18 research outputs found
Adding Virtualization Capabilities to Grid'5000
Ce rapport rĂ©visĂ© a fait l'objet d'une publication, voir hal-00946971Almost ten years after its premises, the Grid'5000 testbed has become one of the most complete testbed for designing or evaluating large-scale distributed systems. Initially dedicated to the study of High Performance Computing, the infrastructure has evolved to address wider concerns related to Desktop Computing, the Internet of Services and more recently the Cloud Computing paradigm. This report present recent improvements of the Grid'5000 software and services stack to support large-scale experiments using virtualization technologies as building blocks. Such contributions include the deployment of customized software environments, the reservation of dedicated network domain and the possibility to isolate them from the others, and the automation of experiments with a REST API. We illustrate the interest of these contributions by describing three different use-cases of large-scale experiments on the Grid'5000 testbed. The first one leverages virtual machines to conduct larger experiments spread over 4000 peers. The second one describes the deployment of 10000 KVM instances over 4 Grid'5000 sites. Finally, the last use case introduces a one-click deployment tool to easily deploy major IaaS solutions. The conclusion highlights some important challenges of Grid'5000 related to the use of OpenFlow and to the management of applications dealing with tremendous amount of data.Dix ans environ aprĂšs ses prĂ©misses, la plate-forme Grid'5000 est devenue une des plates-formes les plus complĂštes utilisĂ©e pour la conception et l'Ă©valuation de systĂšmes distribuĂ©s Ă grande Ă©chelle. DĂ©diĂ©e initialement au calcul Ă haute performance, l'infrastructure a Ă©voluĂ© pour supporter un ensemble de problĂšmes plus vaste liĂ©s au calcul de type Desktop, l'internet des objets et plus rĂ©cemment l'informatique dans les nuages (aussi appelĂ© Cloud Computing). Ce rapport prĂ©sente les amĂ©liorations rĂ©centes apportĂ©es au logiciels et pile de services pour supporter les expĂ©rimentations Ă grande Ă©chelle utilisant les technologies de virtualisation comme blocs de base. Nos contributions incluent le dĂ©ploiement d'environnements logiciels customisĂ©s, la rĂ©servation de domaines rĂ©seaux dĂ©diĂ©s et la possibilitĂ© de les isoler entre eux, et l'automatisation des expĂ©rimentations grĂące Ă une API REST. Nous illustrons l'intĂ©rĂȘt de ces contributions en dĂ©crivant trois expĂ©riences Ă large Ă©chelle sur la plate-forme Grid'5000. La premiĂšre expĂ©rience utilise des machines virtuelles pour conduire des expĂ©rimentations de grande taille sur 4000 pairs. La seconde expĂ©rience dĂ©crit le dĂ©ploiement de 10000 instances KVM sur 4 sites Grid'5000. Enfin le dernier exemple prĂ©sente un outil de dĂ©ploiement simple pour dĂ©ployer des solutions de Cloud de type IaaS. La conclusion discute de prochains dĂ©fis importants de Grid'5000 liĂ©s Ă l'utilisation d'OpenFlow et Ă la gestion d'applications gĂ©rant des grandes masses de donnĂ©es
Adding Virtualization Capabilities to Grid'5000
Ce rapport rĂ©visĂ© a fait l'objet d'une publication, voir hal-00946971Almost ten years after its premises, the Grid'5000 testbed has become one of the most complete testbed for designing or evaluating large-scale distributed systems. Initially dedicated to the study of High Performance Computing, the infrastructure has evolved to address wider concerns related to Desktop Computing, the Internet of Services and more recently the Cloud Computing paradigm. This report present recent improvements of the Grid'5000 software and services stack to support large-scale experiments using virtualization technologies as building blocks. Such contributions include the deployment of customized software environments, the reservation of dedicated network domain and the possibility to isolate them from the others, and the automation of experiments with a REST API. We illustrate the interest of these contributions by describing three different use-cases of large-scale experiments on the Grid'5000 testbed. The first one leverages virtual machines to conduct larger experiments spread