Pore-Cor A three-dimensional pore network model which allows the study of the properties of pore-fluids in meso- and macro-porous solids, such as catalysts, soil, sandstone and paper coatings. |
| Power_Tools_for_Visualization_and_Decision-Making Remarks on simulation as a powerful tool for imagining new systems and allowing scientists to both quantify and observe their behavior. |
| Production_Modeling_Corporation_(PMC) PMC is a simulation and scheduling services company with expertise in applying simulation and scheduling in manufacturing and other industries. PMC also provides technical staffing in simulation and i |
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| Promodel_Corporation Manufacturing, medical, and service simulation modeling. |
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| QCADesigner Quantum-dot cellular automata simulator and design layout tool. QCADesigner is capable of simulation with millions of cells. Available for Linux, mac OS X, and SPARC Solaris and is free to download. |
| QuantumOctave QuantumOctave is a set of GNU Octave functions for doing quick-and-dirty simulations of quantum computers and - in general - quantum systems. |
| Raczynski_Consulting Training, consulting, articles, and software downloads representing Dr. Stanislaw Raczynski's work. |
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JiST / SWANS
Java in Simulation Time / Scalable Wireless Ad hoc Network Simulator
JiST is a high-performance discrete event simulation engine that runs over
a standard Java virtual machine. It is a prototype of a new general-purpose
approach to building discrete event simulators, called virtual
machine-based simulation, that unifies the traditional systems and
language-based simulator designs. The resulting simulation platform is
surprisingly efficient. It out-performs existing highly optimized simulation
runtimes both in time and memory consumption. For example, JiST has twice
the raw event throughput of the highly optimized, C-based Parsec engine, and supports
process-oriented simulation using a fraction of the memory.
The JiST approach is also inherently flexible, capable of transparently
performing important cross-cutting program transformations and optimizations.
This transparency is a key benefit: simulation code that runs on JiST need not
be written in a domain-specific language invented specifically for writing
simulations, nor need it be littered with special-purpose system calls and
call-backs to support runtime simulation functionality. Instead, JiST converts
an existing virtual machine into a simulation platform, by embedding
simulation time semantics at the byte-code level. Thus, JiST simulations are
written in Java, compiled using a regular Java compiler, and run over a
standard, unmodified virtual machine.
The following tables list some JiST time and space micro-benchmark
results. For a detailed explanation and for further information, please refer
to the JiST user guide and other online documentation.
Event throughput
Memory footprint
5 million events
time (sec)
vs. baseline
vs. JiST
baseline
0.738
1.00x
0.76x
JiST
0.970
1.31x
1.00x
Parsec
1.907
2.59x
1.97x
ns2-C
3.260
4.42x
3.36x
GloMoSim
9.539
12.93x
9.84x
ns2-Tcl
76.558
103.81x
78.97x
memory
per entity
per event
10K node sim.
JiST
36B
36B
21MB
GloMoSim
36B
64B
35MB
ns2
544B
40B *
74MB
Parsec
28536B
64B
2885MB
SWANS is a scalable wireless network simulator built atop the JiST
platform. It was created primarily because existing network simulation tools
are not sufficient for current research needs, and its performance serves as a
validation of the virtual machine-based approach to simulator construction.
SWANS is organized as independent software components that can be composed to
form complete wireless network or sensor network configurations. Its
capabilities are similar to ns2 and
GloMoSim, but is able
to simulate much larger networks. SWANS leverages the JiST design to acheive
high simulation throughput, save memory, and run standard Java network
applications over simulated networks. In addition, SWANS implements a data
structure, called hierarchical binning, for efficient computation of
signal propagation.
The following table lists some SWANS time and space macro-benchmark
results running simulations of a beaconing node discovery protocol. SWANS can
simulate networks that are one or two order of magnitude larger than what is
possible with GloMoSim and ns2, respectively, using the same amount of time
and memory, and at the same level of detail. SWANS simulates a million node
network on a 2.0 GHz uni-processor with 2 GB of RAM. For further
information and explanations, please refer to the SWANS user guide and other online documentation.
SWANS performance
nodes
simulator
time
memory
500
SWANS (hier)
43 s
1,101 KB
GloMoSim
82 s
5,759 KB
ns2
7136 s
5,8761 KB
5,000
SWANS (hier)
430 s
5,284 KB
GloMoSim
6191 s
27,570 KB
50,000
SWANS (hier)
4377 s
49,262 KB
1,000,000
SWANS (hier)
--
933 MB
Rimon Barr
<rb83(at)cornell.edu>,
Zygmunt J. Haas
<haas(at)ece.cornell.edu>.
