SchedMD/slurm
Slurm
Slurm is a cluster workload manager and job scheduler designed for high-performance computing environments. It functions as a distributed compute orchestrator that queues and executes large-scale computational tasks across multiple compute nodes in a cluster.
The system acts as a resource arbitrator, distributing hardware nodes and processors among concurrent users to prevent resource conflicts and maximize efficiency. It coordinates the simultaneous launch of multiple processes across different physical servers to execute parallel jobs and scientific workloads.
The platform covers broad capability areas including batch job scheduling, compute resource allocation, and parallel workload execution. It manages the timing and execution of jobs based on resource availability and priority.
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.
- Infrastructure Management - Scalable workload manager for high-performance computing.
- Resource Scheduling - Highly scalable workload manager for high-performance computing.
Star history
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