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.

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

• 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