Bentō: Optimizing Persistent Memory Programs
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866910037985722368 |
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| author | Amaro, Sebastião Gonçalves, João Matos, Miguel |
| author_facet | Amaro, Sebastião Gonçalves, João Matos, Miguel |
| contents | Persistent Memory (PM) is a new storage technology thatbrings high performance, byte addressability, and persistency for a lesser cost than DRAM. Due to cache volatility and store reordering, developers must use explicit instructions (e.g.: flush and fence) to guarantee that the application state remains consistent upon crashes. This is difficult to get right and, in fact, several tools have been created to detect bugs in PM programs. To overcome this difficulty, programmers tend to be overly conservative, for instance, by enforcing unnecessary ordering constraints, which partially forfeits the performance benefits of using PM. In this paper, we study the impact that different combinations of persistency instructions have in several PM programs and found that a specific combination can lead to performance improvements while preserving the original crash-consistency semantics. Based on these results we developed Bentō an automatic and black-box binary rewriter that can boost the performance of existing PM programs by up to 15% with minimal programmer effort. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_01889 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Bentō: Optimizing Persistent Memory Programs Amaro, Sebastião Gonçalves, João Matos, Miguel Emerging Technologies Programming Languages Persistent Memory (PM) is a new storage technology thatbrings high performance, byte addressability, and persistency for a lesser cost than DRAM. Due to cache volatility and store reordering, developers must use explicit instructions (e.g.: flush and fence) to guarantee that the application state remains consistent upon crashes. This is difficult to get right and, in fact, several tools have been created to detect bugs in PM programs. To overcome this difficulty, programmers tend to be overly conservative, for instance, by enforcing unnecessary ordering constraints, which partially forfeits the performance benefits of using PM. In this paper, we study the impact that different combinations of persistency instructions have in several PM programs and found that a specific combination can lead to performance improvements while preserving the original crash-consistency semantics. Based on these results we developed Bentō an automatic and black-box binary rewriter that can boost the performance of existing PM programs by up to 15% with minimal programmer effort. |
| title | Bentō: Optimizing Persistent Memory Programs |
| topic | Emerging Technologies Programming Languages |
| url | https://arxiv.org/abs/2603.01889 |