Working Group Serving, with Yuan Tang and Eduardo Arango
Kubernetes Podcast from Google
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Orchestration and Multi-Host Inference Challenges
This chapter explores the complexities of orchestration and multi-host inference for large language models (LLMs), focusing on standardizing APIs and enhancing community project collaboration. It discusses deployment patterns, network topology challenges, and the critical role of GPUs in efficiently managing model growth. Special emphasis is placed on innovative solutions such as Model Mesh for load balancing and optimizing response times in multi-host serving environments.
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