SlideServe
Menu
Préférences
© SlideServe · v2026

Nomad: A Scalable Operating System for Clusters of Uni and Multiprocessors

peony avatar
9 diapositives · 225 Views · Jul 13, 2014

Nomad is a cutting-edge, scalable operating system designed for clusters of uni- and multiprocessors. It emphasizes scalability, ease of use, and fault tolerance without the need for centralization or dedicated nodes for tasks. Nomad leverages unique process identifiers and efficient resource management, ensuring optimal load balancing and automated task allocation across available nodes. It features a robust file system capable of operating under fault conditions and aims to minimize application downtime through periodic checkpoints and online recovery. Future work includes exploring advanced communication protocols to further enhance performance.

Nomad: A Scalable Operating System for Clusters of Uni and Multiprocessors - slide 1
01 / 9Nomad: A Scalable Operating System for Clusters of Uni and Multiprocessors
1 / 17

Télécharger la présentation

Nomad: A Scalable Operating System for Clusters of Uni and Multiprocessors
Une image / un lien ci-dessous est fourni (tel quel) pour télécharger la présentation

Politique de téléchargement : le contenu du site vous est fourni TEL QUEL pour votre information et votre usage personnel ; il ne peut être vendu, concédé sous licence ni partagé sur d’autres sites sans l’accord de son auteur.Le contenu vous est fourni TEL QUEL, pour votre information et votre usage personnel uniquement. Téléchargez la présentation en cliquant sur ce lien. Lors du téléchargement, si vous ne parvenez pas à télécharger une présentation, l’éditeur a peut-être supprimé le fichier de son serveur.Pendant le téléchargement, si vous ne parvenez pas à obtenir une présentation, le fichier a peut-être été supprimé par l’éditeur.

F I N

Plus de contenu associé

Transcription de la présentation
  1. Nomad: A Scalable Operating System for Clusters of Uni and Multiprocessors Eduardo Pinheiro Ricardo Bianchini Rutgers University

  2. Goals • Scalability • No centralization. • No dedicated nodes to tasks. • Ease of use • Single system image. Backward compatible. • Efficient and automatic management of all resources • CPU, Memories, I/O devices. • Fault tolerant • Resistant to individual node crashes. Redundant.

  3. Applications Nomad Daemon Base Operating System Overview

  4. Mechanisms • Single system image • Unique process identifiers across cluster. • Signal delivery is independent of process location. • Process creation automatically picks best node. • Efficient resource utilization • Load balancing by migration due to resource (CPU, memory or I/O bandwidth) exhaustion. • Implicit co-scheduling across nodes. • Co-scheduling on multiprocessors.

  5. Mechanisms • Scalability • No centralization. Nodes are autonomous. • High throughput striped and randomized file system (software RAID). • Need for extra intra-cluster communication obviated by piggybacked load dissemination information via file system messages.

  6. Mechanisms • Fault Tolerance • Periodic checkpoints to stable storage. • If faults occur, applications can be restarted with minimum losses. • Redundant file system is capable of operating with up to one faulty disk/node. Recovery happens online.

  7. Results

  8. Results • Simulated Results for Load Balancing Obs: Overdemand time is due to sum of CPU, memory and I/O demands and is expressed in seconds.

  9. Publications & Future Work • Eduardo Pinheiro and Ricardo Bianchini, “Nomad: An Efficient Operating System for Clusters of Uni and Multiprocessors", In Proceedings of the 1st IEEE Computer Society International Workshop on Cluster Computing (IWCC'99), Melbourne, Australia, December 1999. • Eduardo Pinheiro "Nomad, a Scalable Operating System for Clusters of Uni and Multiprocessors", XIII Dissertation Thesis Contest (CTD2000), Curitiba, PR, Brazil, July 16-21. Best MSc thesis of 1999. Future Work: • Explore the use user-level protocols (VIA) for communication between daemons. • Explore the use of remote memory writes in more aggressively managing the cluster resources. Award Winning