Finding and Fixing Performance Pathologies in Persistent Memory Software Stacks

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Abstract

Emerging fast, non-volatile memories will enable systems with large amounts of non-volatile main memory (NVMM) attached to the CPU memory bus, bringing the possibility of dramatic performance gains for IO-intensive applications. This paper analyzes the impact of state-of-the-art NVMM storage systems on some of these applications and explores how those applications can best leverage the performance that NVMMs offer. Our analysis leads to several conclusions about how systems and applications should adapt to NVMMs. We propose FiLe Emulation with DAX (FLEX), a technique for moving file operations into user space, and show it and other simple changes can dramatically improve application performance. We examine the scalability of NVMM file systems in light of the rising core counts and pronounced NUMA effects in modern systems, and propose changes to Linux's virtual file system (VFS) to improve scalability. We also show that adding NUMA-aware interfaces to an NVMM file system can significantly improve performance.

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APA

Xu, J., Kim, J., Memaripour, A., & Swanson, S. (2019). Finding and Fixing Performance Pathologies in Persistent Memory Software Stacks. In International Conference on Architectural Support for Programming Languages and Operating Systems - ASPLOS (pp. 427–439). Association for Computing Machinery. https://doi.org/10.1145/3297858.3304077

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