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Inside LLM Inference Engines: KV Caching, PagedAttention, and Continuous Batching
A deep architectural investigation into how modern LLM inference runtimes like vLLM, TensorRT-LLM, and SGLang achieve high throughput—from memory-bound decoding and KV cache fragmentation to virtual memory paging and continuous iteration-level scheduling.