SenseTime's Sandwich Architecture: Solving AI GPU Resource Management at Scale

The Sandwich Approach to AI Computing

SenseTime has revealed its three-tier layered architecture for managing GPU computing resources in the AI-native era. The approach addresses key pain points: resource islands, slow scaling, and complex operations management.

Three Layers

1. Foundation Layer — Physical GPU Pool with unified management and abstracted hardware interfaces
2. Middle Layer — AI Cluster Runtime with fully managed virtual clusters, dynamic scheduling, and multi-tenant isolation
3. Top Layer — Virtual Nodes with on-demand resource provisioning and application-level optimization

Core Technologies

• Fully managed virtual clusters eliminate the need for teams to manage physical hardware
• AI cluster Runtime optimized for training and inference workloads
• Virtual nodes enable granular resource allocation per task requirement

Impact

This architecture eliminates resource silos, enables dynamic scaling without manual intervention, reduces operational complexity, and improves GPU utilization rates across the organization.

Industry Significance

As demand for AI computing grows exponentially, efficient resource management through software-defined infrastructure becomes a competitive advantage over simply buying more hardware.