Object Model Analysis of a Supercomputer with Digital Twin

2026-09-11

AI Summary

为解决超算结构与行为理解难题，提出基于虚幻引擎的三维数字孪生系统DAT，通过可视化和模拟提升操作员对硬件组件状态的理解。

Abstract

Operators and developers need a mental model of both the structure and the live behavior of a large supercomputer, but its physical layout, logical organization, and streams of per-node telemetry are difficult to relate to one another, making it hard to trace a metric or event back to a specific hardware component. We present DAT, an interactive three-dimensional digital analytics twin of a compute cluster built in a real-time game engine, Unreal Engine. DAT expands a compact, parametric description of a supercomputer, a reusable Digital Twin Prototype (DTP), into a navigable Digital Twin Instance (DTI) that mirrors its physical containment hierarchy of racks, chassis, blades, and network links, encoding each node's role and health in its appearance, while a lightweight event-driven simulator animates job and hardware activity over a virtual clock. Our current implementation adds a two-path node-selection mechanism, unifying direct 3D pointing with command-shell queries, that opens an in-world visual-analytics panel beside any selected component showing summary statistics and live, time-varying metrics. We describe this architecture, report qualitative behavior from the working prototype, and outline the path toward driving the panels with recorded telemetry and in-situ anomaly detection.

Problem

• supercomputer
• digital twin
• telemetry
• mental model
• hardware component

Innovation

• Digital Twin
• Interactive 3D Visualization
• Real-time Game Engine
• Event-driven Simulation
• Node Selection Mechanism