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GPU Memory Optimization

Stop Paying for GPU Memory Your AI Workloads Don’t Use

Inference workloads reserve significantly more GPU memory than they consume. ScaleOps autonomously corrects overprovisioned GPU memory requests, reclaiming capacity for sharing and reducing the memory footprint of each workload.

The Problem with Reserved GPU Memory for Inference Workloads

Reserved Allocation Wastes GPU Memory

GPU memory is sized for worst-case demand that rarely arrives. GPU memory sits reserved and idle instead of being available for other workloads.

High Allocation, Low Utilization, No Sharing

Workloads reserve far more GPU memory than they consume. Fractional GPU policies see the allocation and can’t bin-pack, so GPUs sit almost idle and unsharable

Manual Tuning Can’t Match Dynamic Memory Behavior

Teams waste time manually tuning memory for every workload. Traffic shifts and model changes alter how workloads consume memory. Configurations set at deploy time are outdated quickly. 

Autonomously Unlock GPU Sharing 

ScaleOps enables GPU sharing for memory-bound workloads that are blocked by overprovisioning. Once memory reservation aligns with actual usage, fractional GPU policies apply without manual changes.

Continuous Memory Reservation Rightsizing

ScaleOps continuously analyzes each workload’s actual GPU consumption and manages inference memory reservations based on live behavior. Over-provisioned allocations are corrected automatically, so workloads stop holding capacity they never used.

Maximize GPU Utilization

Autonomous Workload Memory Profiling

Inference frameworks like vLLM and TensorFlow allocate all available GPU memory by default, regardless of actual usage. ScaleOps observes each inference workload’s actual GPU memory consumption in live production, tracking how usage shifts across different load conditions and concurrency levels. No manual profiling. No static assumptions.

Cloud Resource Management Reinvented

Boost Performance & Reliability

Ensure consistent performance and uptime, even in the most dynamic environments.

Free Your Engineers

Eliminate repeated manual tuning forever, allowing you to focus on innovation.

Cut Costs by 80%

Pay only for the cloud resources you need without compromising performance.

Install with a single helm
command. That’s it.