# 取消还不够：重试在过载的LLM引擎中留下了什么

> 全文为英语

**Published:** 2026年11月9日
**Author:** Xindan Zhang, Fei Wang
**Source:** arXiv — cs.AI
**Language:** en-US
**HTML:** https://aiqazaqstan.com/zh/articles/cancellation-is-not-enough-what-retries-leave-behind-in-an-overloaded-ll

arXiv:2611.08684v1 通告类型：新 摘要：LLM引擎前的客户端和代理会重试超时的调用。在暂时性过载后，这些重试会阻止引擎恢复，即使调用到达率低于其容量。因为引擎可能继续计算…

arXiv:2611.08684v1 Announce Type: new Abstract: Clients and proxies in front of an LLM engine retry calls that time out. After a transient overload, these retries can keep the engine from recovering even when calls arrive below its capacity. Since the engine may keep computing for clients that have left, propagating cancellation looks like the natural remedy. In this paper, we test it on vLLM with overload experiments on three open models, and with scheduler traces of one that follow each client attempt to the execution it creates in the engine. We find that with retries on, cancellation alone did not restore service in any run, and only 12-38% of the calls that arrived after the overload were delivered. The traces suggest why: retries that vLLM ran typically started prefill less than half a second before they timed out. Executions that vLLM later aborted took 79-85% of the prompt tokens it computed, and vLLM's prompt-token counter missed a third to half of all computed prompt tokens. A retry budget restored service by shedding retries but left many of the overload's calls undelivered. Request coalescing delivered every call from the overload onward, some late, unless cancellation had already aborted the running execution. Overload controls should thus be judged by the executions that retries add and the calls that clients receive.

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*内容来自原始来源： [arXiv — cs.AI](https://arxiv.org/abs/2611.08684). 查看原文.*

**标签：** #arXiv

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