Vmem: A Lightweight Hot-Upgradable Memory Management for In-production Cloud Environment
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arXiv
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| Main Authors: | , , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866911263265652736 |
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| author | Zheng, Hao Wang, Qiang Wang, Longxiang Qiu, Xishi Shen, Yibin Dong, Xiaoshe Guan, Naixuan Wei, Jia Qiu, Fudong Zhang, Xingjun Xu, Yun Zhao, Mao Xie, Yisheng Zhao, Shenglong He, Min Li, Yu Zheng, Xiao Luo, Ben Wu, Jiesheng |
| author_facet | Zheng, Hao Wang, Qiang Wang, Longxiang Qiu, Xishi Shen, Yibin Dong, Xiaoshe Guan, Naixuan Wei, Jia Qiu, Fudong Zhang, Xingjun Xu, Yun Zhao, Mao Xie, Yisheng Zhao, Shenglong He, Min Li, Yu Zheng, Xiao Luo, Ben Wu, Jiesheng |
| contents | Traditional memory management suffers from metadata overhead, architectural complexity, and stability degradation, problems intensified in cloud environments. Existing software/hardware optimizations are insufficient for cloud computing's dual demands of flexibility and low overhead. This paper presents Vmem, a memory management architecture for in-production cloud environments that enables flexible, efficient cloud server memory utilization through lightweight reserved memory management. Vmem is the first such architecture to support online upgrades, meeting cloud requirements for high stability and rapid iterative evolution. Experiments show Vmem increases sellable memory rate by about 2%, delivers extreme elasticity and performance, achieves over 3x faster boot time for VFIO-based virtual machines (VMs), and improves network performance by about 10% for DPU-accelerated VMs. Vmem has been deployed at large scale for seven years, demonstrating efficiency and stability on over 300,000 cloud servers supporting hundreds of millions of VMs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_09961 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Vmem: A Lightweight Hot-Upgradable Memory Management for In-production Cloud Environment Zheng, Hao Wang, Qiang Wang, Longxiang Qiu, Xishi Shen, Yibin Dong, Xiaoshe Guan, Naixuan Wei, Jia Qiu, Fudong Zhang, Xingjun Xu, Yun Zhao, Mao Xie, Yisheng Zhao, Shenglong He, Min Li, Yu Zheng, Xiao Luo, Ben Wu, Jiesheng Operating Systems Traditional memory management suffers from metadata overhead, architectural complexity, and stability degradation, problems intensified in cloud environments. Existing software/hardware optimizations are insufficient for cloud computing's dual demands of flexibility and low overhead. This paper presents Vmem, a memory management architecture for in-production cloud environments that enables flexible, efficient cloud server memory utilization through lightweight reserved memory management. Vmem is the first such architecture to support online upgrades, meeting cloud requirements for high stability and rapid iterative evolution. Experiments show Vmem increases sellable memory rate by about 2%, delivers extreme elasticity and performance, achieves over 3x faster boot time for VFIO-based virtual machines (VMs), and improves network performance by about 10% for DPU-accelerated VMs. Vmem has been deployed at large scale for seven years, demonstrating efficiency and stability on over 300,000 cloud servers supporting hundreds of millions of VMs. |
| title | Vmem: A Lightweight Hot-Upgradable Memory Management for In-production Cloud Environment |
| topic | Operating Systems |
| url | https://arxiv.org/abs/2511.09961 |