over 4000 peers. The second one describes the deployment of 10000 KVM instances over 4 Grid'5000 sites. Finally, the last use case introduces a one-click deployment tool to easily deploy major IaaS solutions. The conclusion highlights some important challenges of Grid'5000 related to the use of OpenFlow and to the management of applications dealing with tremendous amount of data.Dix ans environ aprĂšs ses prĂ©misses, la plate-forme Grid'5000 est devenue une des plates-formes les plus complĂštes utilisĂ©e pour la conception et l'Ă©valuation de systĂšmes distribuĂ©s Ă grande Ă©chelle. DĂ©diĂ©e initialement au calcul Ă haute performance, l'infrastructure a Ă©voluĂ© pour supporter un ensemble de problĂšmes plus vaste liĂ©s au calcul de type Desktop, l'internet des objets et plus rĂ©cemment l'informatique dans les nuages (aussi appelĂ© Cloud Computing). Ce rapport prĂ©sente les amĂ©liorations rĂ©centes apportĂ©es au logiciels et pile de services pour supporter les expĂ©rimentations Ă grande Ă©chelle utilisant les technologies de virtualisation comme blocs de base. Nos contributions incluent le dĂ©ploiement d'environnements logiciels customisĂ©s, la rĂ©servation de domaines rĂ©seaux dĂ©diĂ©s et la possibilitĂ© de les isoler entre eux, et l'automatisation des expĂ©rimentations grĂące Ă une API REST. Nous illustrons l'intĂ©rĂȘt de ces contributions en dĂ©crivant trois expĂ©riences Ă large Ă©chelle sur la plate-forme Grid'5000. La premiĂšre expĂ©rience utilise des machines virtuelles pour conduire des expĂ©rimentations de grande taille sur 4000 pairs. La seconde expĂ©rience dĂ©crit le dĂ©ploiement de 10000 instances KVM sur 4 sites Grid'5000. Enfin le dernier exemple prĂ©sente un outil de dĂ©ploiement simple pour dĂ©ployer des solutions de Cloud de type IaaS. La conclusion discute de prochains dĂ©fis importants de Grid'5000 liĂ©s Ă l'utilisation d'OpenFlow et Ă la gestion d'applications gĂ©rant des grandes masses de donnĂ©es
Supporting Experimental Computer Science
The ability to conduct consistent, controlled, and repeatable large-scale experiments in all areas of computer science related to parallel, large-scale, or distributed computing and networking is critical to the future and development of computer science. Yet conducting such experiments is still too often a challenge for researchers, students, and practitioners because of the unavailability of dedicated resources, inability to create controlled experimental conditions, and variability in software. Availability, repeatability, and open sharing of electronic products are all still difficult to achieve. To discuss those challenges and share experiences in their solution, the Workshop on Experimental Support for Computer Science brought together scientists involved in building and operating infrastructures dedicated to sup- porting computer science experiments to discuss challenges and solutions in this space. The workshop was held in November 2011 and was collocated with the SC11 conference in Seattle, Washington. Our objec- tives were to share experiences and knowledge related to supporting large-scale experiments conducted on experimental infrastructures, understand user requirements, and discuss methodologies and opportunities created by emerging technologies. This report ties together the workshop presentations and discussion and the consensus that emerged on the state of the field and directions for moving forward.La possibilité d'effectuer des expériences à grande échelle consistantes, contrÎlées, et reproductibles dans tous les domaines de l'informatique liés au parallélisme et au calcul distribué est critique pour le futur et le développement de l'informatique. Le lancement de telles expérimentations est souvent difficile pour les chercheurs, les étudiants et les développeurs et ceci en partie à cause de l'absence de ressources dédiées, l'impossibilité de créer des conditions expérimentales contrÎlées et l'évolution des logiciels. La disponibilité, la reproductibilité, et le partage ouvert de plates-formes informatiques sont toujours difficiles à atteindre. Afin de discuter de ces challenges et de partager nos expériences sur les solutions à ces problÚmes, le workshop "Experimental Support for Computer