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Dynamic trace-based sampling algorithm for memory usage tracking of enterprise applications

Houssem Daoud, Naser Ezzati-Jivan, Michel Dagenais

Paper (2017)

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Abstract

Excessive memory usage in software applications has become a frequent issue. A high degree of parallelism and the monitoring difficulty for the developer can quickly lead to memory shortage, or can increase the duration of garbage collection cycles. There are several solutions introduced to monitor memory usage in software. However they are neither efficient nor scalable. In this paper, we propose a dynamic tracing-based sampling algorithm to collect and analyse run time information and metrics for memory usage. It is implemented as a kernel module which gathers memory usage data from operating system structures only when a predefined condition is set or a threshold is passed. The thresholds and conditions are preset but can be changed dynamically, based on the application behavior. We tested our solutions to monitor several applications and our evaluation results show that the proposed method generates compact trace data and reduces the time needed for the analysis, without loosing precision.
Subjects: 2700 Information technology > 2705 Software and development
2700 Information technology > 2713 Algorithms
Department: Department of Computer Engineering and Software Engineering
Department of Mechanical Engineering
Funders: CRSNG/NSERC, Prompt, Ericsson, EfficiOS
Grant number: CRDPJ468687-14
PolyPublie URL: https://publications.polymtl.ca/2979/
Conference Title: 2017 IEEE High Performance Extreme Computing Conference
Conference Location: Waltham, MA, USA
Conference Date(s): 2017-09-12 - 2017-09-14
Publisher: IEEE
DOI: 10.1109/hpec.2017.8091061
Official URL: https://doi.org/10.1109/hpec.2017.8091061
Date Deposited: 12 Feb 2018 17:06
Last Modified: 25 Nov 2022 03:22
Cite in APA 7: Daoud, H., Ezzati-Jivan, N., & Dagenais, M. (2017, September). Dynamic trace-based sampling algorithm for memory usage tracking of enterprise applications [Paper]. 2017 IEEE High Performance Extreme Computing Conference, Waltham, MA, USA (7 pages). https://doi.org/10.1109/hpec.2017.8091061

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