88,963 research outputs found
Experiences with Implementing Parallel Discrete-event Simulation on GPU
Modern graphics processing units (GPUs) offer much more computational power than recent CPUs by providing a vast number of simple, data-parallel, multithreaded cores. In this study, we focus on the use of a GPU to perform parallel discrete-event simulation. Our approach is to use a modified service time distribution function to allow more independent events to be processed in parallel. The implementation issues and alternative strategies will be discussed in detail. We describe and compare our experience and results in using Thrust and CUB, two open-source parallel algorithms libraries which resemble the C++ Standard Template Library, to build our tool. The experimental results show that our implementation can be two orders of magnitude faster than the sequential simulation for large-scale simulation models
A 3D discrete model of the diaphragm and human trunk
In this paper, a 3D discrete model is presented to model the movements of the
trunk during breathing. In this model, objects are represented by physical
particles on their contours. A simple notion of force generated by a linear
actuator allows the model to create forces on each particle by way of a
geometrical attractor. Tissue elasticity and contractility are modeled by local
shape memory and muscular fibers attractors. A specific dynamic MRI study was
used to build a simple trunk model comprised of by three compartments: lungs,
diaphragm and abdomen. This model was registered on the real geometry.
Simulation results were compared qualitatively as well as quantitatively to the
experimental data, in terms of volume and geometry. A good correlation was
obtained between the model and the real data. Thanks to this model, pathology
such as hemidiaphragm paralysis can also be simulated.Comment: published in: "Lung Modelling", France (2006
ROOT - A C++ Framework for Petabyte Data Storage, Statistical Analysis and Visualization
ROOT is an object-oriented C++ framework conceived in the high-energy physics
(HEP) community, designed for storing and analyzing petabytes of data in an
efficient way. Any instance of a C++ class can be stored into a ROOT file in a
machine-independent compressed binary format. In ROOT the TTree object
container is optimized for statistical data analysis over very large data sets
by using vertical data storage techniques. These containers can span a large
number of files on local disks, the web, or a number of different shared file
systems. In order to analyze this data, the user can chose out of a wide set of
mathematical and statistical functions, including linear algebra classes,
numerical algorithms such as integration and minimization, and various methods
for performing regression analysis (fitting). In particular, ROOT offers
packages for complex data modeling and fitting, as well as multivariate
classification based on machine learning techniques. A central piece in these
analysis tools are the histogram classes which provide binning of one- and
multi-dimensional data. Results can be saved in high-quality graphical formats
like Postscript and PDF or in bitmap formats like JPG or GIF. The result can
also be stored into ROOT macros that allow a full recreation and rework of the
graphics. Users typically create their analysis macros step by step, making use
of the interactive C++ interpreter CINT, while running over small data samples.
Once the development is finished, they can run these macros at full compiled
speed over large data sets, using on-the-fly compilation, or by creating a
stand-alone batch program. Finally, if processing farms are available, the user
can reduce the execution time of intrinsically parallel tasks - e.g. data
mining in HEP - by using PROOF, which will take care of optimally distributing
the work over the available resources in a transparent way
Exploring the Interplay between CAD and FreeFem++ as an Energy Decision-Making Tool for Architectural Design
The energy modelling software tools commonly used for architectural purposes do not allow
a straightforward real-time implementation within the architectural design programs. In addition,
the surrounding exterior spaces of the building, including the inner courtyards, hardly present
a specific treatment distinguishing these spaces from the general external temperature in the thermal
simulations. This is a clear disadvantage when it comes to streamlining the design process in relation
to the whole-building energy optimization. In this context, the present study aims to demonstrate
the advantages of the FreeFem++ open source program for performing simulations in architectural
environments. These simulations include microclimate tests that describe the interactions between
a building architecture and its local exterior. The great potential of this mathematical tool can be
realized through its complete system integration within CAD (Computer-Aided Design) software
such as SketchUp or AutoCAD. In order to establish the suitability of FreeFem++ for the performance
of simulations, the most widely employed energy simulation tools able to consider a proposed
architectural geometry in a specific environment are compared. On the basis of this analysis,
it can be concluded that FreeFem++ is the only program displaying the best features for the
thermal performance simulation of these specific outdoor spaces, excluding the currently unavailable
easy interaction with architectural drawing programs. The main contribution of this research is,
in fact, the enhancement of FreeFem++ usability by proposing a simple intuitive method for the
creation of building geometries and their respective meshing (pre-processing). FreeFem++ is also
considered a tool for data analysis (post-processing) able to help engineers and architects with
building energy-efficiency-related tasks
Overview of crowd simulation in computer graphics
High-powered technology use computer graphics in education, entertainment, games, simulation, and virtual heritage applications has led it to become an important area of research. In simulation, according to Tecchia et al. (2002), it is important to create an interactive, complex, and realistic virtual world so that the user can have an immersive experience during navigation through the world. As the size and complexity of the environments in the virtual world increased, it becomes more necessary to populate them with peoples, and this is the reason why rendering the crowd in real-time is very crucial. Generally, crowd simulation consists of three important areas. They are realism of behavioral (Thompson and Marchant 1995), high-quality visualization (Dobbyn et al. 2005) and convergence of both areas. Realism of behavioral is mainly used for simple 2D visualizations because most of the attentions are concentrated on simulating the behaviors of the group. High quality visualization is regularly used for movie productions and computer games. It gives intention on producing more convincing visual rather than realism of behaviors. The convergences of both areas are mainly used for application like training systems. In order to make the training system more effective, the element of valid replication of the behaviors and high-quality visualization is added
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