Science" a réuni des scientifiques impliqués dans la construction et la maintenance de plates-formes expérimentales dédiées au support pour les expériences informatiques pour discuter des challenges et de leurs solutions. Ce workshop s'est tenu en novembre 2011 au sein de la conférence SC11 à Seattle, Washington. Notre objectif était de partager notre expériences et nos connais- sances autour du support pour les expériences à grande échelle lancées sur des plates-formes d'expérimentation, comprendre les besoins des utilisateurs et discuter des méthodes et des opportunités créées par ces technologies émergentes. Ce rapport présente les contributions liées aux présentations du workshop et aux discussions qui ont eu lieu et le consensus issu sur l'état de l'art et des directions pour les travaux futurs
DĂ©ploiement et partitionnement dynamique de clusters avec Kadeploy et Kavlan
National audienceGrid'5000 est une plate-forme expĂ©rimentale pour la recherche sur les systĂšmes distribuĂ©s (P2P, grilles, Cloud, HPC, ...) composĂ©e de 1600 machines dans 10 sites en France. La principale spĂ©cificitĂ© de la plate-forme est d'ĂȘtre reconfigurable par les utilisateurs, leur permettant ainsi de rĂ©aliser des expĂ©riences complexes. Ce poster prĂ©sentera deux outils-clĂ© pour la reconfiguration de la plate-forme par les utilisateurs : Kadeploy et KaVLAN. Kadeploy http://kadeploy3.gforge.inria.fr est un outil libre de dĂ©ploiement de clusters. Il utilise des mĂ©canismes permettant des dĂ©ploiements rapides et passant bien Ă l'Ă©chelle : il est par exemple possible de dĂ©ployer un cluster de 140 machines en moins de 5 minutes. Il utilise des technologies et des protocoles comme IPMI ou RSA pour contrĂŽler les machines de maniĂšre centralisĂ©e, PXE et TFTP pour le processus de boot, et des mĂ©canismes de diffusion de donnĂ©es P2P (soit en organisant les noeuds sous forme de chaĂźne, soit en utilisant BitTorrent). Kavlan est un outil d'isolation rĂ©seau permettant de sĂ©parer un rĂ©seau physique rĂ©el en diffĂ©rents rĂ©seaux indĂ©pendants, en configurant automatiquement les routeurs et les switchs. Il permet ainsi de rĂ©aliser des expĂ©riences sur des logiciels nĂ©cessitant une infrastructure lourde (DHCP diffĂ©rent, par exemple) ou reposant sur l'utilisation de mĂ©canisme de diffusion. L'utilisation de Kadeploy et Kavlan sur Grid'5000 rĂ©pond Ă des besoins assez spĂ©cifiques de la communautĂ© de recherche sur les systĂšmes distribuĂ©s. Toutefois, ils peuvent ĂȘtre utiles dans d'autres contextes, notamment pour installer ou mettre Ă jour des clusters de production ou des grands nombres de machines oĂč l'aspect "passage Ă l'Ă©chelle" est important
Adding Virtualization Capabilities to the Grid'5000 Testbed
International audienc
Supporting Experimental Computer Science
The ability to conduct consistent, controlled, and repeatable large-scale experiments in all areas of computer science related to parallel, large-scale, or distributed computing and networking is critical to the future and development of computer science. Yet conducting such experiments is still too often a challenge for researchers, students, and practitioners because of the unavailability of dedicated resources, inability to create controlled experimental conditions, and variability in software. Availability, repeatability, and open sharing of electronic products are all still difficult to achieve. To discuss those challenges and share experiences in their solution, the Workshop on Experimental Support for Computer Science brought together scientists involved in building and operating infrastructures dedicated to supporting computer science experiments to discuss challenges and solutions in this space. The workshop was held in November 2011 and was collocated with the SC11 conference in Seattle, Wash. Our objectives were to share experiences and knowledge related to supporting large-scale experiments conducted on experimental infrastructures, understand user requirements, and discuss methodologies and opportunities created by emerging technologies. This report ties together the workshop presentations and discussion and the consensus that emerged on the state of the field and directions for moving forward