Overview

Efficient use of compute nodes on SeaWulf ensures fair access for all users and maximizes throughput. Proper resource management helps avoid wasted CPU time, memory, and GPU usage, benefiting both your work and the wider user community.

Shared Queues

Whenever possible, use shared queues to allow multiple jobs to run concurrently on the same nodes. Shared queues improve overall throughput and make the cluster more efficient for everyone. See Shared Queues for details.

Resource Allocation

Match resources to your job: Request only the number of cores, nodes, memory, and GPUs your job actually needs. Sometimes it is acceptable to allocate fewer resources than a full node, but check the queue table first to ensure it is the most efficient choice.

Interactive sessions: Allocate an entire compute node interactively only if you plan to use all cores. Otherwise, run interactive jobs in a shared queue to avoid leaving cores idle for other users.

Monitoring and Efficiency

Monitor resource usage: Track memory, CPU, and GPU consumption to prevent over- or under-allocation. Use Monitoring Resource Usage on SeaWulf or the Job Management guide for practical commands.

Optimize your code: Efficient code reduces wasted CPU time and memory usage, allowing jobs to complete faster and freeing resources for other users.

Release nodes promptly: Once your job finishes, freeing nodes helps other users and maximizes cluster throughput.