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Scaling LLM Inference: AWS Inferentia Meets Ray Serve on EKS | Ray Summit 2024
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The race for efficient, scalable AI inference is on, and AWS is at the forefront with innovative solutions. This session showcases how to achieve high-performance, cost-effective inference for large language models like Llama2 and Mistral-7B using Ray Serve and AWS Inferentia on Amazon EKS.
Vara Bonthu and Ratnopam Chakrabarti will guide you through the intricacies of building a scalable inference infrastructure that bypasses GPU availability constraints. They'll demonstrate how the synergy between Ray Serve, AWS Neuron SDK, and Karpenter autoscaler on Amazon EKS creates a powerful, flexible environment for AI workloads. Attendees will explore strategies for optimizing costs while maintaining high performance, opening new possibilities for deploying and scaling advanced language models in production environments.
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Vara Bonthu and Ratnopam Chakrabarti will guide you through the intricacies of building a scalable inference infrastructure that bypasses GPU availability constraints. They'll demonstrate how the synergy between Ray Serve, AWS Neuron SDK, and Karpenter autoscaler on Amazon EKS creates a powerful, flexible environment for AI workloads. Attendees will explore strategies for optimizing costs while maintaining high performance, opening new possibilities for deploying and scaling advanced language models in production environments.
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Interested in more?
--
🔗 Connect with us: