On performance debugging of unnecessary lock contentions on multicore processors: A replay-based approach

Zheng, Long; Liao, Xiaofei; He, Bingsheng; Wu, Song; Jin, Hai

doi:10.1109/cgo.2015.7054187

Cited by 9 publications

(5 citation statements)

References 23 publications

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“…Last but not least, SyncPerf contributes with an additional tool to help diagnose some specific type of performance issues. Zheng et al [44] replay traces to identify lock contentions and calculate potential improvement that can be achieved by reducing the contentions. HaLock [21] utilizes a hardware memory tracing tool to store profiling data, in order to avoid memory interference with the applications.…”

Section: Related Workmentioning

confidence: 99%

SyncPerf

Alam

Liu

Zeng³

et al. 2017

Proceedings of the Twelfth European Conference on Computer Systems

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Despite the obvious importance, performance issues related to synchronization primitives are still lacking adequate attention. No literature extensively investigates categories, root causes, and fixing strategies of such performance issues. Existing work primarily focuses on one type of problems, while ignoring other important categories. Moreover, they leave the burden of identifying root causes to programmers. This paper first conducts an extensive study of categories, root causes, and fixing strategies of performance issues related to explicit synchronization primitives. Based on this study, we develop two tools to identify root causes of a range of performance issues. Compare with existing work, our proposal, SyncPerf, has three unique advantages. First, SyncPerf's detection is very lightweight, with 2.3% performance overhead on average. Second, SyncPerf integrates information based on callsites, lock variables, and types of threads. Such integration helps identify more latent problems. Last but not least, when multiple root causes generate the same behavior, SyncPerf provides a second analysis tool that collects detailed accesses inside critical sections and helps identify possible root causes. SyncPerf discovers many unknown but significant synchronization performance issues. Fixing them provides a performance gain anywhere from 2.5% to 42%. Low overhead, better coverage, and informative reports make SyncPerf an effective tool to find synchronization performance bugs in the production environment. ⇤ Alam and Liu contributed equally to this work.

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Section: Related Workmentioning

confidence: 99%

SyncPerf

Alam

Liu

Zeng³

et al. 2017

Proceedings of the Twelfth European Conference on Computer Systems

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“…We use its Pin-based version. Pin 12) is an underlying framework, which enables programmers to perform the program analysis at runtime without any source codes.…”

Section: Methodsmentioning

confidence: 99%

“…Therefore it is necessary to know the explicit characteristics of lock-related thread interleavings (e.g., lock interleavings [12]). We first take the several typical lock interleavings into account for the demand of practical detection, and then classify them into four categories.…”

Section: Fig 1 An Execution Snapshot In Different Ordersmentioning

confidence: 99%

Understanding and identifying latent data races cross-thread interleaving

Zheng

Fan

et al. 2015

Front. Comput. Sci.

Self Cite

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Data races are ubiquitous in multi-threaded applications, but they are by no means easy to detect. One of the most important reasons is the complexity of thread interleavings. A volume of research has been devoted to the interleaving-insensitive detection. However, all the previous work focuses on the uniform detection (unknown to the characteristics of thread interleavings), thereby making the detection defective in either reporting false positives or suffering from prohibitive overhead. To cope with the problem above, we propose an efficient, precise, and sound step-by-step resolution based on the characteristics of thread interleavings. We first try to tease apart the categories of thread interleavings from the several typical sources arising from the lock synchronizations. We then conduct a brief study and find a new and complex pattern the previous work cannot detect. It is also revealed that the simple pattern with the majority of thread interleavings can be resolved by a simple processing to achieve a big profit for the previous reordering-based design. Our final experimental results demonstrate the effectiveness of our empiricism-based approach, and show that 51.0% of execution time and 52.3% of trace size arising from the stateof-the-art reordering technique can be saved through a quick filtering of the simple pattern with a negligible (4.45%) performance overhead introduced on-the-fly.

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“…Performance debugging techniques are applied to reduce the scope of code locations and the dependency on expert knowledge. Such techniques include replay, 38 profiling, 39,40 and mining. 3 Performance Estimation includes research in building and applying performance prediction models.…”

Section: Rq11: Research Categories and Distributionmentioning

confidence: 99%

A systematic mapping study of software performance research

Han

Yan

2023

Softw Pract Exp

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Summary Context: Software performance is crucial for ensuring the quality of software products. As one of the non‐functional requirements, the few efforts devoted to software performance have often been neglected until a later phase in the software development life cycle (SDLC). The lack of clarity of what software performance research literature is available prevents researchers from understanding what software performance research fields are available. It also creates difficulty for practitioners to adopt state‐of‐the‐art software performance techniques. Software performance research is not as organized as other established research topics such as software testing. Thus, it is essential to conduct a systematic mapping study as a first step to provide an overview of the latest research literature available in software performance. Objective: The objective of this systematic mapping study is to survey and map software performance research literature into suitable categories and to synthesize the literature data for future access and reference. Method: This systematic mapping study conducts a manual examination by querying research literature in noble journals and proceedings in software engineering in the past decade. We examine each paper manually and identify primary studies for further analysis and synthesis according to the pre‐defined inclusion criteria. Lastly, we map the primary studies based on their corresponding classification category. Results: This systematic mapping study provides a state‐of‐the‐art literature mapping in software performance research. We have carefully examined 222 primary studies out of 2000+ research literature. We have identified six software performance research categories and 15 subcategories. We generate the primary study mapping and report five research findings. Conclusions: Unlike established research fields, it is unclear what types of software performance research categories are available to the community. This work takes the systematic mapping study approach to survey and map the latest software performance research literature. The study results provide an overview of the paper distribution and a reference for researchers to navigate research literature on software performance.

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On performance debugging of unnecessary lock contentions on multicore processors: A replay-based approach

Cited by 9 publications

References 23 publications

SyncPerf

SyncPerf

Understanding and identifying latent data races cross-thread interleaving

A systematic mapping study of software performance research

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