动态记忆压力感知气球

Jinchun Kim, Viacheslav V. Fedorov, Paul V. Gratz, A. Reddy
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引用次数: 17

摘要

硬件虚拟化是大规模服务器和数据中心部署的主要组成部分,因为它们有助于服务器整合和可伸缩性。然而,就系统主内存利用率而言,虚拟化的代价很高。当前的虚拟机(VM)内存管理解决方案带来了很高的性能损失,并且忽略了系统的操作机制。因此,非常需要低影响的VM内存管理技术,这种技术能够感知并响应当前系统状态,从而降低虚拟化的开销。我们观察到主机在不同的内存压力下运行,因为客户机vm的内存需求在运行时动态变化。适应这种运行时系统状态对于降低VM内存管理的性能成本至关重要。本文提出了一种新的动态内存管理策略,称为内存压力感知(MPA)膨胀。MPA膨胀机制根据当前内存压力动态分配内存资源给每个虚拟机。此外,MPA膨胀可以主动响应和适应来宾虚拟机内存需求的突然变化。MPA膨胀既不需要额外的硬件支持,也不会在内存压力估计中导致额外的小页面错误。我们表明,与当前的膨胀技术相比,MPA膨胀在一组运行在客户机vm中的应用程序混合中提供了13.2%的几何速度提升;通常产生与非内存约束系统几乎相同的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dynamic Memory Pressure Aware Ballooning
Hardware virtualization is a major component of large scale server and data center deployments due to their facilitation of server consolidation and scalability. Virtualization, however, comes at a high cost in terms of system main memory utilization. Current virtual machine (VM) memory management solutions impose a high performance penalty and are oblivious to the operating regime of the system. Therefore, there is a great need for low-impact VM memory management techniques which are aware of and reactive to current system state, to drive down the overheads of virtualization. We observe that the host machine operates under different memory pressure regimes, as the memory demand from guest VMs changes dynamically at runtime. Adapting to this runtime system state is critical to reduce the performance cost of VM memory management. In this paper, we propose a novel dynamic memory management policy called Memory Pressure Aware (MPA) ballooning. MPA ballooning dynamically allocates memory resources to each VM based on the current memory pressure regime. Moreover, MPA ballooning proactively reacts and adapts to sudden changes in memory demand from guest VMs. MPA ballooning requires neither additional hardware support, nor incurs extra minor page faults in its memory pressure estimation. We show that MPA ballooning provides an 13.2% geomean speed-up versus the current ballooning techniques across a set of application mixes running in guest VMs; often yielding performance nearly identical to that of a non-memory constrained system.
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