Optimizing I/O for AI Workloads in GPU Clusters

This technical whitepaper explores the challenges faced by AI/ML infrastructure teams in optimizing GPU utilization across geo-distributed clusters. It discusses common causes of low GPU performance, the impact of data management complexities, and solutions to enhance efficiency. The paper includes a case study of a global e-commerce giant that accelerated AI model training, providing insights into best practices for managing I/O in multi-GPU environments.