CNS Core: Medium: Collaborative Research: Persistent memory objects for consistent sharing in Non-Volatile Main Memories

CNS 核心：中：协作研究：用于非易失性主存储器中一致共享的持久内存对象

• 批准号: 1900758
• 负责人: Michael Swift
• 金额: $ 50.97万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1900758&HistoricalAwards=false
• 关键词: CNS; Core; Medium; Collaborative; Research

The continual performance growth of data center servers is critical to the nation's economic competitiveness and as a catalyst for progress in scientific endeavors. Two important data center components are the main memory, which has fast access but can only store data temporarily, and storage, which keeps data permanently but suffers from slow access. Recent technology advances have brought in a new non-volatile memory, now commercially available, that can both host permanent data and be accessed quickly. However, to reach its potential, utilizing these new memory technologies requires rethinking of how data should be persistently and efficiently stored. This proposal describes a new abstraction for storing persistent data in non-volatile memory: hyperfiles, which are long lived, provide fast access, and can be quickly attached to and detached from a process address space. Hyperfiles provide naming and permission characteristics similar to (but faster than) files, and speed closer to memory. They are accessed directly through loads/stores to avoid system call overhead. This project also investigates new sharing semantics for hyperfiles, allowing non-cooperating processes to share them simultaneously and safely, while keeping the crash recovery property. Architecture support to accelerate hyperfile sharing will also be designed and evaluated. This project will enable fast access to persistent data by reducing overheads inherent in file access, and will enable more concurrent use of data through strong sharing semantics. Big-data workloads becoming common across all industries will either perform better or require fewer resources. The software and prototyping artifacts produced will enable other researchers to further enhance the design, and to adapt workloads to take advantage of the hyperfile abstraction. The education and outreach components of this plan will train the next generation of programmers on use of persistent memory, and will encourage underrepresented students to join the next generation of programmers. The project will maintain data, code, results, publications, and simulator artifacts for the duration of the project plus five years afterward. Each artifact will be released as it reaches sufficient maturity. They will be posted at: https://sites.google.com/view/hyperfile.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

项目成果

CBMM: Financial Advice for Kernel Memory Managers

CBMM：内核内存管理器的财务建议

• 发表时间: 2022
• 期刊: Proceedings of the USENIX Annual Technical Conference
• 作者: Mark Mansi, Bijan Tabatabai

FBMM: Using the VFS for Extensibility in Kernel Memory Management

FBMM：使用 VFS 实现内核内存管理的可扩展性

• DOI: 10.1145/3593856.3595908
• 发表时间: 2023
• 期刊: HOTOS '23: Proceedings of the 19th Workshop on Hot Topics in Operating Systems
• 作者: Tabatabai, Bijan;Mansi, Mark;Swift, Michael M.
• 通讯作者: Swift, Michael M.

MadFS: Per-File Virtualization for Userspace Persistent Memory Filesystems

• 发表时间: 2023
• 作者: Shawn Zhong;Chenhao Ye;Guanzhou Hu;Suyan Qu;Andrea C. Arpaci-Dusseau;Remzi H. Arpaci-Dusseau;M. Swift

DaxVM: Stressing the Limits of Memory as a File Interface

• DOI: 10.1109/micro56248.2022.00037
• 发表时间: 2022-10
• 期刊: 2022 55th IEEE/ACM International Symposium on Microarchitecture (MICRO)
• 作者: Chloe Alverti;Vasileios Karakostas;Nikhita Kunati;G. Goumas;M. Swift

ASAP: A Speculative Approach to Persistence

• DOI: 10.1109/hpca53966.2022.00070
• 发表时间: 2022-04
• 期刊: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA)
• 作者: Sujay Yadalam;Nisarg Shah;Xiangyao Yu;M. Swift