Amazon SageMaker HyperPod Inference Gateway Announced
A new routing system developed to increase GPU efficiency and reduce latency in running large language models has been introduced.
Amazon Web Services has announced a new routing system designed to prevent resource waste in the scalable operation of large language models and significantly reduce time-to-first-token latency.
Preventing GPU Resource Waste
Running large language models at scale on GPU cluster infrastructure incurs high costs. Standard Kubernetes load balancers can further increase this cost and inefficiency because they cannot see the actual state inside the GPU.
Features of the Routing System
The newly introduced system stands out as a Kubernetes-based and GPU-aware routing mechanism. It can be deployed on the existing HyperPod infrastructure as a single EKS managed add-on.
Real-Time GPU Signals
The system places each inference request onto the most suitable pod by utilizing real-time GPU signals. As a result, no modifications are required in the model servers or client applications.