Boundaryless Computing: Optimizing LLM Performance, Cost, and Efficiency in Multi-Cloud Architecture

Explore a conference talk on optimizing large language model (LLM) performance, cost, and efficiency in multi-cloud architectures. Dive into the challenges of meeting user demands for LLM inference across multiple geographic regions and learn how the OCM and Fluid communities collaborate to address these issues. Discover automated solutions for multi-region distribution of inference applications, combining OCM's multi-cluster deployment capabilities with Fluid's data orchestration. Gain insights into cross-regional model distribution, pre-warming techniques, and strategies to enhance deployment and upgrade efficiency. Understand the importance of boundaryless computing in overcoming GPU resource limitations and providing optimal user experiences for LLM applications.