The project investigates intelligent cloud orchestration and efficient task
scheduling methods for large-scale model inference. The research focuses on
optimizing the allocation and management of computational resources in
cloud environments to support the execution of large AI models. The project
aims to develop advanced algorithms and orchestration strategies that
improve efficiency, scalability, and performance of distributed computing
systems, enabling reliable and cost-effective processing of complex machine
learning workloads.