HybridPersist: A Compiler Support for User-Friendly and Efficient PM Programming

Persistent memory (PM), with its data persistence, has found widespread applications. However, programmers have to manually annotate PM operations in programming to achieve crash consistency, which is labor-intensive and error-prone. In this paper, to alleviate the burden of programming PM applications, we develop HybridPersist, a compiler support for user-friendly and efficient PM programming. On the one hand, HybridPersist automatically achieves crash consistency, minimally intruding on programmers with negligible annotations. On the other hand, it enhances both performance and correctness of PM programs through a series of dedicated analysis passes. The evaluations on well-known benchmarks validate that HybridPersist offers superior programming productivity and runtime performance compared to the state-of-the-art.

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Publication Details

Journal
Proceedings of the ACM on Programming Languages
Published
2025-10-09
DOI
https://doi.org/10.1145/3763089
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
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article

HybridPersist: A Compiler Support for User-Friendly and Efficient PM Programming

Zhiqiang Zuo, Xuandong Li, Yiyu Zhang, Yongzhi Wang et al.
Proceedings of the ACM on Programming Languages
Parallel Computing and Optimization Techniques
article

HybridPersist: A Compiler Support for User-Friendly and Efficient PM Programming

Zhiqiang Zuo, Xuandong Li, Yiyu Zhang, Yongzhi Wang, Y. Gao
article en

Abstract

Persistent memory (PM), with its data persistence, has found widespread applications. However, programmers have to manually annotate PM operations in programming to achieve crash consistency, which is labor-intensive and error-prone. In this paper, to alleviate the burden of programming PM applications, we develop HybridPersist, a compiler support for user-friendly and efficient PM programming. On the one hand, HybridPersist automatically achieves crash consistency, minimally intruding on programmers with negligible annotations. On the other hand, it enhances both performance and correctness of PM programs through a series of dedicated analysis passes. The evaluations on well-known benchmarks validate that HybridPersist offers superior programming productivity and runtime performance compared to the state-of-the-art.

Proceedings of the ACM on Programming LanguagesVol. 9(OOPSLA2)
Nanjing University (CN)
Openalex Percentile: Top 69%
Parallel Computing and Optimization Techniques
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HybridPersist: A Compiler Support for User-Friendly and Efficient PM Programming — Zhiqiang Zuo, Xuandong Li, et al. · Proceedings of the ACM on Programming Languages (2025) | TGRS Research Map | TGRS