Originally published at: Cut Model Deployment Costs While Keeping Performance With GPU Memory Swap | NVIDIA Technical Blog
Deploying large language models (LLMs) at scale presents a dual challenge: ensuring fast responsiveness during high demand, while managing the costs of GPUs. Organizations often face a trade-off between provisioning additional GPUs for peak demand or risking service level agreement during spikes in traffic, where they decide between: Deploying many replicas with GPUs to handle…