LLFree: Scalable and Optionally-Persistent Page-Frame Allocation
Lars Wrenger, Florian Rommel, Alexander Halbuer, Christian Dietrich, Daniel Lohmann
Abstract
Within the operating-system's memory-management subsystem, the page-frame allocator is the most fundamental component. It administers the physical-memory frames, which are required to populate the page-table tree. Although the appearance of heterogeneous, nonvolatile, and huge memories has drastically changed the memory hierarchy, we still manage our physical memory with the seminal methods from the 1960s.
With this paper, we argue that it is time to revisit the design of page-frame allocators. We demonstrate that the Linux frame allocator not only scales poorly on multi-core systems, but it also comes with a high memory overhead, suffers from huge-frame fragmentation, and uses scattered data structures that hinder its usage as a persistent-memory allocator. With LLFREE, we provide a new lock-and log-free allocator design that scales well, has a small memory footprint, and is readily applicable to nonvolatile memory. LLFREE uses cache-friendly data structures and exhibits antifragmentation behavior without inducing additional performance overheads. Compared to the Linux frame allocator, LLFREE reduces the allocation time for concurrent 4 KiB allocations by up to 88 percent and for 2 MiB allocations by up to 98 percent. For memory compaction, LLFREE decreases the number of required page movements by 64 percent.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 6e571d32-2c62-43ce-b5af-5dd3e68cad98Cited by top-tier papers8
- Cloud-Native Database Systems and Unikernels: Reimagining OS Abstractions for Modern HardwareViktor Leis, Christian DietrichVLDB 2024 · 12 citations
- StreamCache: Revisiting Page Cache for File Scanning on Fast Storage DevicesZhiyue Li, Guangyan ZhangUSENIX ATC 2024 · 9 citations
- FineMem: Breaking the Allocation Overhead vs. Memory Waste Dilemma in Fine-Grained Disaggregated Memory ManagementXiaoyang Wang, Yongkun Li, Kan Wu, Wenzhe Zhu et al.OSDI 2025 · 3 citations
- MettEagle: Costs and Benefits of Implementing Containers on MicrokernelsTill Miemietz, Viktor Reusch, Matthias Hille, Lars Wrenger et al.OSDI 2025 · 2 citations
- Expeditious High-Concurrency MicroVM SnapStart in Persistent Memory with an Augmented HypervisorXingguo Pang, Yanze Zhang, Liu Liu, Dazhao Cheng et al.USENIX ATC 2024 · 2 citations
Builds on6
- An Empirical Guide to the Behavior and Use of Scalable Persistent MemoryJian Yang, Juno Kim, Morteza Hoseinzadeh, Joseph Izraelevitz et al.FAST 2020 · 470 citations
- Lock-free Concurrent Level Hashing for Persistent MemoryZhangyu Chen, Yu Hua, Bo Ding, Pengfei ZuoUSENIX ATC 2020 · 98 citations
- Pronto: Easy and Fast Persistence for Volatile Data StructuresAmir Saman Memaripour, Joseph Izraelevitz, Steven SwansonASPLOS 2020 · 55 citations
- Twizzler: a Data-Centric OS for Non-Volatile MemoryDaniel Bittman, Peter Alvaro, Pankaj Mehra, Darrell D. E. Long et al.USENIX ATC 2020 · 50 citations
- Virtual-Memory Assisted Buffer ManagementViktor Leis, Adnan Alhomssi, Tobias Ziegler, Yannick Loeck et al.SIGMOD 2023 · 37 citations
Related papers
- NVAlloc: rethinking heap metadata management in persistent memory allocatorsZheng Dang, Shuibing He, Peiyi Hong, Zhenxin Li et al.ASPLOS 2022 · 35 citations
- Preventing Use-After-Free Attacks with Fast Forward AllocationBrian Wickman, Hong Hu, Insu Yun, Daehee Jang et al.USENIX Security 2021 · 53 citations
- Compaction-Free Memory Defragmentation for Virtualization via Infinite Guest Physical Address SpacePeixin Zeng, Hao Huang, Yanqi Pan, Wen Xia et al.OSDI 2026
- Contiguitas: The Pursuit of Physical Memory Contiguity in DatacentersKaiyang Zhao, Kaiwen Xue, Ziqi Wang, Dan Schatzberg et al.ISCA 2023 · 26 citations
- MemPerf: Profiling Allocator-Induced Performance SlowdownsJin Zhou, Sam Silvestro, Steven (Jiaxun) Tang, Hanmei Yang et al.OOPSLA 2023
