Amazon SageMaker AI 推出容器缓存,加速模型扩展

Introducing container caching in Amazon SageMaker AI for faster model scaling

精选理由

AWS给SageMaker AI加了容器缓存,扩展时延迟直接减半,适合需要快速响应的生成式AI部署。

AI 摘要

Amazon SageMaker AI 发布容器镜像缓存功能,针对推理场景优化扩展速度。该功能在模型扩缩容时可将端到端延迟最高提升2倍。它专为生成式AI模型设计,减少冷启动时间。现已可在AWS区域使用。

图片来源 · AWS Machine Learning Blog
原文 · AWS Machine Learning Blog

Introducing container caching in Amazon SageMaker AI for faster model scaling

Today, we’re excited to announce container image caching for Amazon SageMaker AI inference, the next major advancement in our faster scaling optimization journey. This speeds up end-to-end latency by up to 2x for generative AI models during scale-out events.

Amazon SageMaker AI 推出容器缓存,加速模型扩展 · AI 热点