Challenges and Solutions for AI Storage Systems in Cloud‑Native Training
The talk outlines how AI training’s growing data and compute demands create storage bottlenecks across four evolutionary stages, identifies four core problems—massive data, data‑flow, resource scheduling, and compute acceleration—and proposes hardware, software (parallel file systems, caching), and cloud‑native orchestration (Fluid, Baidu Canghai) solutions that combine object‑storage lakes with high‑performance acceleration layers to achieve near‑full GPU utilization.