Maximize AI Infrastructure Throughput by Consolidating Underutilized GPU Workloads

Build an intelligent K8s scheduler plugin that detects underutilized GPU resources and dynamically packs heterogeneous inference workloads into them. This solves the massive waste found in standard Kubernetes deployments.

Suggested repo: GPU-Packer

"Stop wasting GPU cycles on idle clusters with intelligent workload consolidation."

Estimated effort: 120h