English(EN) I Cut Concurrency Latency by 60% in Production. Here is Why Single-User Speed Barely Moved at First.

开发者使用多工作进程 ASGI 将 LLM 并发延迟降低 60%

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-02 12:17

一位开发者通过使用 FastAPI 和 Uvicorn 实现多工作进程 ASGI 设置，显著提高了 LLM 并发延迟，将负载下的性能下降从 4.31 倍降低到 1.28 倍。这解决了单个工作进程序列化请求导致严重延迟的瓶颈。进一步的优化包括解决通过 SQLAlchemy 与 Neon 进行同步数据库调用导致 asyncio 事件循环冻结的问题，以及产生近一倍的跨大陆往返成本，将身份验证开销从近一秒降低到毫秒。 AI

影响通过优化的基础设施和降低的延迟，提高了 LLM 系统的性能。

排序理由该条目详细介绍了 LLM 系统的技术优化，而非新的模型发布或重大的行业性事件。

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dev.to — LLM tag TIER_1 English(EN) · Victor · 2026-11-02 12:17

I Cut Concurrency Latency by 60% in Production. Here is Why Single-User Speed Barely Moved at First.

<p>This is the fourth series of the production LLM Systems and RAG of Vicquant.<br /> Step 1 was fixing the concurrency queue with multi-worker ASGI. Step 2 was unblocking the event loop and facing the 8-round-trip database tax.</p> <p>In the previous article, I exposed a critica…

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I Cut Concurrency Latency by 60% in Production. Here is Why Single-User Speed Barely Moved at First.

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