AKC:用于云计算的高级KSM

Sioh Lee, Bongkyu Kim, Youngpil Kim, C. Yoo
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引用次数: 1

摘要

Linux内核存档中的内核同页合并(Kernel samepage merge, KSM)是一种查找重复页面并共享页面的内存重复数据删除方案,以缓解云环境中的内存瓶颈。然而,由于KSM必须扫描内存中的所有页面才能找到重复的页面,因此KSM消耗很高的CPU周期,从而导致虚拟机(vm)性能下降[1]。这种虚拟机性能的下降是云服务实时应用程序(即Netflix)的障碍[3]。先前的工作CMD[1]提出了页面分组方案来减少页面比较,但它需要特殊的监控硬件,XLH[2]增强了与guest VM I/O操作信息的页面共享。然而,XLH的CPU开销仍然非常高——与默认的KSM类似。为了使KSM更有用,我们需要一个消耗更少CPU周期的优化方案。因此,我们首先分析了KSM的CPU周期消耗,结果表明页面比较(28.77%)和页面校验和(26.14%)占用了大部分周期。基于结果,我们提出了用于云计算(AKC)的高级KSM,它比默认KSM消耗更少的CPU周期。为了减少页面比较的次数,我们采用了基于校验和的rb树结构。此外,AKC通过硬件加速的crc32哈希函数减少了页面校验和开销。
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AKC: advanced KSM for cloud computing
Kernel samepage merging (KSM) in Linux kernel archive is a memory deduplication scheme that finds duplicate pages and shares the page in order to alleviate memory bottleneck in cloud. However, because the KSM has to scan all pages in memory to find duplicate pages, KSM consumes high CPU cycles and so causes virtual machines (VMs) performance degradation [1]. This degradation of VMs performance is an obstacle in cloud to service real-time applications (i.e. Netflix) [3]. A previous work, CMD [1] proposed page grouping scheme to reduce page comparisons, but it requires special monitoring hardware, XLH [2] enhanced page sharing with the information of guest VM I/O operation. However, the CPU overhead of XLH is still very high - similar to the default KSM. to make KSM more useful, we need an optimization scheme that consume less CPU cycles. Therefore, we first profile the CPU cycle consumption of KSM and the results show that page comparison (28.77%) and page checksum (26.14%) take most of cycles. Based on the results, we propose advanced KSM for cloud computing (AKC) that consumes less CPU cycles than the default KSM. to reduce the number of page comparisons, we apply checksum based RB-tree structure. In addition, AKC decreases page checksum overhead with hardware-accelerated crc32 hash function.
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