Tag: Continuous Batching

In high-density artificial intelligence infrastructure, serving standard chat interfaces represents a largely solved problem. Modern inference engines (such as vLLM, TensorRT-LLM, and TGI) leverage continuous iteration-level batching (dynamic batching), PagedAttention, and streaming Server-Sent Events (SSE) to multiplex hundreds of concurrent human dialogues across shared GPU clusters. In human-facing chat workloads, the operational model is clear: […]