Paged Attention in Large Language Models LLMs

When running LLMs at scale, the real limitation is GPU memory rather than compute, mainly because each request requires a KV cache to store token-level data. In traditional setups, a large fixed memory block is reserved per request based on the maximum sequence length, which leads to significant unused space and limits concurrency. Paged Attention […] The post Paged Attention in Large Language Models LLMs appeared first on MarkTechPost.