Taming Hot Bloat Under Virtualization with HugeScope

Document Type

Conference Proceeding

Publication Date

2024

Department

Department of Computer Science

Abstract

Huge pages are effective in reducing the address translation overhead under virtualization. However, huge pages suffer from the hot bloat problem, where accesses to a huge page are skewed towards a few base pages (i.e., 4KB page), making the hypervisor (mistakenly) classify the whole huge page as hot. Hot bloat renders several critical techniques used in virtualization ineffective, including tiered memory and page sharing. Prior work addressing hot bloat either requires hardware modification or targets a specific scenario and is not applicable to a hypervisor. This paper presents HugeScope, a lightweight, effective and generic system that addresses the hot bloat problem under virtualization based on commodity hardware. HugeScope includes an efficient and precise page tracking mechanism, leveraging the other level of indirect memory translation in the hypervisor. HugeScope provides a generic framework to support page splitting and coalescing policies, considering the memory pressure, as well as the recency, frequency, and skewness of page access. Moreover, HugeScope is general and modular, thereby can be easily applied to various scenarios concerning hot bloat, including tiered memory management (HS-TMM) and page sharing (HS-Share). Evaluation shows that HugeScope incurs less than 4% overhead, and by addressing hot bloat, HS-TMM improves performance by up to 61% over vTMM while HS-Share saves 41% more memory than Ingens while offering comparable performance.

Publication Title

Proceedings of the 2024 USENIX Annual Technical Conference, ATC 2024

ISBN

9781939133410

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