|Reference : Architecture of a Grid-Enabled Lattice-Boltzmann Middleware|
|Scientific congresses and symposiums : Poster|
|Engineering, computing & technology : Computer science|
|Architecture of a Grid-Enabled Lattice-Boltzmann Middleware|
|Dethier, Gérard [Université de Liège - ULg > Département de chimie appliquée > Génie chimique - Opérations physiques unitaires >]|
|Marchot, Pierre [Université de Liège - ULg > Département de chimie appliquée > Génie chimique - Systèmes polyphasiques >]|
|de Marneffe, Pierre-Arnoul [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Informatique (ingénierie du logiciel et algorithmique) >]|
|Advanced COmputational Methods in ENgineering (Acomen) 2008|
|du 26 mai 2008 au 28 mai 2008|
|[en] Grid Computing ; Lattice Boltzmann|
|[en] Lattice-Boltzmann (LB) simulation methods constitute a family of computational fluid dynamics
methods that can deal with complex multiphysics models and are easily parallelizable. They are based
on modified lattice-gas automata.
The algorithm of LB simulations is quite simple. Space is discretized into a lattice. Each node of
this lattice has a state. This state indicates the proportion of particules moving along fixed directions
(these proportions are generally called “fields”). At each time step, the state of all lattice nodes is
updated. Each node first receives fields coming from its neighbors and then “collides” them by applying
a collision operator which generates the new state.
Grid computing can be defined as “coordinated resource sharing and problem solving in dynamic,
multi-institutional collaborations”. In practice, a Grid user (which can be a software component)
submits a job composed of tasks to the Grid. The tasks are automatically run on available computational
resources across organizational boundaries (i.e. clusters of multiple departments).
LaBoGrid is an application combining the concepts of LB modelling and Grid computing. It is able
to run LB simulations on an arbitrary number of computational resources from a Grid. It deals with
operating system and hardware performance heterogeneity. The former because LaBoGrid is written in
Java. The latter thanks to load-balancing. This is essential because all LaBoGrid tasks are inter-
connected and depend on information from one another. A slow LaBoGrid task will slow down the
LaBoGrid is based on asynchronous agents exchanging messages. The two main agents are the
Controller agent (CA) and the distributed agent (DA). In a deployed LaBoGrid system, the CA exists in
only one instance. It keeps track of the DAs and their topology.
A task agent running some arbitrary code can be attached to the CA (CAT) and the DAs (DAT).
In LaBoGrid, LB-specialized task agents are used (this system could be adapted to other problems).
A configuration file parsed by the LB CAT gives the parameters of an LB simulation. The LB CAT
configures automatically the LB DATs which handle the simulation code. Currently, LB simulations are
done on 3D fluids with 19 fields per state. However, the code can be adapted very easily to other fluid
dimensions and different state definitions, storage and computation precisions and collision types.
|Communauté française de Belgique - CfB|
|Researchers ; Professionals|
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