SchedMD/slurm
Slurm
Slurm est un gestionnaire de charge de travail de cluster et un planificateur de tâches conçu pour les environnements de calcul haute performance. Il fonctionne comme un orchestrateur de calcul distribué qui met en file d'attente et exécute des tâches computationnelles à grande échelle sur plusieurs nœuds de calcul dans un cluster.
Le système agit comme un arbitre de ressources, distribuant les nœuds matériels et les processeurs entre les utilisateurs simultanés pour éviter les conflits de ressources et maximiser l'efficacité. Il coordonne le lancement simultané de multiples processus sur différents serveurs physiques pour exécuter des jobs parallèles et des charges de travail scientifiques.
La plateforme couvre de vastes domaines de capacités, notamment la planification de jobs par lots, l'allocation de ressources de calcul et l'exécution de charges de travail parallèles. Il gère le timing et l'exécution des jobs en fonction de la disponibilité des ressources et de la priorité.
Features
- HPC Resource Allocation - Manages hardware resource allocation and job priority specifically for high-performance computing environments.
- High-Performance Computing - Executes computationally intensive tasks across distributed hardware architectures using a cluster manager.
- Managed Cluster Batch Execution - Queues and executes large-scale computational batch workloads across multiple compute nodes in a cluster.
- Process Coordination - Synchronizes the simultaneous launch of multiple processes across different physical servers for parallel jobs.
- HPC Cluster Orchestrations - Provides orchestration and resource management of large-scale computational workloads across high-performance computing clusters.
- Cluster Workload Managers - Controls the execution and timing of high performance computing jobs to ensure optimal hardware utilization.
- Priority-Based Job Schedulers - Queues and executes batch computational workloads based on priority and resource availability.
- Batch Schedulers - Queues and executes computational batch tasks based on priority and available hardware.
- Job Execution Controllers - Provides runtime control over the start, stop, and monitoring of work across allocated compute nodes.
- Remote Job Dispatchers - Dispatches control signals from a central manager to specific nodes to trigger task execution.
- Resource Allocation - Distributes hardware nodes and processors across a cluster to ensure efficient utilization.
- Queue Priority Scheduling - Orders pending workloads in a logical queue and dispatches them according to user priorities.
- Parallel Job Orchestrators - Coordinates the simultaneous launch and execution of parallel workloads across multiple processes and distributed compute nodes.
- Distributed Workload Execution - Runs single computational tasks across multiple compute nodes simultaneously to reduce processing time.
- Resource Access Arbitrators - Resolves conflicting requests for available system resources through a centralized coordinator.
- Distributed Node Agents - Uses lightweight agents on every compute node to manage local job execution and report health status.
- Distributed Job Executors - Executes and monitors computational workloads by integrating with distributed compute nodes.
- Scientific Workload Schedulers - Schedules the timing and execution of complex scientific workloads across a network of distributed servers.
- State-Based Resource Tracking - Maintains a real-time database of node availability and allocations to prevent hardware oversubscription.
- Infrastructure and Deployment - Scalable workload manager for high-performance computing.
- Gestion d'infrastructure - Gestionnaire de charge de travail évolutif pour le calcul haute performance (HPC).
- Resource Scheduling - Highly scalable workload manager for high-performance computing.
