Based on the article, the authors replaced their RAG pipeline with a persistent KV cache system, which stores the full document's attention state after a single prefill and reuses it for every query. …
Running large language model inference servers like vLLM and TGI in production requires specialized observability because they behave differently from standard web services, with key metrics like late…
The KV cache is a critical optimization for LLM inference that stores the Key and Value matrices from previously generated tokens, eliminating the need to recompute attention over the entire sequence …
Synchronous continuous batching in LLM inference causes inefficiency by forcing the CPU and GPU to work sequentially, leaving one idle while the other operates. This idle time can account for nearly a…