Maximize GPU Utilization & Infrastructure ROI

Many organizations operate GPU environments at less than 50% utilization while simultaneously facing resource shortages. We help improve scheduling efficiency, workload placement, and capacity planning to maximize the value of every GPU.

Capacity Assessment

Architecture & Capacity Planning

We evaluate cluster performance, utilization patterns, and future growth requirements to identify opportunities for improving efficiency and maximizing GPU ROI.

• GPU utilization trends
• Queue wait time analysis
• Resource fragmentation assessment
• Job scheduling efficiency review
• Cluster growth and capacity projections

Optimization Areas

Scheduler Optimization for Slurm

• Fair-share tuning
• QoS (Quality of Service) configuration
• Backfill scheduling optimization
• Partition design and workload segmentation

Scheduler Optimization for Kubernetes

• Kueue implementation
• Volcano Scheduler deployment and tuning
• Gang scheduling configuration
• Bin packing optimization

Cost Optimization

• GPU fleet right-sizing
• Reserved capacity planning
• Capacity forecasting and budgeting

Outcomes

• Higher GPU utilization
• Lower cost per training run
• Reduced queue wait times
• Improved workload throughput