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    <title>Pagedattention on Gen-AI</title>
    <link>https://gen-ai.fyi/tags/pagedattention/</link>
    <description>Recent content in Pagedattention on Gen-AI</description>
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    <lastBuildDate>Sun, 27 Sep 2026 00:00:00 +0000</lastBuildDate>
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      <title>PagedAttention Made KV-Cache Feel Like a Memory Allocator</title>
      <link>https://gen-ai.fyi/one-layer-down/pagedattention-kv-cache-allocator/</link>
      <pubDate>Sun, 27 Sep 2026 00:00:00 +0000</pubDate>
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      <description>My first GPU-backed run used vLLM&amp;rsquo;s offline LLM.generate API. The second run put vLLM behind its OpenAI-compatible server and measured streaming TTFT and TPOT. Those experiments showed the runtime from a caller&amp;rsquo;s point of view. They did not show how serving engines manage memory.
To understand the memory problem, I first needed to follow one request through generation: how the model reads its prompt, produces each new token, and retains useful state from earlier tokens in that same request.</description>
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