Scaler: Efficient and Effective Cross Flow Analysis

Performance analysis is challenging as different components (e.g., different libraries, and applications) of a complex system can interact with each other. However, few existing tools focus on understanding such interactions. To bridge this gap, we propose a novel analysis method-"Cross Flow An...

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Bibliographic Details
Published in:IEEE/ACM International Conference on Automated Software Engineering : [proceedings] pp. 907 - 918
Main Authors: Tang, Jiaxun, Xiang, Mingcan, Wang, Yang, Wu, Bo, Chen, Jianjun, Liu, Tongping
Format: Conference Proceeding
Language:English
Published: ACM 27.10.2024
Subjects:
Accuracy
Benchmark testing
Bridges
Complex systems
Libraries
library
Monitoring
Performance analysis
profiler
Runtime
Source coding
ISSN:2643-1572
Online Access:Get full text
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Summary:Performance analysis is challenging as different components (e.g., different libraries, and applications) of a complex system can interact with each other. However, few existing tools focus on understanding such interactions. To bridge this gap, we propose a novel analysis method-"Cross Flow Analysis (XFA)"- that monitors the interactions/flows across these components. We also built the Scaler profiler that provides a holistic view of the time spent on each component (e.g., library or application) and every API inside each component. This paper proposes multiple new techniques, such as Universal Shadow Table, and Relation-Aware Data Folding. These techniques enable Scaler to achieve low runtime overhead, low memory overhead, and high profiling accuracy. Based on our extensive experimental results, Scaler detects multiple unknown performance issues inside widely-used applications, and therefore will be a useful complement to existing work.The reproduction package including the source code, benchmarks, and evaluation scripts, can be found at https://doi.org/10.5281/zenodo.13336658.
ISSN:2643-1572
DOI:10.1145/3691620.3695473