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Recent years have seen a proliferation of large language models (LLMs) that extend beyond traditional language tasks to generative AI. This includes models like ChatGPT and Stable Diffusion. As this generative AI focus continues to grow, there is a rising need for a cloud native infrastructure that
Provides solid and scalable multi-cluster machine learning platform.
This talks will explore how these rising needs are addressed by leverage Volcano and Karmada that enable multi-cluster job queuing, management, enhanced scheduling.
This talk will cover: - The challenges for LLM training in single Kubernetes cluster\ - How to combine Volcano and Karmada to build a multi-cluster training platform - How to handle to job queuing across multi-cluster to ensure the fairness and SLA - How to balance the workload performance and multi-cluster utilization. - Scheduling policies to avoid busy waiting and dead lock
