scholarly journals Parallel simulation techniques for large-scale discrete-event models

2011 ◽  
Author(s):  
Shafagh Jafer
Keyword(s):  
Large Scale ◽  
Discrete Event ◽  
Parallel Simulation ◽  
Simulation Techniques ◽  
Event Models

PARALLEL SIMULATION OF LARGE-SCALE ARTIFICIAL SOCIETY WITH GPU AS COPROCESSOR

2013 ◽  
Vol 04 (02) ◽  
pp. 1350005 ◽  
Author(s):  
GANG GUO ◽  
BIN CHEN ◽  
XIAOGANG QIU
Keyword(s):  
Message Passing ◽  
High Performance ◽  
Large Scale ◽  
Discrete Event ◽  
Parallel Simulation ◽  
System Specification ◽  
Artificial Society ◽  
Simulation Engine ◽  
Event System ◽  
Efficient Communication

Large-scale artificial societies with millions or billions of agents call for high-performance parallel simulation. Prevailing supercomputers with thousands of CPUs and GPUs make it possible to carry out such simulation. The key is to distribute large-scale agents to massive cores of CPUs and GPUs properly for parallel computing with efficient communication and synchronization. For simplicity and efficiency, a modified discrete event system specification (DEVS) is proposed for large-scale artificial society modeling and parallelism is exploited in agent models because similar agents usually share similar behaviors. Through phased synchronization, a two-tier parallel simulation engine is designed with support of MPI and OpenCL where GPU is used as coprocessor. One-sided communication is used for reflection of remote simulation objects and message passing between processes. A general kernel function prototype is elaborately designed and conditionally compiled for execution on both CPU and GPU. An artificial society for epidemic study is used to test the performance on a supercomputer with 1024 CPU cores and 1792 GPU cores. The speedup reaches 3512 for even 2 billion agents with GPU acceleration which is far over 701 when only CPUs are used. It turns out feasible for parallel simulation of large-scale artificial society with GPU as coprocessor.

COMBINING MODELICA MODELS WITH DISCRETE EVENT FORMALISMS FOR SIMULATION USING THE DES/M ENVIRONMENT

2005 ◽  
Vol 15 (02) ◽  
pp. 349-355 ◽  
Author(s):  
MANUEL A. PEREIRA REMELHE ◽  
SEBASTIAN ENGELL
Keyword(s):  
Modeling And Simulation ◽  
Discrete Event ◽  
Object Oriented ◽  
Software Tools ◽  
Modeling Languages ◽  
Physical Systems ◽  
Simulation Techniques ◽  
Discrete Event Control ◽  
Event Models ◽  
Technical Systems

Technical systems that include complex physical dynamics as well as extensive discrete event control, require powerful modeling and simulation techniques. As the most adequate means for modeling hybrid physical systems, we advocate the use of object-oriented modeling languages such as Modelica. However, the discrete event models often require the use of dedicated graphical editors that cannot be defined appropriately using Modelica. The purpose of the DES/M modeling environment [10] is to provide such editors for different discrete event formalisms and to translate discrete event models automatically into Modelica components such that a discrete event controller can be integrated easily into Modelica models and simulated using standard Modelica software tools. This contribution presents the main concepts used for the representation of several discrete event formalisms in the Modelica language and discusses the class of discrete event formalisms that can be supported by the DES/M environment.

Parallel simulation techniques for large-scale networks

1998 ◽  
Vol 36 (8) ◽  
pp. 42-47 ◽  
Author(s):  
S. Bhatt ◽  
R. Fujimoto ◽  
A. Ogielski ◽  
K. Perumalla
Keyword(s):  
Large Scale ◽  
Parallel Simulation ◽  
Simulation Techniques ◽  
Large Scale Networks

scholarly journals Collisionless Dynamics and the Cosmic Web

2014 ◽  
Vol 11 (S308) ◽  
pp. 87-96
Author(s):  
Oliver Hahn
Keyword(s):  
Dark Matter ◽  
Structure Formation ◽  
Large Scale ◽  
Velocity Potential ◽  
Three Dimensional ◽  
Maximum Amount ◽  
Lagrangian Manifold ◽  
Linear Regime ◽  
Fine Grained ◽  
Simulation Techniques

AbstractI review the nature of three-dimensional collapse in the Zeldovich approximation, how it relates to the underlying nature of the three-dimensional Lagrangian manifold and naturally gives rise to a hierarchical structure formation scenario that progresses through collapse from voids to pancakes, filaments and then halos. I then discuss how variations of the Zeldovich approximation (based on the gravitational or the velocity potential) have been used to define classifications of the cosmic large-scale structure into dynamically distinct parts. Finally, I turn to recent efforts to devise new approaches relying on tessellations of the Lagrangian manifold to follow the fine-grained dynamics of the dark matter fluid into the highly non-linear regime and both extract the maximum amount of information from existing simulations as well as devise new simulation techniques for cold collisionless dynamics.

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