With the brand new vLLM/TPU integration, you possibly can deploy your fashions on TPUs with out the necessity for in depth code modifications. A spotlight is the help for the favored vLLM library on TPUs, permitting interoperability throughout GPUs and TPUs. By opening up the facility of TPUs for inference on GKE, Google Cloud is offering in depth selections for purchasers seeking to optimize their price-to-performance ratio for demanding AI workloads.
AI-aware load balancing with GKE Inference Gateway
In contrast to conventional load balancers that distribute visitors in a round-robin style, GKE Inference Gateway is clever and AI-aware. It understands the distinctive traits of generative AI workloads, the place a easy request can lead to a prolonged, computationally intensive response.
The GKE Inference Gateway intelligently routes requests to essentially the most acceptable mannequin reproduction, taking into consideration elements like the present load and the anticipated processing time, which is proxied by the KV cache utilization. This prevents a single, long-running request from blocking different, shorter requests, a standard explanation for excessive latency in AI purposes. The result’s a dramatic enchancment in efficiency and useful resource utilization.