NVIDIA：AI 负载上线前如何验证 GPU 集群就绪状态
Validate GPU Cluster Readiness Before AI Workloads Land
即便每块 GPU、网络链路和 pod 都显示健康，512-GPU 训练任务仍可能性能不达标或直接失败，原因可能是单块 GPU 变慢、链路在负载下降级，或配置悄悄把流量导向更慢的路径。运维者往往要到任务跑了几小时后才会发现问题。
A GPU cluster can pass every health check and still fail to run an AI workload. Even when every GPU, network link, and pod reports healthy, a 512-GPU training...
A GPU cluster can pass every health check and still fail to run an AI workload. Even when every GPU, network link, and pod reports healthy, a 512-GPU training job can underperform or fail. The cause may be one slow GPU, a link that degrades under load, or a configuration that quietly routes traffic over a slower path. Operators may not discover the problem until hours into the run or until a…
来源：NVIDIA Developer Blog · developer.nvidia.com