Reference : IV Grid Plugtests: composing dedicated tools to run an application efficiently on Gri...

	Document type :	Scientific Presentations in Universities or Research Centers : Scientific presentation in universities or research centers
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/10993/39969

Title :	IV Grid Plugtests: composing dedicated tools to run an application efficiently on Grid'5000
Language :	English
Author, co-author :	Besseron, Xavier [Laboratoire d'Informatique de Grenoble > MOAIS project]
	Danjean, Vincent [Laboratoire d'Informatique de Grenoble > MOAIS project]
	Gautier, Thierry [Laboratoire d'Informatique de Grenoble > MOAIS project]
	Guelton, Serge [Laboratoire d'Informatique de Grenoble > MOAIS project]
	Huard, Guillaume [Laboratoire d'Informatique de Grenoble > MOAIS project]
	Wagner, Frédéric [Laboratoire d'Informatique de Grenoble > MOAIS project]
Publication date :	12-Feb-2008
Audience :	International
Event name :	3rd EGEE User Forum
Event date :	from 11-02-2008 to 14-02-2008
Event place (city) :	Clermont-Ferrand
Event country :	France
Keywords :	[en] Grid ; Deployment ; Work-stealing scheduling ; Tools for the grids
Abstract :	[en] Exploiting efficiently the resources of whole Grid'5000 with the same application requires to solve several issues: 1) resources reservation; 2) application's processes deployment; 3) application's tasks scheduling. For the IV Grid Plugtests, we used a dedicated tool for each issue to solve. The N-Queens contest rules imposed ProActive for the resources reservations (issue 1). Issue 2 was solved using TakTuk which allows to deploy a large set of remote nodes. Deployed nodes take part in the deployment using an adaptive algorithm that makes it very efficient. For the 3rd issue, we wrote our application with Athapascan API whose model is based on the concepts of tasks and shared data. The application is described as a data-flow graph using the Shared and Fork keywords. This high level abstraction of hardware gives us an efficient execution with the Kaapi runtime engine using a work-stealing scheduling algorithm to balance the workload between all the distributed processes.
Permalink :	http://hdl.handle.net/10993/39969
Other URL :	https://indico.cern.ch/event/22351/contributions/463884/

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