Affiliation:
1. Peking University and Beijing Huawei Digital Technologies, China
2. Peking University, China
3. Michigan Technological University, USA
Abstract
The tiered-memory system can effectively expand the memory capacity for virtual machines (VMs). However, virtualization introduces new challenges specifically in enforcing performance isolation, minimizing context switching, and providing resource overcommit. None of the state-of-the-art designs consider virtualization and address these challenges; we observe that a VM with tiered memory incurs up to a 2× slowdown compared to a DRAM-only VM.
We propose
vTMM
, a hardware-software collaborative tiered-memory management framework for virtualization. A key insight in
vTMM
is to leverage the unique system features in virtualization to meet the above challenges.
vTMM
automatically determines page hotness and migrates pages between fast and slow memory to achieve better performance. Specially,
vTMM
optimizes page tracking and migration based on page-modification logging (PML), a hardware-assisted virtualization mechanism, and adaptively distinguishes hot/cold pages through the page “temperature” sorting.
vTMM
also dynamically adjusts fast memory among multi-VMs on demand by using a memory pool. Further,
vTMM
tracks huge pages at regular-page granularity in hardware and splits/merges pages in software, realizing hybrid-grained page management and optimization. We implement and evaluate
vTMM
with single-grained page management on an Intel processor, and the hybrid-grained page management on a Sunway processor with hardware mode supporting hardware/software co-designs. Experiments show that
vTMM
outperforms existing tiered-memory management designs in virtualization.
Funder
National Key R&D Program of China
National Science Foundation of China
Publisher
Association for Computing Machinery (ACM)
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Application-Attuned Memory Management for Containerized HPC Workflows;2024 IEEE International Parallel and Distributed Processing Symposium (IPDPS);2024-05-27