AI Workloads Management at the Edge Solution Brief

This solution brief outlines a collaborative platform developed by Supermicro and NAMUTECH for managing AI inference workloads at the edge using Kubernetes. It addresses challenges such as unreliable internet connections and the high costs associated with data movement and cloud processing, particularly for sensitive data. The solution aims to optimize GPU utilization through features like NVIDIA GPU sharing capabilities, which allow for efficient management of workloads. The document details various use cases across industries, including mining, robotics, healthcare, and retail, demonstrating how edge AI can enhance operational efficiency and decision-making. Additionally, it describes the architecture of the solution, including the deployment of Kubernetes clusters on Supermicro servers and the integration of Cocktail Cloud for application management. The performance evaluation highlights the effectiveness of the solution in achieving optimal performance and operational efficiency, emphasizing its capabilities in simplifying AI application deployment and management.