PagedAttention revolutionizes memory management in language models by utilizing non-contiguous memory spaces, thus optimizing the storage of keys and values.
The vLLM engine employs a centralized scheduler that efficiently coordinates distributed GPU workers, enhancing performance and memory management across various decoding scenarios.
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