Effective Huge Page Strategies for TLB Miss Reduction in Nested Virtualization

Weiwei Jia, Jiyuan Zhang, Jianchen Shan, Xiaoning Ding

Research output: Contribution to journalArticlepeer-review

Abstract

Huge page strategies, such as Linux Transparent Huge Page (THP), have become a prevalent solution to mitigate the performance bottleneck caused by increasingly high memory address translation overhead. However, in cloud environments, virtualization presents a two-fold challenge, exacerbating address translation overhead and undermining the effectiveness of huge page strategies. To effectively reduce address translation overhead, huge page strategies in the host and guest virtual machines (VMs) must work in concert for 'proper huge page alignment', i.e., huge pages in guest VMs being backed by host huge pages. This requires a cross-layer coordinating mechanism, which has been designed targeting non-nested virtualization settings. The paper introduces xGemini as an efficient solution targeting nested virtualization settings, where addressing these issues is particularly challenging, given the additional obstacles in creating synergy between host and guest VMs, due to an extra layer of page mappings by guest hypervisors. xGemini addresses these challenges by improving the shadow paging mechanism. Evaluation based on the KVM/Linux prototype implementation and diverse real-world applications shows xGemini greatly reduces TLB misses and enhances application performance in nested virtualization.

Original languageEnglish (US)
Pages (from-to)1983-1996
Number of pages14
JournalIEEE Transactions on Computers
Volume73
Issue number8
DOIs
StatePublished - 2024

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computational Theory and Mathematics

Keywords

  • huge pages
  • memory management
  • nested virtualization
  • TLB

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