HMTRace: Hardware-Assisted Memory-Tagging based Dynamic Data Race Detection
Fuente:
arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| Soggetti: | |
| Accesso online: | |
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| _version_ | 1866916229536546816 |
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| author | Shastri, Jaidev Wang, Xiaoguang Shivakumar, Basavesh Ammanaghatta Verbeek, Freek Ravindran, Binoy |
| author_facet | Shastri, Jaidev Wang, Xiaoguang Shivakumar, Basavesh Ammanaghatta Verbeek, Freek Ravindran, Binoy |
| contents | Data race, a category of insidious software concurrency bugs, is often challenging and resource-intensive to detect and debug. Existing dynamic race detection tools incur significant execution time and memory overhead while exhibiting high false positives. This paper proposes HMTRace, a novel Armv8.5-A memory tag extension (MTE) based dynamic data race detection framework, emphasizing low compute and memory requirements while maintaining high accuracy and precision. HMTRace supports race detection in userspace OpenMP- and Pthread-based multi-threaded C applications. HMTRace showcases a combined f1-score of 0.86 while incurring a mean execution time overhead of 4.01% and peak memory (RSS) overhead of 54.31%. HMTRace also does not report false positives, asserting all reported races. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_19139 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | HMTRace: Hardware-Assisted Memory-Tagging based Dynamic Data Race Detection Shastri, Jaidev Wang, Xiaoguang Shivakumar, Basavesh Ammanaghatta Verbeek, Freek Ravindran, Binoy Distributed, Parallel, and Cluster Computing Data race, a category of insidious software concurrency bugs, is often challenging and resource-intensive to detect and debug. Existing dynamic race detection tools incur significant execution time and memory overhead while exhibiting high false positives. This paper proposes HMTRace, a novel Armv8.5-A memory tag extension (MTE) based dynamic data race detection framework, emphasizing low compute and memory requirements while maintaining high accuracy and precision. HMTRace supports race detection in userspace OpenMP- and Pthread-based multi-threaded C applications. HMTRace showcases a combined f1-score of 0.86 while incurring a mean execution time overhead of 4.01% and peak memory (RSS) overhead of 54.31%. HMTRace also does not report false positives, asserting all reported races. |
| title | HMTRace: Hardware-Assisted Memory-Tagging based Dynamic Data Race Detection |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2404.19139 |