AI 中文总结
研究多层自愈人工智能基础设施故障注入规划问题，提出ADA-ST自适应方法，用加权故障传播图指导跨层场景选择，构建平台故障传播图，弥补现有测试覆盖不足，通过迭代达全边覆盖，还能跨硬件代际传递知识，揭示跨层漏洞。
AI 中文摘要
现代GPU加速平台依赖跨越硬件、固件、管理软件和编排的多层自愈管道。故障跨层传播时会绕过检测、破坏诊断或触发冲突修复，而传统故障注入活动孤立地测试各层。本文提出ADA-ST，一种自适应故障注入方法，用加权故障传播图指导跨层场景选择。为超大规模运营商的三个平台构建四层图，以积累72550张维修工单的生产系统Alpha为实证基础。结果表明现有静态测试活动仅覆盖20%-25%的建模故障传播边，ADA-ST通过迭代活动指导场景选择弥补差距，在不同平台达到全边覆盖。故障层抽象映射在硬件代际间传递传播知识，最新平台物理现场验证确认测试传播边，揭示跨层漏洞。
英文摘要
Modern GPU-accelerator platforms rely on multi-layer self-healing pipelines that span hardware, firmware, management software, and orchestration. When faults propagate across layer boundaries, they can bypass detection, corrupt diagnosis, or trigger conflicting remediations--yet conventional fault-injection campaigns test each layer in isolation. We present ADA-ST, an adaptive fault-injection methodology that uses a weighted fault-propagation graph to guide cross-layer scenario selection. We construct four-layer graphs for three successive platforms at a hyperscale operator: Alpha, Beta, and Gamma. Platform Alpha, a production system that accumulated 72,550 repair tickets over four years, provides the empirical foundation; 49% of those tickets involve cross-layer fault propagation. We show that existing static test campaigns cover only 20-25% of the modeled fault-propagation edges, leaving approximately three-quarters of the cross-layer attack surface unexercised. ADA-ST closes this gap through iterative, activity-guided scenario selection that maximizes marginal coverage gain per iteration, reaching full edge coverage within 10 iterations on Alpha, 12 on Beta, and 9 on Gamma. The Fault-Layer Abstraction Mapping (FLAM) transfers propagation knowledge across hardware generations with 100% fidelity from Alpha to Beta and 96% from Beta to Gamma. Physical spot-validation on the newest platform confirms all four tested propagation edges, revealing cross-layer vulnerabilities spanning telemetry blind spots, absence-based detection gaps, multi-signal correlation failures, and trust-without-verification propagation at the L2-to-L3 boundary.
