FBMM: Making Memory Management Extensible With Filesystems
Bijan Tabatabai, James Christopher Sorenson III, Michael M. Swift
Abstract
New memory technologies like CXL promise diverse memory configurations such as tiered memory, far memory, and processing in memory. Operating systems must be modified to support these new hardware configurations for applications to make use of them. While many parts of operating systems are extensible, memory management remains monolithic in most systems, making it cumbersome to add support for a diverse set of new memory policies and mechanisms.
Rather than creating a whole new extensible interface for memory managers, we propose to instead use the memory management callbacks provided by the Linux virtual file system (VFS) to write memory managers, called memory management filesystems (MFSs). Memory is allocated by creating and mapping a file in an MFS's mount directory and freed by deleting the file. Use of an MFS is transparent to applications. We call this system File Based Memory Management (FBMM).
Using FBMM, we created a diverse set of standalone memory managers for tiered memory, contiguous allocations, and memory bandwidth allocation, each comprising 500-1500 lines of code. Unlike current approaches that require custom kernels, with FBMM, an MFS can be compiled separately from the kernel and loaded dynamically when needed. We measure the overhead of using filesystems for memory management and found the overhead to be less than 8% when allocating a single page, and less than 0.1% when allocating as little as 128 pages. MFSs perform competitively with kernel implementations, and sometimes better due to simpler implementations.
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.
Cited by top-tier papers4
- CXLfork: Fast Remote Fork over CXL FabricsChloe Alverti, Stratos Psomadakis, Burak Ocalan, Shashwat Jaiswal et al.ASPLOS 2025 · 14 citations
- Tigon: A Distributed Database for a CXL PodYibo Huang, Haowei Chen, Newton Ni, Yan Sun et al.OSDI 2025 · 12 citations
- vCXLGen: Automated Synthesis and Verification of CXL Bridges for Heterogeneous ArchitecturesAnatole Lefort, Julian Pritzi, Nicolò Carpentieri, David Schall et al.ASPLOS 2026 · 2 citations
- Cxlalloc: Safe and Efficient Memory Allocation for a CXL PodNewton Ni, Yan Sun, Zhiting Zhu, Emmett WitchelASPLOS 2026 · 2 citations
Builds on9
- Pond: CXL-Based Memory Pooling Systems for Cloud PlatformsHuaicheng Li, Daniel S. Berger, Lisa Hsu, Daniel Ernst et al.ASPLOS 2023 · 328 citations
- TPP: Transparent Page Placement for CXL-Enabled Tiered-MemoryHasan Al Maruf, Hao Wang, Abhishek Dhanotia, Johannes Weiner et al.ASPLOS 2023 · 255 citations
- Effectively Prefetching Remote Memory with LeapHasan Al Maruf, Mosharaf ChowdhuryUSENIX ATC 2020 · 186 citations
- Clio: a hardware-software co-designed disaggregated memory systemZhiyuan Guo, Yizhou Shan, Xuhao Luo, Yutong Huang et al.ASPLOS 2022 · 110 citations
- HeMem: Scalable Tiered Memory Management for Big Data Applications and Real NVMAmanda Raybuck, Tim Stamler, Wei Zhang, Mattan Erez et al.SOSP 2021 · 93 citations
Related papers
- Nomad: Non-Exclusive Memory Tiering via Transactional Page MigrationLingfeng Xiang, Zhen Lin, Weishu Deng, Hui Lu et al.OSDI 2024 · 59 citations
- ctFS: Replacing File Indexing with Hardware Memory Translation through Contiguous File Allocation for Persistent MemoryRuibin Li, Xiang Ren, Xu Zhao, Siwei He et al.FAST 2022 · 43 citations
- Beyond Page Migration: Enhancing Tiered Memory Performance via Integrated Last-Level Cache Management and Page MigrationHwanjun Lee, Minho Kim, Yeji Jung, Seonmu Oh et al.MICRO 2025 · 2 citations
- ExtMem: Enabling Application-Aware Virtual Memory Management for Data-Intensive ApplicationsSepehr Jalalian, Shaurya Patel, Milad Rezaei Hajidehi, Margo I. Seltzer et al.USENIX ATC 2024 · 12 citations
- NeoMem: Hardware/Software Co-Design for CXL-Native Memory TieringZhe Zhou, Yiqi Chen, Tao Zhang, Yang Wang et al.MICRO 2024 · 17 citations
