# AI2.3 Resource-Aware Deployment

This skill focuses on deploying AI workloads in a manner that accounts for the limitations and availability of HPC resources such as compute, memory, storage, and energy. It teaches techniques to maximize efficiency and sustainability.

## Requirements

* External: Familiarity with AI workload characteristics and HPC job environments
* Internal: None

## Learning Outcomes

* Define what makes a deployment “resource-aware” in the context of HPC.
* Select appropriate compute and memory configurations based on model size and workload type.
* Use resource profiling tools to guide allocation decisions.
* Apply strategies to reduce energy consumption during training and inference.
* Explain the trade-offs between performance, resource use, and scheduling constraints.

** Caution: All text is AI generated **