Accelerating Address Translation for Virtualization by Leveraging Hardware Mode

The overhead of memory virtualization remains nontrivial. The traditional shadow paging (TSP) resorts to a shadow page table (SPT) to achieve the native page walk speed, but page table updates require hypervisor interventions. Alternatively, nested paging enables low-overhead page table updates, but...

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Bibliographic Details
Published in:IEEE transactions on computers 2022-11, Vol.71 (11), p.3047-3060
Main Authors: Sha, Sai, Zhang, Yi, Luo, Yingwei, Wang, Xiaolin, Wang, Zhenlin
Format: Article
Language:English
Subjects:
Hardware
hardware mode
hypervisor
Memory management
Memory virtualization
nested paging
Paging
Server pages
Servers
shadow paging
Shadows
Software
Switches
Synchronism
Synchronization
translation lookaside buffer
Virtual machine monitors
Virtualization
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Summary:The overhead of memory virtualization remains nontrivial. The traditional shadow paging (TSP) resorts to a shadow page table (SPT) to achieve the native page walk speed, but page table updates require hypervisor interventions. Alternatively, nested paging enables low-overhead page table updates, but utilizes the hardware MMU to perform a long-latency two-dimensional page walk. This paper proposes new memory virtualization solutions based on hardware (machine) mode-the highest CPU privilege level in some architectures like Sunway and RISC-V. A programming interface, running in hardware mode, enables software-implementation of hardware support functions. We first propose Software-based Nested Paging (SNP) , which extends the software MMU to perform a two-dimensional page walk in hardware mode. Second, we present Swift Shadow Paging (SSP) , which accomplishes page table synchronization by intercepting TLB flushing in hardware mode. Finally we propose Accelerated Shadow Paging (ASP) combining SSP and SNP. ASP handles the last-level SPT page faults by walking two-dimensional page tables in hardware mode, which eliminates most hypervisor interventions. This paper systematically compares multiple memory virtualization models by analyzing their designs and evaluating their performance both on a real system and a simulator. The experiments show that the virtualization overhead of ASP is less than 4.5% for all workloads.
ISSN:0018-9340
1557-9956
DOI:10.1109/TC.2022.3145671