潮汐：回收智能体MicroVM中的分阶段内存

中文摘要 AI 辅助

云智能体在隔离的MicroVM中运行每个任务。问题在于该客户机内部的循环框架：框架在等待模型时几乎处于空闲状态，然后在使用一个大小仅在运行时才知的工具时使用率上升，这使主机端的内存管理变得复杂。现有方法根据访问频率和内存占用推断回收目标，而客户机分配器将空闲框架和短生命周期工具放在同一页面上。因此，回收要么选择错误的页面，要么确定不正确的容量，要么部分回收一个大页面，从而拆分其透明大页面。本文提出Tide，一种针对智能体MicroVM的主动内存回收技术。我们的关键见解是，框架已经知道每个阶段的内存意图（哪些内存、何时以及其内容是否必须存活），因此客户机可以报告该意图作为独占的客户机物理区域，供主机直接回收。为实现这一见解，我们引入了一种称为arena的抽象和一组用于管理具有独占意图的内存的用户空间API；一个客户机内核分配器，将独占分配分组为对齐大页面的范围；以及一个管理程序扩展，将这些范围解析为主机后备存储并应用所报告的操作，保持客户机容量不变。在记录的智能体轨迹上的实验表明，Tide优于最先进的机制，同时产生较低的开销。

英文摘要

Cloud agents run each task in an isolated MicroVM. The trouble is the harness loop inside that guest: the harness is nearly idle while it waits on the model, then usage rises on a tool whose size is known only at run time, which complicates memory management from the host. Existing approaches infer reclaim targets from access frequency and memory footprint while the guest allocator places the idle harness and the short-lived tool on the same pages. Therefore, reclamation either selects the wrong pages, fixes on an incorrect capacity, or partially reclaims a huge page, splitting its transparent huge page. This paper proposes Tide, a proactive memory reclamation technique for agent MicroVMs. Our key insight is that the harness already knows each phase's memory intent (which memory, when, and whether its contents must survive), so the guest can report that intent as an exclusive guest-physical region for the host to reclaim directly. To realize this insight, we introduce an abstraction called arena and a set of user-space APIs for managing memory with exclusive intent; a guest-kernel allocator that groups exclusive allocations into huge-page-aligned extents; and a hypervisor extension that resolves those extents to host backing and applies the reported action, leaving guest capacity unchanged. Experiments on recorded agent trajectories show that Tide outperforms state-of-the-art mechanisms while incurring low overhead.

发表机构

• Institute of Parallel and Distributed Systems, Shanghai Jiao Tong University（上海交通大学并行与分布式系统研究所）

机构由 AI 辅助整理，请以论文原文为准。