Flexible computing rack for interruptible artificial intelligence computing in data centers

Abstract

Systems and methods for allocating and managing computing resources are described. The system may use a flexible computing rack which includes a plurality of server devices, an artificial intelligence engine, and power distribution units to manage and allocate data computation in a data center. The system may execute computational allocation based on interruption factors which include prioritization of tasks, electrical power consumption, device temperatures, and provide for state preservation and seamless resumption of interrupted workloads. The artificial intelligence engine may collect data representative of these characteristics of the data center, train machine learning models on rack-specific operational patterns, and provide efficiency enhancements and optimization for data computation through autonomous workload orchestration that responds to both internal rack conditions and external grid signals.

Dependencies are inferred from the claim text.